14 Commits
Author SHA1 Message Date
ced4568andClaude Sonnet 5 2db136875f docs(phase6b): document curriculum expansion
PHASE6B_ROOT_CURRICULUM_EXPANSION.md — the phase summary: what was
authored per course, the is_required extension, the capstone unlock
fix, verified scenario coverage before/after (44 -> 88 of 98, 89.8%,
by direct query not estimate), and honest known limitations/Phase 6C
recommendations.

ROOT_CAPSTONE_READINESS.md — the readiness module and the server-side
unlock fix in full detail, including why the module's completion and
the real assessment's unlock gate are deliberately independent systems.

Updated ROOT_CURRICULUM_INVENTORY.md (Phase 6B coverage numbers),
ROOT_PROGRAM_ARCHITECTURE.md (ROOT 08/09 PARTIAL, new module lists per
course), COURSE_CONTENT_MODEL.md (is_required completion rule, a new
content-versioning section per this phase's own requirement),
COURSE_AUTHORING_STANDARD.md (classifying near-duplicate/advanced
scenarios), ENGINEERING_SOP.md (new Phase 6B section),
REMOTE_AND_SELF_PACED_ARCHITECTURE.md (cross-reference), and
platform/README.md (e2e-phase6b.js, the Phase 6B rehearsal, isolation-
per-suite regression guidance).

Co-Authored-By: Claude Sonnet 5 <[email protected]>
2026-08-26 09:09:47 -05:00
ced4568andClaude Sonnet 5 505783e5f7 test(phase6b): add ROOT curriculum acceptance coverage + real-Lab rehearsal
e2e-phase6b.js (24 checks): hierarchy for the 13 new modules across
ROOT 05-10/12/Capstone, prerequisite chains through the newly-inserted
front-door modules, lesson/knowledge-check completion in brand-new
modules, a newly-wired scenario (job-task) completing correctly, the
optional-vs-required (is_required) completion rule, persistence/
isolation/RBAC/draft-hiding proven against the new content, and the
capstone server-side unlock fix in both directions (a direct bypass
attempt rejected with blocking_stage_ids, an ordinary exam unaffected,
a legitimately unlocked attempt still accepted and its completion
reflected in the course content model).

test-phase6b-root-course-rehearsal.js + wrapper (11 checks, real k3s):
one continuous student narrative through a brand-new module (ROOT 07
Services & Service Discovery, not the Phase 6A gold module) — real Lab
launch, the Lab's own setup_commands, a real 'kubectl expose' against
the live cluster, real validate, logout/login/Resume Learning, Lab
destroy/recreate with academic progress intact — plus an instructor
narrative proving Curriculum view, Prepare Labs, and classroom/learning
tooling all still work against the expanded curriculum.

e2e-phase6a.js updated for two of this phase's own intentional,
documented behavior changes (not defects): resume now points at
root-05's new mental-model module instead of the old bare-lab bank, and
root-10's gold module now unlocks the new troubleshooting-framework
module rather than the bare-lab bank directly.

Co-Authored-By: Claude Sonnet 5 <[email protected]>
2026-08-26 09:09:20 -05:00
ced4568andClaude Sonnet 5 e0f954e714 feat(instructor): expand curriculum teaching visibility
CurriculumView.jsx's per-module activity table gains a Required column
(required/optional) so an instructor can see at a glance which of
Phase 6B's new CORE vs. GUIDED/INDEPENDENT/ADVANCED activities a
student needs to complete a module. Reuses the existing Classroom/
Prepare Labs tooling unchanged — no second classroom system.

Co-Authored-By: Claude Sonnet 5 <[email protected]>
2026-08-26 09:08:54 -05:00
ced4568andClaude Sonnet 5 54b35e8ad7 feat(student): polish structured ROOT learning flow
CourseView.jsx now shows an '(optional)' label on any activity marked
is_required=false, both in the module activity list and the activity
detail header — the only genuine UX need Phase 6B's new optional/
advanced practice content exposed. No other changes to the existing
Course/Module/Activity navigation, Launch Lab flow, or Practice tab.

Co-Authored-By: Claude Sonnet 5 <[email protected]>
2026-08-26 09:08:28 -05:00
ced4568andClaude Sonnet 5 de6c5b3286 feat(root): build Real Ops and capstone readiness content
root-12-real-ops gains a Detect -> Triage -> Diagnose -> Mitigate ->
Recover -> Verify -> Learn incident-response framing lesson at the
front of the existing 4-incident module, and a post-incident reflection
at the end — the incidents themselves are unchanged, still deliberately
un-guided ('you are responsible for this environment,' not 'complete
this exercise'). No fixes revealed; instructor notes carry the deeper
solution guidance the student-facing lesson intentionally withholds.

root-capstone-m02-capstone-readiness — a new READY orientation module:
what the Capstone measures, how the timed/randomized draw works, time
management and troubleshooting strategy under a clock, and a genuine
self-assessment checklist. Never publishes the current draw or answers.
See docs/ROOT_CAPSTONE_READINESS.md for why this module's completion is
deliberately independent of the real capstone's server-side unlock gate.

Co-Authored-By: Claude Sonnet 5 <[email protected]>
2026-08-26 09:08:01 -05:00
ced4568andClaude Sonnet 5 831486d664 feat(root): expand troubleshooting and observability curriculum
The Phase 6A gold-standard Health Probes module is preserved byte-for-
byte unchanged — it's the template, not a page to rewrite for
consistency.

root-10-m03-troubleshooting-framework — a new PARTIAL module
introducing a repeatable Observe -> Gather Evidence -> Form Hypothesis
-> Test -> Repair -> Validate -> Prevent Recurrence framework, applied
to a CrashLoopBackOff and a broken Service selector. Lesson,
demonstration (the full framework walked through a real
CrashLoopBackOff, command by command), knowledge check, and real Labs
(crashloop-fix, endpoint-fix-task). Sequenced between the gold module
and the existing bare-lab bank, which now sits behind it.

Co-Authored-By: Claude Sonnet 5 <[email protected]>
2026-08-26 09:07:34 -05:00
ced4568andClaude Sonnet 5 960a638ec9 feat(root): add Kubernetes security curriculum
Four new modules, moving ROOT 09 off PLANNED and building the
22-scenario CKS-style bank into a coherent course instead of
disconnected exam tasks — see docs/ROOT_CURRICULUM_COVERAGE_MATRIX.md
for the CORE/GUIDED/INDEPENDENT/ADVANCED/ASSESSMENT-BANK classification
behind every placement.

root-09-m01-security-model-and-securitycontext — READY, full
gold-standard pattern: defense in depth, least privilege, hardening a
Pod with SecurityContext. Lesson, demonstration (a Pod before/after
hardening), knowledge check, guided exercise (a hardening checklist),
real Labs (CORE: non-root/drop-capabilities/read-only-fs/
pod-security-context; GUIDED: seccomp; ADVANCED: AppArmor; INDEPENDENT:
the generic pod-security-context duplicate), and a reflection.

root-09-m02-serviceaccounts-and-rbac — PARTIAL: workload identity and
least-privilege permissions. Lesson + knowledge check + real Labs.

root-09-m03-network-and-supplychain-security — PARTIAL: NetworkPolicy
as a security control (default-deny), image/registry trust, TLS
ingress. Lesson + knowledge check + real Labs.

root-09-m04-cluster-hardening-and-runtime — PARTIAL, deliberately
survey-depth: Pod Security Admission and a lighter treatment of
audit-policy/runtime-sandboxing topics that don't belong in the core
daily-driver path.

Co-Authored-By: Claude Sonnet 5 <[email protected]>
2026-08-26 09:07:07 -05:00
ced4568andClaude Sonnet 5 73cea1ba1d feat(root): add storage and scheduling curriculum
Two new PARTIAL modules, moving ROOT 08 off PLANNED for the first time:

root-08-m01-storage-fundamentals — ephemeral vs. persistent storage,
PV/PVC/StorageClass. Lesson + knowledge check + real Labs (emptydir-pod,
pv-pvc-mount, pvc-dynamic-task, storageclass-mcq).

root-08-m02-scheduling-resource-governance — how the scheduler places
Pods and how quotas/limits/priority/disruption budgets shape that
placement. Lesson + knowledge check + real Labs (node-label-selector,
node-taint-toleration, pod-affinity-mcq, priority-class-task,
pod-disruption-budget-task, resource-quota-ns, limitrange-task).

cluster-upgrade-mcq and etcd-backup-mcq deliberately left unwired —
ROOT 11/DevOps territory, out of this phase's scope, not overlooked.

Co-Authored-By: Claude Sonnet 5 <[email protected]>
2026-08-26 09:06:43 -05:00
ced4568andClaude Sonnet 5 dbcc210889 feat(root): author networking and configuration curriculum
root-07-m03-services-and-service-discovery — a new, full gold-standard-
pattern module: the Service/Endpoints/DNS request path, choosing the
right Service type. Lesson, demonstration (a Service with zero
Endpoints — the single fastest diagnostic check for this failure
class), knowledge check, guided exercise (ClusterIP vs. NodePort vs.
LoadBalancer for three real components), a real Lab
(expose-service-basics), and a reflection.

root-07-m04-ingress-networkpolicy-foundations — a new PARTIAL module:
Ingress and NetworkPolicy at the architectural level (the security-
control framing of NetworkPolicy is deliberately deferred to ROOT 09).
Lesson + knowledge check + real Labs (ingress-task, network-policy).

Co-Authored-By: Claude Sonnet 5 <[email protected]>
2026-08-26 09:06:19 -05:00
ced4568andClaude Sonnet 5 86ea035e9b feat(root): author workloads curriculum
root-06-m02-deployments-scaling-updates — a new, full gold-standard-
pattern module: why Deployments/ReplicaSets exist, how a rolling update
actually progresses, and what rollback restores. Lesson, demonstration
(a healthy rollout vs. one stalled on ImagePullBackOff), knowledge
check, guided exercise (planning a safe rollout strategy), real Labs
(rolling-update-task, deployment-rollback), and a reflection.

root-06-m03-jobs-cronjobs-daemonsets — a new PARTIAL module: Jobs,
CronJobs, and DaemonSets as distinct workload shapes from a
Deployment's always-on model. Lesson + knowledge check + real Labs
(job-task, cronjob-task).

Co-Authored-By: Claude Sonnet 5 <[email protected]>
2026-08-26 09:06:00 -05:00
ced4568andClaude Sonnet 5 25409d3bd7 feat(root): author Kubernetes foundations curriculum
root-05-m00-kubernetes-mental-model — a new, full gold-standard-pattern
front-door module for ROOT 05: what Kubernetes solves, the desired-state
model, the control-plane/worker split, and Pods/Namespaces/labels
through kubectl. Lesson, demonstration (watching a Pod get replaced
after manual deletion), knowledge check, guided exercise (planning a
Namespace layout), a real Lab (namespaces-basics), and a reflection —
sequenced ahead of the existing bare kubectl-fluency lab bank.

Co-Authored-By: Claude Sonnet 5 <[email protected]>
2026-08-26 09:05:40 -05:00
ced4568andClaude Sonnet 5 046a0fba18 fix(capstone): enforce unlock rule server-side
POST /api/assessments/:definitionId/start only ever checked that the
definition existed and was active — it never checked unlock_rule. GET
/api/capstone correctly computed and displayed lock state, and the
student UI never exposed a start action while locked, but a direct POST
to this route bypassed the check entirely (documented as a known gap in
docs/PHASE6A_ROOT_COURSE_FOUNDATION.md §10). Student UI state is not the
enforcement boundary.

Fixed by binding to the exact same computeCurriculumState() gate
/api/capstone already relies on, rather than re-parsing
definition.unlock_rule independently — one computation of 'is this
unlocked,' not two that could drift. Only a definition the curriculum
path actually names as ITS capstone is gated this way; an ordinary exam
is completely unaffected. Returns a clean 403 { error: 'locked',
blocking_stage_ids } — the same shape /api/capstone already exposes.

Found while fixing this: e2e-phase5b.js's own capstone-completion test
had been passing only because of this exact gap — it never included the
real-ops stage in its completion loop before attempting to start the
capstone, and the missing unlock check let it succeed anyway. Fixed
alongside the platform code (REAL_OPS added to ALL_NON_CAPSTONE), not
routed around.

Co-Authored-By: Claude Sonnet 5 <[email protected]>
2026-08-26 09:05:18 -05:00
ced4568andClaude Sonnet 5 bee57d89fd feat(root): wire ROOT 05-10/12/Capstone curriculum expansion
023_phase6b_curriculum.sql — additive on top of 022_course_content.sql:
13 new teaching modules (ROOT 08/09 move from PLANNED to PARTIAL; ROOT
05-07/10 gain a new front-door module sequenced ahead of the existing
bare-lab bank; ROOT 12 gains an incident-response framing lesson +
reflection; Capstone gains a readiness module). No existing row is
deleted; a small number of existing rows have their sequence/
prerequisites updated so a new teaching module supersedes the bare-lab
bank as the front door — never their scenario_id/activity_type/
completion_behavior, so no student's derived completion changes meaning.

is_required (new module_activities column, defaults true — every Phase
6A activity unaffected) lets a module distinguish CORE teaching from
GUIDED/INDEPENDENT-practice duplicates and ADVANCED/optional extras.
course-progress.js's totals() now considers a module complete once
every REQUIRED activity is done, not literally every activity — an
incomplete optional one no longer blocks completion, though it still
counts toward the displayed percentage.

Co-Authored-By: Claude Sonnet 5 <[email protected]>
2026-08-26 09:04:55 -05:00
ced4568andClaude Sonnet 5 82f17a05e8 docs(curriculum): map Phase 6B ROOT coverage
Course -> module -> objective -> lesson/demo/knowledge-check/guided-
exercise -> scenario(s) -> Real Ops connection -> status, for ROOT 05-10,
12, and Capstone, grounded in the Phase 6A inventory. Every scenario
placement has an intentional reason, not a coverage-percentage target —
includes an explicit 'duplicate concepts identified' section for the
near-duplicate scenario pairs (pod-security-context vs.
cks-pod-security-context, rbac-clusterrole vs. cks-rbac-clusterrole,
network-policy's architectural vs. security-control framing) and which
scenarios are deliberately left out of structured curriculum entirely.

Co-Authored-By: Claude Sonnet 5 <[email protected]>
2026-08-26 09:04:30 -05:00
65 changed files with 4265 additions and 25 deletions
@@ -0,0 +1,108 @@
# What Kubernetes Solves & the Desired-State Model
## Before Kubernetes: the problem
Imagine you're running a web application on three servers by hand. One server crashes at 2am —
someone has to notice, log in, and restart the application. Traffic grows, so you need a fourth
server — someone has to provision it, install dependencies, and configure it to match the other
three. You ship a new version — someone has to update all four servers, one at a time, without
taking the whole application down.
None of this is hard in isolation. It becomes unmanageable at scale, and it depends entirely on
a human noticing and reacting fast enough. Kubernetes exists to make a computer do that
noticing and reacting instead — continuously, automatically, and the same way every time.
## The core idea: desired state
You don't tell Kubernetes *how* to run your application step by step. You tell it *what you
want to be true* — "3 replicas of this container should be running" — and Kubernetes
continuously works to make that true, correcting drift whenever reality doesn't match.
This is the single most important mental shift for someone new to Kubernetes: you're not
writing a script that runs once. You're declaring a **desired state**, and a background process
never stops comparing the real world against it.
```yaml
apiVersion: apps/v1
kind: Deployment
metadata:
name: web
spec:
replicas: 3 # <- the desired state: "3 of these, always"
...
```
If a Pod crashes, Kubernetes doesn't "restart the crashed one" as a special case — it just
notices reality (2 running) no longer matches desired state (3 wanted) and creates a
replacement. Same mechanism, no special-casing.
## The cluster mental model
A Kubernetes cluster has two conceptually different kinds of machines:
- **The control plane** — the "brain." It stores the desired state (in `etcd`), watches actual
state, and makes decisions (the API server, scheduler, and controllers all live here). You
talk to the control plane through `kubectl`; you never SSH into it to manage workloads.
- **Worker nodes** — where your containers actually run. Each node runs a `kubelet` (an agent
that starts/stops containers as the control plane instructs) and a container runtime.
You describe desired state to the control plane. The control plane decides which nodes should
run what. The nodes' kubelets make it actually happen. You never manually place a Pod on a
specific node in normal operation — that placement decision belongs to the scheduler.
## Declarative, not imperative
"Imperative" means giving step-by-step instructions ("start a container, then another, then
configure networking between them"). "Declarative" means describing an end state and letting
the system figure out the steps. Kubernetes' API objects (Pods, Deployments, Services, and
everything else you'll learn in ROOT_) are declarative — you write YAML describing what should
exist, `kubectl apply` submits it, and the control plane does the rest.
This is also why Kubernetes YAML looks the way it does: it's not a script, it's a specification.
## Pods, Namespaces, and labels — the vocabulary you need first
- **Pod** — the smallest deployable unit. Usually one container, sometimes a small group of
tightly-coupled containers that must run together on the same node and share networking.
You'll rarely create bare Pods directly in real use (a Deployment manages them for you, see
ROOT 06) but understanding the Pod itself is foundational to everything built on top of it.
- **Namespace** — a way to partition one cluster into logically separate areas (e.g. `dev`,
`staging`, teams, or projects), so names don't collide and access/quotas can be scoped.
- **Labels** — arbitrary key/value tags attached to objects (`app: web`, `env: prod`). Labels
are how almost everything in Kubernetes finds related objects — a Deployment finds "its" Pods
by label selector, not by name pattern matching.
## kubectl: your one tool for all of this
`kubectl` is the command-line client that talks to the control plane's API server. Nearly
everything you'll do in ROOT_ Labs goes through it: `kubectl get` (list/inspect),
`kubectl describe` (detailed status + recent events — your primary troubleshooting tool),
`kubectl apply -f` (submit a desired-state YAML file), `kubectl logs` (see what a container
printed). You'll build real fluency with these across this module and the ones that follow.
## Instructor Notes
**Approximate timing:** 15 minutes read, 10-12 minutes for a live walkthrough with discussion.
**Demo plan:** Before the demonstration activity, it's worth drawing the control-plane/worker
split on a whiteboard (or sharing a simple diagram) and tracing one request: `kubectl apply` ->
API server -> etcd -> scheduler -> kubelet -> container runtime. Students retain the mental
model much better when they've seen the path, not just read about it.
**Likely misconceptions to watch for:**
- Students often assume `kubectl` talks directly to nodes/containers. It doesn't — it only ever
talks to the API server. Worth stating explicitly.
- "Declarative" is sometimes read as "automatic" in a vague sense. Be concrete: it means "you
describe the end state; a controller loop makes it true," not "Kubernetes guesses what you
want."
**Discussion question:** "If desired state says 3 replicas and you manually run `kubectl delete
pod` on one of them, what happens next, and why?" (Answer: a new one is created almost
immediately — deleting a Pod doesn't change the Deployment's desired replica count, so the
control loop restores it.)
**Optional extension:** Ask students to predict what would happen if they edited a running Pod's
container image directly with `kubectl edit pod` instead of updating the Deployment that manages
it (answer: it works until that specific Pod is replaced for any reason, at which point the new
Pod reverts to whatever the Deployment's template says — a good early illustration of "the
Deployment is the source of truth, not the running Pod").
@@ -0,0 +1,76 @@
# Demonstration: Desired State Reconciliation
Watch what actually happens when reality drifts from desired state — this is the mechanism the
whole lesson describes, made concrete.
## Setup
A Namespace called `demo` exists with a Deployment `web` declaring `replicas: 2`. Right now,
reality matches desired state:
```
$ kubectl get pods -n demo
NAME READY STATUS RESTARTS AGE
web-7d8f9c6b5d-abcde 1/1 Running 0 3m
web-7d8f9c6b5d-fghij 1/1 Running 0 3m
```
## Someone (or something) deletes one Pod
```
$ kubectl delete pod web-7d8f9c6b5d-abcde -n demo
pod "web-7d8f9c6b5d-abcde" deleted
```
## What happens in the next second or two, without anyone doing anything else
```
$ kubectl get pods -n demo
NAME READY STATUS RESTARTS AGE
web-7d8f9c6b5d-fghij 1/1 Running 0 3m
web-7d8f9c6b5d-klmno 0/1 ContainerCreating 0 1s
```
A brand new Pod (`...-klmno`, a new random suffix — this is NOT the deleted Pod coming back)
appeared on its own. Nobody ran `kubectl create` again. The Deployment's controller noticed
actual state (1 running Pod matching its label selector) no longer matched desired state
(`replicas: 2`), and created exactly one replacement to close the gap — not two, not zero.
A few seconds later:
```
$ kubectl get pods -n demo
NAME READY STATUS RESTARTS AGE
web-7d8f9c6b5d-fghij 1/1 Running 0 3m
web-7d8f9c6b5d-klmno 1/1 Running 0 8s
```
Back to 2/2 — desired state restored, entirely without human intervention.
## Why this matters beyond the demo
This exact mechanism is what makes a node crash, a Pod eviction, or a container being
OOM-killed something Kubernetes recovers from automatically instead of something that pages a
human at 2am. The controller loop doesn't know or care WHY a Pod disappeared — crash, manual
delete, node failure — it only ever asks "does reality match desired state right now?" and acts
if not. Understanding this one loop explains a huge amount of Kubernetes' behavior that would
otherwise look like unrelated special cases.
## Instructor Notes
**Demo script:** Run this live rather than only showing the captured output above — have
students watch `kubectl get pods -n demo --watch` in one terminal while you delete a Pod from
another. Watching the new Pod name/age appear in real time lands the "this is a NEW Pod, not a
restart" point far better than static text.
**Approximate timing:** 8-10 minutes live; 5 minutes as a self-paced read.
**Common misconception to correct:** students frequently describe this as "Kubernetes restarted
the Pod." Correct this explicitly — a deleted Pod is gone permanently; a *new* Pod object was
created to satisfy the replica count. This distinction matters later when debugging (the new
Pod has zero history from the old one — no old logs, no old restart count).
**Optional extension:** ask what would happen if you deleted the Deployment itself instead of
one Pod (answer: all of its Pods are deleted and NOT replaced, because the thing declaring
desired state is now gone — a good way to reinforce that the Deployment, not any individual
Pod, is the actual source of truth).
@@ -0,0 +1,48 @@
# Knowledge Check: The Kubernetes Mental Model
Answer each question yourself before reading the answer that follows it.
---
**1. You run `kubectl delete pod` on one Pod belonging to a Deployment with `replicas: 3`. A
few seconds later, `kubectl get pods` shows 3 Pods again, but one has a different name than any
of the original three. What actually happened?**
*Answer:* The deleted Pod is gone permanently. The Deployment's controller noticed actual state
(2 Pods) no longer matched desired state (3 Pods) and created ONE new Pod to close the gap. It
is not the old Pod restarting — it's a brand new object.
---
**2. A Deployment has `replicas: 3`, and there are 5 nodes in the cluster. Which of these
decides WHICH node each of the 3 Pods actually lands on?**
*Answer:* The scheduler (part of the control plane), not the person who wrote the Deployment
YAML and not the nodes themselves. You declare desired state; the scheduler makes the placement
decision based on available resources and any placement rules configured.
---
**3. True or false: `kubectl` communicates directly with the kubelet on whichever node your
Pod happens to be running on.**
*Answer:* False. `kubectl` only ever talks to the API server (part of the control plane). The
API server is the single entry point for every read and write — it never bypasses the control
plane to reach a node directly for a normal `get`/`apply`/`describe` call.
---
**4. Why is Kubernetes YAML described as "declarative" rather than a script?**
*Answer:* A script describes a sequence of steps to execute once. Kubernetes YAML describes an
END STATE you want to exist ("3 replicas of this container should be running") — a controller
loop then continuously works to keep reality matching that description, correcting drift
whenever it appears, indefinitely, not just once at apply time.
## Instructor Notes
**Facilitation:** Ask these aloud in a live classroom before revealing answers — question 1 in
particular tends to surface the "it restarted" misconception the demonstration activity should
have already addressed; if it hasn't landed, this is the moment to circle back.
**Approximate timing:** 5 minutes.
@@ -0,0 +1,57 @@
# Guided Exercise: Planning a Namespace Layout
This is a paper-and-thinking exercise — work through it before the Lab, not during it.
## The scenario
You're setting up a small Kubernetes cluster for a class project with three teams (`frontend`,
`backend`, `data`), each running their own set of Pods, and you also need a shared area for
tools everyone uses (a shared logging dashboard, for example).
## Your task
Sketch out, on paper or in a scratch file:
1. What Namespaces would you create, and why? (Hint: think about who needs to see what, and
whether any team's mistake — e.g. deleting the wrong Pod by accident — should be able to
affect another team.)
2. If `frontend` team members should be able to manage their own Pods but NOT touch `backend`'s
or `data`'s, what does that suggest about how Namespaces relate to access control? (You'll
learn the actual mechanism, RBAC, in ROOT 09 — for now just reason about why Namespace
boundaries make that kind of restriction possible at all.)
3. Would you put the shared logging dashboard in one of the three team Namespaces, or somewhere
else? Justify your answer.
4. If two teams both need to run something they each call `web`, what would happen if they were
in the SAME Namespace? What changes if they're in separate Namespaces?
## A reasonable answer to check yourself against
1. Three Namespaces (`frontend`, `backend`, `data`) — one per team, so each team's objects are
isolated from the others and a mistake in one Namespace (deleting the wrong Pod, applying a
bad manifest) can't accidentally affect a different team's workloads.
2. Namespace boundaries are what RBAC rules can be scoped TO — "this person can manage Pods in
the `frontend` Namespace" is a real, common permission model. Without separate Namespaces,
you'd have to distinguish access by resource name pattern instead of by boundary, which is
far more error-prone.
3. A separate Namespace (e.g. `shared-tools` or `platform`) — it isn't owned by any one team,
and mixing it into a team's Namespace would make it unclear who's responsible for it or
accidentally couple its lifecycle to that team's.
4. In the SAME Namespace, object names must be unique — a second `web` Deployment would either
fail to create or overwrite the first, depending on how it's applied. In SEPARATE
Namespaces, both `frontend/web` and `backend/web` can coexist without conflict — the
Namespace is part of what makes a name unique, not just the name itself.
If your answer differed meaningfully from this, re-read the lesson's Namespace section before
continuing to the Lab.
## Instructor Notes
**Facilitation:** Good as a 2-3 person small-group discussion in a live classroom before
revealing the reasonable answer — question 4 in particular often produces a genuine "oh" moment
once students realize name uniqueness is Namespace-scoped, not cluster-wide.
**Approximate timing:** 10 minutes live with discussion; 10 minutes self-paced.
**Optional extension:** ask what would need to be true for the `data` team to be ALLOWED to read
(but not modify) something in `shared-tools` — a good bridge to RBAC's read vs. write verbs,
covered properly in ROOT 09.
@@ -0,0 +1,44 @@
# Launch Lab: Working with Namespaces
Time to apply the mental model for real — you'll create an actual isolated Namespace and deploy
into it, in your own disposable Lab environment.
## What you're doing
You'll create a Namespace (`team-alpha`) and deploy an application into it with a specific
replica count — directly applying the "isolated area within one cluster" idea from the guided
exercise, and the desired-state model from the lesson (once you declare `replicas: 2`, that
becomes the standing desired state for that Deployment, enforced continuously).
## Before you start
Think back to the demonstration: once your Deployment exists with its desired replica count,
Kubernetes will keep it there on its own. You don't need to "check back" and manually fix
anything — if you want to prove this to yourself, try deleting one of your Pods after you've
finished the task and watch what happens.
## Your task in this Lab
Create the Namespace, then deploy the application inside it with the exact replica count
specified. Use `kubectl get namespace` and `kubectl get deployment -n <namespace>` to confirm
your work — the same verification pattern you'll use constantly throughout ROOT_.
This Lab has its own in-context hints if you get stuck. Try working from the lesson and guided
exercise first — the commands you need are exactly the ones described there.
When you're done, return to this module to close out with a reflection on why this isolation
matters beyond just "keeping things organized."
## Instructor Notes
**Classroom flow:** This is most students' first real `kubectl apply`/`create` in ROOT_ beyond
whatever pilot exposure they've had — a good moment to circulate and check that basic
`kubectl` command syntax isn't the blocker (as opposed to the Namespace concept itself, which
the guided exercise should have already addressed).
**Approximate timing:** 10-15 minutes.
**Common mistake to watch for:** creating the Deployment in the DEFAULT namespace instead of
`team-alpha` (forgetting `-n team-alpha` or the namespace field in the manifest) — this is a
very common first mistake and a good real-world illustration of why Namespace isolation only
works if you're actually specifying it every time.
@@ -0,0 +1,44 @@
# Reflection: Why Desired State Matters in Production
You just created an isolated Namespace and a Deployment with a declared replica count. Take a
few minutes to connect this to why it matters beyond passing this Lab's validation.
## Reflection questions
1. If your `team-alpha` Namespace were a real team's production environment, what's one mistake
in a DIFFERENT namespace that Namespace isolation would have protected you from?
2. You declared `replicas: 2` rather than manually creating two Pods. What would you have had
to do manually, over and over, if Kubernetes only supported creating individual Pods with no
concept of desired state?
3. Think of one non-Kubernetes system you've used (a thermostat, a spell-checker, an
auto-save feature) that also works by continuously comparing "what is" to "what should be."
What made you think of it?
## Real Ops takeaway
**Namespaces are your first real production safety boundary, and they're free.** A
misconfigured `kubectl delete` scoped to the wrong Namespace is a common, entirely preventable
class of incident — teams that consistently namespace their environments (dev/staging/prod, or
per-team) limit the blast radius of almost any operator mistake to just that Namespace. This
costs nothing to set up and prevents a real, common category of outage.
**Desired state is what makes self-healing possible at all.** Every "the platform recovered on
its own" story you'll hear about Kubernetes in production traces back to exactly the mechanism
you just watched in the demonstration: a controller comparing actual state to desired state and
correcting the gap. Understanding this loop is what lets you predict Kubernetes' behavior
instead of being surprised by it.
This module is complete. Continue to the next module.
## Instructor Notes
**Discussion questions for a live classroom:** use all three reflection questions as discussion
prompts. Question 3 in particular tends to produce good analogies that make the abstract
"controller loop" concept concrete and memorable.
**Approximate timing:** 8-10 minutes live discussion; 5 minutes self-paced writing.
**Optional extension:** ask students to name one place in their own life (not computing) where
"declare the goal and let a system enforce it" would work better than "manually do the thing
every time" — a genuinely reflective prompt that reinforces the mental model beyond Kubernetes
specifically.
@@ -0,0 +1,81 @@
# Why Deployments Exist & How a Rolling Update Progresses
## The problem a bare Pod doesn't solve
A Pod, on its own, has no self-healing and no concept of "there should be more than one of
these." If a Pod crashes, nothing recreates it. If you need 3 copies for capacity, you'd have to
create 3 separately-named Pods by hand and keep track of all of them yourself. If you need to
update the container image, you'd have to delete and recreate every one of them manually,
almost certainly causing a visible outage while you do it.
**A Deployment solves all three problems at once**: it declares how many replicas of a Pod
template should exist, keeps that count true continuously (the exact desired-state mechanism
from ROOT 05), and knows how to change the Pod template over time — a version upgrade — without
just deleting everything and starting over.
## ReplicaSets: the layer underneath, briefly
You'll rarely touch a ReplicaSet directly, but understanding it clarifies what a Deployment
actually does. A Deployment doesn't manage Pods directly — it manages a ReplicaSet, which is
what actually keeps N Pods matching a label selector running. When you update a Deployment's
Pod template (like changing the image), the Deployment creates a NEW ReplicaSet with the new
template and gradually shifts replicas from the old ReplicaSet to the new one. The old
ReplicaSet isn't deleted — it's scaled to zero and kept around, which is exactly what makes
rollback possible (more on that below).
## How a rolling update actually progresses
By default, a Deployment updates using the `RollingUpdate` strategy: it doesn't take all old
Pods down and bring all new ones up at once (that would cause an outage). Instead, it
incrementally creates new-version Pods and removes old-version ones, always keeping enough
capacity available:
```
Before: [v1] [v1] [v1]
Step 1: [v1] [v1] [v1] [v2] <- one new Pod created
Step 2: [v1] [v1] [v2] <- one old Pod removed once new one is Ready
Step 3: [v1] [v1] [v2] [v2]
Step 4: [v1] [v2] [v2]
...
After: [v2] [v2] [v2]
```
Crucially, a new Pod only counts as "up" for the purposes of proceeding once it passes its
readiness probe (see ROOT 10's gold-standard module) — this is exactly why a misconfigured
readiness probe can make a rollout hang indefinitely instead of failing fast: Kubernetes is
correctly waiting for a "ready" signal that will never come.
## Rollback: what it actually restores
`kubectl rollout undo` doesn't magically know how to "undo" arbitrary changes — it works because
of the old ReplicaSet still sitting around at zero replicas, from the mechanism described above.
Rolling back means: scale the OLD ReplicaSet back up and the current (broken) one back down,
using the exact same rolling mechanism as a forward update. This is why rollback is fast and
safe — it's not a special operation, it's the same well-tested rolling-update machinery running
in reverse, against a Pod template that's already known to have worked before.
## Instructor Notes
**Approximate timing:** 15 minutes read, 10-12 minutes live with the ReplicaSet diagram.
**Demo plan:** Draw (or show) the ReplicaSet-swap diagram above on a whiteboard before the
demonstration activity — students who see the "old ReplicaSet scaled to zero, not deleted"
detail up front connect rollback to rollout much faster.
**Likely misconceptions to watch for:**
- Students often think rollback "restores a backup" or reverts a Git-style diff. Correct this:
it's scaling an existing (still-present) ReplicaSet back up, nothing is being restored from
storage.
- "Rolling update" is sometimes assumed to mean "one Pod at a time, always." The actual pace is
controlled by `maxSurge`/`maxUnavailable` (not covered in depth here, but worth naming so
students don't over-generalize from the simplified diagram).
**Discussion question:** "Why does a rolling update need readiness probes to work correctly,
specifically?" (Answer: without a readiness signal, Kubernetes has no way to know when a new
Pod is actually safe to receive traffic before removing an old one — it would either guess via a
fixed delay, unreliable, or not wait at all, unsafe.)
**Optional extension:** ask what would happen to an in-progress rollout if the new image simply
doesn't exist (a typo in the tag) — a good bridge to real troubleshooting: the rollout stalls
indefinitely with `ImagePullBackOff` on the new Pods, never completing and never rolling back on
its own.
@@ -0,0 +1,77 @@
# Demonstration: Watching a Rollout, Good and Bad
## A healthy rollout
A Deployment `app-v1` running `nginx:1.24` at 3 replicas gets updated to `nginx:1.25`:
```
$ kubectl set image deployment/app-v1 nginx=nginx:1.25
deployment.apps/app-v1 image updated
$ kubectl rollout status deployment/app-v1
Waiting for deployment "app-v1" rollout to finish: 1 out of 3 new replicas have been updated...
Waiting for deployment "app-v1" rollout to finish: 2 out of 3 new replicas have been updated...
Waiting for deployment "app-v1" rollout to finish: 1 old replicas are pending termination...
deployment "app-v1" successfully rolled out
```
`kubectl rollout status` blocks and reports exactly the incremental progress described in the
lesson — this is your primary tool for watching (or scripting a wait on) a rollout, rather than
repeatedly polling `kubectl get pods` yourself.
## Checking revision history
```
$ kubectl rollout history deployment/app-v1
REVISION CHANGE-CAUSE
1 <none>
2 <none>
```
Revision 1 is the original ReplicaSet (now scaled to zero, still present); revision 2 is the
current one. This history is exactly what `kubectl rollout undo` uses.
## A stalled rollout
Now imagine the same update, but to a typo'd tag, `nginx:1.25-typo`, which doesn't exist:
```
$ kubectl rollout status deployment/app-v1
Waiting for deployment "app-v1" rollout to finish: 1 out of 3 new replicas have been updated...
```
...and it just sits there. `kubectl get pods` shows why:
```
$ kubectl get pods
NAME READY STATUS RESTARTS AGE
app-v1-7d8f9c6b5d-abcde 1/1 Running 0 5m
app-v1-7d8f9c6b5d-fghij 1/1 Running 0 5m
app-v1-9c5b7d8f6b-klmno 0/1 ImagePullBackOff 0 30s
```
The new Pod can never become Ready because its image can't even be pulled — so the rollout
correctly refuses to proceed further (removing more old Pods would reduce capacity for no
benefit, since the replacement will never come up). Nothing is "broken" in the platform; the
platform is behaving exactly correctly given bad input.
**The fix here is `kubectl rollout undo`, not waiting longer** — this exact scenario is what
`deployment-rollback`'s Lab, later in ROOT_, gives you real hands-on practice with.
## Instructor Notes
**Demo script:** If time allows, run the healthy rollout live against a throwaway Deployment,
then intentionally break the second one with a bad tag so students see `ImagePullBackOff` occur
in real time rather than only in static text.
**Approximate timing:** 8-10 minutes live; 5-7 minutes self-paced.
**Common misconception to preempt:** students sometimes assume a stalled rollout will
eventually time out and auto-rollback on its own. By default it will not — a Deployment has no
automatic rollback trigger; a human (or automation) has to run `kubectl rollout undo` (or fix
the underlying issue) explicitly. This is worth stating directly since it's a genuine and
consequential production gotcha.
**Optional extension:** ask what `kubectl rollout status --timeout=2m` would change about this
scenario (answer: the command itself would exit with an error after 2 minutes instead of
blocking forever — useful in CI/CD pipelines that need to fail a deploy step rather than hang).
@@ -0,0 +1,48 @@
# Knowledge Check: Deployments & Rollouts
---
**1. A rolling update to a new image version has been "in progress" for 20 minutes with no
error message, and `kubectl rollout status` never returns. What's the first thing you should
check, and why?**
*Answer:* `kubectl get pods` to see the new Pod's status, then `kubectl describe pod` on it if
it isn't `Running`. A stalled rollout with no explicit error almost always means a new Pod can't
become Ready — commonly `ImagePullBackOff` (bad image/tag) or a failing readiness probe. The
rollout isn't broken; it's correctly refusing to proceed until the new Pod proves healthy.
---
**2. True or false: `kubectl rollout undo` restores your application from a backup of its
previous state.**
*Answer:* False. It scales the previous (still-present, just scaled-to-zero) ReplicaSet back up
and the current one back down — the same rolling mechanism as a forward update, just pointed at
an older, already-proven-working Pod template. Nothing is being restored from storage.
---
**3. A Deployment has `replicas: 3`. You need it to handle more traffic. Which is the correct
action: edit the Pod template's resource limits, or change the replica count? Justify your
answer for a stateless web application.**
*Answer:* Change the replica count (scale out) for a stateless application handling more
concurrent traffic — more identical copies sharing the load. Changing resource limits affects
how much each individual Pod can use, not how many Pods exist; it doesn't add capacity for more
concurrent requests the way scaling does.
---
**4. Why does a Deployment keep an old, scaled-to-zero ReplicaSet around instead of deleting it
immediately after a successful rollout?**
*Answer:* That scaled-down ReplicaSet is exactly what makes fast, safe rollback possible later —
deleting it immediately would mean a "rollback" would have to rebuild the old Pod template from
scratch (or fail entirely) instead of simply scaling existing, already-defined Pods back up.
## Instructor Notes
**Facilitation:** Question 1 is the most important one to discuss out loud — it's the exact
diagnostic instinct students will need repeatedly in ROOT 10.
**Approximate timing:** 5 minutes.
@@ -0,0 +1,54 @@
# Guided Exercise: Planning a Safe Rollout Strategy
Paper-and-thinking exercise — work through this before the Lab.
## The scenario
Your team runs `api-server`, a Deployment with 6 replicas serving live traffic. You need to
ship a new image version. The team lead asks: "what could go wrong, and how would we know
before it takes down the whole service?"
## Your task
Work through these questions:
1. If the new image has a bug that crashes the container immediately on startup, at what point
in the rolling update would you expect to notice — after 1 new Pod, after all 6, or somewhere
in between? Why?
2. What's the difference in blast radius between that crash-on-startup bug and a subtler bug
that only fails under load, several minutes after a Pod starts serving traffic?
3. Given your answer to question 2, what's the practical value of watching `kubectl rollout
status` and `kubectl get pods` DURING a rollout, rather than only checking after it reports
"successfully rolled out"?
4. If you noticed a problem partway through, what's the single command that gets you back to
the last known-good state fastest?
## A worked answer to check yourself against
1. After the FIRST new Pod — a crash-on-startup bug means the new Pod never becomes Ready
(`CrashLoopBackOff`), so the rollout stalls immediately, well before more old Pods are
removed. This is actually the SAFEST kind of bug, because the blast radius stays tiny.
2. A crash-on-startup bug is naturally self-limiting (the rollout stalls itself, as above). A
bug that only appears under load is NOT self-limiting the same way — by the time it's
noticeable, several old (working) replicas may already have been replaced, meaning a larger
fraction of real traffic is already hitting the broken version.
3. Watching during the rollout, not just checking the final "successfully rolled out" message,
is what lets you catch the load-dependent case in question 2 early — waiting for the final
status alone would let the rollout complete entirely (100% on the broken version) before you
noticed anything wrong.
4. `kubectl rollout undo deployment/api-server` — assuming the previous ReplicaSet is still
present (the default), this is faster than trying to hand-diagnose and hot-fix the new
version under pressure.
## Instructor Notes
**Facilitation:** Question 2's distinction (self-limiting vs. not) is the core insight worth
making sure lands — it's why "the rollout said success" is necessary but not sufficient
evidence that a deploy actually went well.
**Approximate timing:** 10-15 minutes live with discussion; 10 minutes self-paced.
**Optional extension:** ask what monitoring/observability signal (beyond `kubectl` output) a
real team would want during a rollout to catch the load-dependent case even faster (a good
forward pointer to ROOT 10's observability themes, without needing to build any actual
monitoring infrastructure here).
@@ -0,0 +1,39 @@
# Launch Lab: Perform a Rolling Update
Time to run a real rolling update against a real Deployment in your disposable Lab.
## What you're doing
A Deployment `app-v1` is running an older image version. Your task is to update it to a newer
version and confirm every replica ends up running the new image — exactly the mechanism from
the lesson and demonstration, on a real cluster this time.
## Before you start
Recall the demonstration: `kubectl rollout status` is your tool for watching progress rather
than repeatedly polling `kubectl get pods` yourself, and a stalled rollout with no obvious error
usually means a new Pod can't become Ready. If your update seems to hang, that's exactly the
diagnostic instinct from the knowledge check to apply.
## Your task in this Lab
Update the Deployment's image and verify all replicas are running the new version. Use
`kubectl rollout status` to confirm completion, not just a single `kubectl get pods` snapshot.
This Lab has its own in-context hints if you get stuck.
When you're done, return to this module for a short reflection on what "successfully rolled
out" actually guarantees — and doesn't.
## Instructor Notes
**Classroom flow:** A good moment to have students keep `kubectl get pods --watch` open in a
second terminal (if their Lab environment supports multiple panes) so they see the incremental
old-Pod/new-Pod transition happen live, reinforcing the demonstration.
**Approximate timing:** 10-15 minutes.
**Common mistake to watch for:** running `kubectl edit deployment` and forgetting to save/apply
correctly, or editing the wrong field (e.g. `replicas` instead of the container image) — a good
moment to reinforce reading the task description precisely rather than pattern-matching to a
similar-looking previous Lab.
@@ -0,0 +1,43 @@
# Reflection: Rollback Is a Plan, Not a Panic Button
You just completed a real rolling update. Take a few minutes to connect it to how this plays out
in a real production team.
## Reflection questions
1. "Successfully rolled out" (from `kubectl rollout status`) tells you every replica is Running
and Ready. What does it NOT tell you about whether the new version is actually correct?
2. If you were on-call and a rollout you just ran seemed to be causing problems, would you reach
for `kubectl rollout undo` immediately or try to hot-fix the new version first? What would
change your answer?
3. Think back to the guided exercise's crash-on-startup vs. load-dependent distinction. Which
one would a typical automated health check (like a readiness probe, ROOT 10) catch, and
which one might slip through even with probes configured correctly?
## Real Ops takeaway
**A rollout completing is not the same as a deploy succeeding.** "Every Pod is Running and
Ready" only proves the new code started up and passed whatever checks are configured — it says
nothing about whether the new version is functionally correct under real traffic. Real teams
pair a rollout with actual monitoring (error rates, latency) before calling a deploy genuinely
successful, not just a green `kubectl rollout status`.
**Rollback should be a rehearsed, low-drama action, not a last resort.** Teams that treat
`kubectl rollout undo` as a normal, expected tool — something you reach for calmly the moment
something looks wrong — recover from bad deploys in seconds. Teams that treat rollback as an
admission of failure hesitate, try to hot-fix forward under pressure, and turn a small,
recoverable mistake into a longer outage.
This module is complete. Continue to the next module.
## Instructor Notes
**Discussion questions for a live classroom:** question 2 is worth pushing on — many students'
instinct is to try to fix forward, and it's worth surfacing WHY that instinct is often wrong
under time pressure (unknown time-to-fix vs. known, fast rollback).
**Approximate timing:** 8-10 minutes live discussion; 5 minutes self-paced writing.
**Optional extension:** ask students to write the one-sentence Slack message they'd post to
their team the moment they decide to roll back a bad deploy — reinforces that rollback is a
normal, communicable operational action, not a private failure.
@@ -0,0 +1,85 @@
# Jobs, CronJobs, and DaemonSets: The Other Workload Shapes
Everything in the previous module assumed a long-running application that should always have N
replicas up. Not every workload looks like that. Kubernetes has three other primitives for
genuinely different shapes of work — using a Deployment for any of these would be the wrong
tool, not just a less elegant one.
## Job: run to completion, exactly once (or a fixed number of times)
A Job creates one or more Pods and considers itself done when they exit successfully — it does
NOT restart a Pod that exits with success, and it DOES retry one that fails, up to a configured
limit. This is fundamentally different from a Deployment, which expects its Pods to run forever
and treats any exit as something to replace.
Use a Job for: a database migration, a batch data-processing task, a one-off cleanup script —
anything with a defined "finished" state.
```yaml
apiVersion: batch/v1
kind: Job
metadata:
name: migrate-db
spec:
template:
spec:
containers:
- name: migrate
image: myapp:latest
command: ["./migrate.sh"]
restartPolicy: Never
backoffLimit: 3
```
## CronJob: a Job, on a schedule
A CronJob doesn't run Pods itself — it creates a new Job on a cron schedule (`schedule:
"0 2 * * *"` for "every day at 2am"), and that Job behaves exactly as described above. Use a
CronJob for anything that should run periodically and finish: nightly backups, scheduled
reports, periodic cleanup.
A CronJob that reliably fails to complete (an image that always crashes, for example) will keep
creating new Jobs on schedule, each failing the same way — this is a real, common way to
silently exhaust cluster resources (job/pod history accumulating) if nobody's watching.
## DaemonSet: exactly one Pod per node, automatically
A DaemonSet doesn't declare a replica count at all — it ensures exactly one matching Pod runs
on every node in the cluster (or every node matching a selector), and automatically adds a Pod
when a new node joins. Use a DaemonSet for per-node infrastructure: a log-shipping agent, a
node-level monitoring exporter, a network plugin component — things that fundamentally need to
exist once per machine, not "N copies somewhere."
## The decision in one pass
| You need... | Use |
|---|---|
| Always-on, N identical copies, restarted forever | Deployment |
| Run once (or a few times) until it finishes successfully | Job |
| The above, but on a recurring schedule | CronJob |
| Exactly one copy on every node | DaemonSet |
## Instructor Notes
**Approximate timing:** 15 minutes read; 10 minutes live.
**Demo plan (if extending this PARTIAL module later):** live-create a Job with a command that
deliberately fails once then succeeds (`backoffLimit: 2`), and watch `kubectl get pods` show
the failed attempt alongside the eventual successful one — makes the retry-until-backoffLimit
behavior concrete.
**Likely misconceptions to watch for:**
- Students often assume a Job that finishes successfully gets cleaned up automatically. It
doesn't by default — the completed Pod/Job objects remain until manually deleted or a
`ttlSecondsAfterFinished` is configured (not covered here, worth a one-line mention if asked).
- "DaemonSet" is sometimes confused with "one Pod, cluster-wide" (singular). It's the opposite —
one Pod PER NODE, which can be many Pods total in a multi-node cluster.
**Discussion question:** "Why doesn't a Deployment support 'run once and be done'?" (Answer: a
Deployment's whole contract is maintaining a standing replica count forever — repurposing it for
one-shot work would fight that contract rather than use a primitive designed for it.)
**Optional extension:** ask what would go wrong if a CronJob's schedule ran more often than a
single Job execution takes to complete (answer: overlapping Job runs, unless
`concurrencyPolicy` is set to `Forbid` or `Replace` — a real gotcha worth naming even without
building a full lab around it).
@@ -0,0 +1,45 @@
# Knowledge Check: Choosing the Right Workload Primitive
---
**1. You need to run a database migration script exactly once when a new version deploys. Which
primitive fits, and why not a Deployment?**
*Answer:* A Job. A Deployment expects its Pods to run forever and replaces any that exit; a
migration script is supposed to exit successfully when done, which a Deployment would treat as
a failure to "fix" by restarting it — the wrong behavior for a task that's supposed to finish.
---
**2. A CronJob scheduled for "every 5 minutes" keeps creating Jobs that fail immediately due to
a bad image tag. What actually happens over the next hour if nobody notices?**
*Answer:* A new failing Job (and its Pod) gets created roughly every 5 minutes, accumulating
failed Job/Pod objects and consuming cluster resources — nothing stops this automatically. This
is exactly the kind of slow, easy-to-miss resource exhaustion a real on-call engineer should
watch for.
---
**3. True or false: a DaemonSet's Pod count scales with a `replicas` field, the same as a
Deployment.**
*Answer:* False. A DaemonSet has no `replicas` field — its Pod count is implicitly "one per
matching node," and it grows or shrinks automatically as nodes join or leave the cluster.
---
**4. You need a log-shipping agent that must run on every node, including any new node added
later. Which primitive, and what would go wrong if you used a Deployment with a high replica
count instead?**
*Answer:* A DaemonSet. A Deployment's replicas are placed by the scheduler wherever it decides
is best — nothing guarantees one per node, and a newly-added node wouldn't automatically get a
copy the way a DaemonSet guarantees.
## Instructor Notes
**Facilitation:** Question 2 is worth emphasizing — it's a genuinely realistic "how does a
cluster quietly get into trouble" scenario, not just trivia.
**Approximate timing:** 5 minutes.
@@ -0,0 +1,87 @@
# The Service/Endpoints/DNS Request Path
## The problem: Pod IPs are not stable
Every Pod gets its own IP address, but that IP is NOT durable — when a Pod is replaced (a
rollout, a crash recovery, a reschedule), the new Pod gets a brand new IP. If another part of
your application had that old IP hardcoded, it would silently start talking to nothing. This is
the exact problem in `expose-service-basics`'s scenario: "other pods cannot reliably connect
because pod IPs change when they restart."
## A Service: a stable address in front of a moving set of Pods
A Service is a stable virtual IP and DNS name that automatically routes to whichever Pods
currently match its label selector — regardless of how many there are or how often they change.
You never talk to a Pod's IP directly in normal operation; you talk to the Service, and the
Service's Endpoints (a live, continuously-updated list of the matching Pods' IPs) determines
where traffic actually goes.
```yaml
apiVersion: v1
kind: Service
metadata:
name: redis-svc
spec:
selector:
app: redis # <- matches Pods by label, same mechanism from ROOT 05
ports:
- port: 6379
```
This is the same label-selector mechanism you learned in ROOT 05 — a Service doesn't know or
care about specific Pod names, only which Pods currently carry a matching label.
## The three Service types you'll use most
- **ClusterIP** (the default) — reachable only from inside the cluster. Use this for
internal-only communication, like one microservice talking to another or to a database.
- **NodePort** — additionally exposes the Service on a static port on every node's own IP,
reachable from outside the cluster. Mostly used for development/testing or when there's no
cloud load balancer available.
- **LoadBalancer** — asks the cloud provider to provision a real external load balancer pointed
at the Service. This is the standard way to expose something to the public internet on a
cloud-hosted cluster.
Choosing wrong isn't just a style preference — a ClusterIP Service is architecturally
unreachable from outside the cluster no matter how correctly everything else is configured.
## DNS: how Pods actually find a Service by name
Every Service automatically gets a DNS name inside the cluster
(`<service-name>.<namespace>.svc.cluster.local`, or usually just `<service-name>` from within
the same Namespace) — this is why application code can use a plain hostname like `redis-svc`
instead of an IP address at all. Kubernetes' internal DNS resolves that name to the Service's
stable virtual IP, which then routes to whichever Pods are currently healthy.
## The full request path, end to end
```
Client -> DNS lookup "redis-svc" -> Service's stable virtual IP
-> Service consults its Endpoints (live list of matching, ready Pods)
-> traffic forwarded to one of those Pod IPs
```
Every one of these steps can fail independently, which is exactly why "the app can't reach
redis" requires checking each layer rather than guessing — the next activity shows you what
that looks like when the Endpoints layer is empty.
## Instructor Notes
**Approximate timing:** 15 minutes read, 10-12 minutes live with the request-path diagram.
**Demo plan:** Before the next activity, it's worth live-running `kubectl get endpoints
<service-name>` against a healthy Service so students see a populated Endpoints list before
they see an empty one in the demonstration.
**Likely misconceptions to watch for:**
- Students often think a Service "is" a load balancer process running somewhere. It's closer to
a routing rule maintained by `kube-proxy` on every node — worth clarifying that there's no
single "Service Pod" to go find and debug.
- ClusterIP vs. NodePort vs. LoadBalancer is sometimes memorized without the "why" — the
knowledge check's Service-type question is designed to test the underlying reasoning, not
just recall.
**Discussion question:** "If a Service's selector matches zero Pods, does the Service itself
fail to exist?" (Answer: no — the Service object exists fine; its Endpoints list is just empty,
which looks like connection failure from the client's side without any error at the Service
level itself. This is exactly the next activity's topic.)
@@ -0,0 +1,82 @@
# Demonstration: A Service With Zero Endpoints
This is one of the most common "it just doesn't work" incidents in real Kubernetes operation —
and it produces no error message at all at the Service level.
## The setup
A Service `api-svc` selects Pods labeled `app: api`. A Deployment was recently updated and its
Pods now carry the label `app: api-v2` instead (a rename during a refactor, deliberately or
accidentally).
## What you'd see from the client side
```
$ curl http://api-svc:8080/health
curl: (7) Failed to connect to api-svc port 8080: Connection refused
```
Just a generic connection failure — nothing here says "your Service's selector doesn't match
any Pods."
## What the Service object itself shows
```
$ kubectl get service api-svc
NAME TYPE CLUSTER-IP PORT(S) AGE
api-svc ClusterIP 10.96.34.201 8080/TCP 2h
```
Completely normal-looking. The Service exists, has a stable IP, is not in any kind of "error"
state — because from the Service's own perspective, nothing is wrong. It's doing exactly what
it's configured to do: route to whatever matches its selector, which currently happens to be
nothing.
## Where the real evidence is: Endpoints
```
$ kubectl get endpoints api-svc
NAME ENDPOINTS AGE
api-svc <none> 2h
```
This is the actual signal. `<none>` means the Service's selector currently matches zero Pods —
this is the single fastest check for "is this a Service-to-Pod mismatch" any time something
reachable-in-principle looks like a connection failure.
## Confirming the mismatch
```
$ kubectl get pods --show-labels
NAME READY STATUS LABELS
api-abc123 1/1 Running app=api-v2
```
The Pod is healthy and running — `app=api-v2`, not `app=api`. The Service's selector
(`app: api`) matches nothing, and nothing about the Pod itself is broken.
## The general diagnostic shape
`curl`/application-level connection failure tells you *that* something's wrong, but nothing
about *where*. `kubectl get endpoints <service>` is the fastest way to distinguish "the Service
has no matching Pods" from "the Pods exist and are ready but something else is wrong" —
reach for it early whenever a Service-fronted connection fails for no obvious reason.
## Instructor Notes
**Demo script:** Live-create this exact mismatch (a Service with one selector, a Deployment
with a slightly different label) and walk through `kubectl get service` -> `kubectl get
endpoints` -> `kubectl get pods --show-labels` in front of the class, narrating what each
command is and isn't telling you.
**Approximate timing:** 8-10 minutes live; 5-7 minutes self-paced.
**Common misconception to preempt:** students often check the Service object first and, seeing
nothing obviously wrong, assume the problem must be elsewhere entirely (DNS, firewall, the
application itself) — reinforce that `kubectl get endpoints` is the specific, fast check for
this exact failure mode, before reaching for anything more complex.
**Optional extension:** ask what `kubectl describe service api-svc` would additionally show
compared to `kubectl get service` (answer: the same selector the Service is using, which lets
you directly compare it against `kubectl get pods --show-labels`'s actual Pod labels side by
side, rather than inferring the mismatch).
@@ -0,0 +1,47 @@
# Knowledge Check: Services & Service Discovery
---
**1. A Deployment has three replicas but `kubectl get endpoints` shows `<none>` for its Service.
Which part of the system should you inspect first, and why?**
*Answer:* Compare the Service's selector (`kubectl describe service`) against the actual Pods'
labels (`kubectl get pods --show-labels`) — a Service with a healthy backend Deployment but zero
Endpoints almost always means the selector doesn't match the Pods' current labels, not that the
Pods themselves are unhealthy.
---
**2. You need a microservice reachable ONLY from other services inside the same cluster, never
from the public internet. Which Service type, and why not LoadBalancer?**
*Answer:* ClusterIP — it's reachable only from inside the cluster by design, which is exactly
the requirement. A LoadBalancer would provision a real external endpoint reachable from the
public internet, which is more exposure than the requirement calls for, and depends on cloud
provider support this scenario doesn't need.
---
**3. True or false: application code that connects to `redis-svc` by that plain hostname is
relying on Kubernetes' internal DNS to resolve it.**
*Answer:* True. Every Service automatically gets a DNS name; that's specifically what lets code
use a stable hostname instead of hardcoding a Pod IP that could change at any time.
---
**4. A Service's Endpoints list is non-empty, but the application still can't connect. Does
this rule out a Service-level problem entirely?**
*Answer:* Not entirely — a non-empty Endpoints list means at least one Pod currently matches the
selector, but the connection could still fail for other reasons (wrong port number on the
Service, a NetworkPolicy blocking the traffic, the application inside the Pod not actually
listening). A populated Endpoints list narrows the problem, it doesn't prove the whole path
works.
## Instructor Notes
**Facilitation:** Question 1 is the single most transferable diagnostic habit from this module —
worth explicitly calling out as "the first thing to check" for this entire class of problem.
**Approximate timing:** 5 minutes.
@@ -0,0 +1,49 @@
# Guided Exercise: Choosing the Right Service Type
Paper-and-thinking exercise before the Lab.
## The scenario
You're deploying three components for a class project on a cloud-hosted cluster:
1. A Postgres database that only your own backend application should ever talk to.
2. A backend API that the frontend (also running in the cluster) calls internally.
3. The frontend web application itself, which needs to be reachable by users on the public
internet.
## Your task
For each of the three components, decide: ClusterIP, NodePort, or LoadBalancer — and justify
each choice in one sentence referencing WHO needs to reach it.
## A worked answer to check yourself against
1. **Postgres — ClusterIP.** Only your own backend (running inside the same cluster) needs to
reach it; there is no reason for it to be reachable from outside the cluster at all, and
exposing a database externally is a real, avoidable security risk.
2. **Backend API — ClusterIP.** The frontend calls it from inside the cluster too — same
reasoning as the database. External users never talk to the backend directly; they only ever
go through the frontend.
3. **Frontend — LoadBalancer** (on a real cloud-hosted cluster). Public internet users need to
reach it, and a cloud provider's LoadBalancer is the standard mechanism for that. NodePort
would technically work but is typically used for development/testing rather than a real
public-facing service on a cloud cluster.
## Self-check
If you chose LoadBalancer for the database or the backend API, reconsider — "internet-reachable
by default" is not the safe default for anything that doesn't need to be, and getting this
choice right the first time avoids a real security exposure later, not just a style issue.
## Instructor Notes
**Facilitation:** Push on the "why not just LoadBalancer everything, it works" instinct some
students will have — this is a good early moment to connect Service-type choice to the security
mindset that ROOT 09 builds on more fully (exposure should be intentional, not the path of
least resistance).
**Approximate timing:** 10 minutes live with discussion; 10 minutes self-paced.
**Optional extension:** ask what would need to be added (not covered in this module) to let
public users reach the frontend at a real domain name over HTTPS rather than a bare
LoadBalancer IP — a natural forward pointer to Ingress, covered in the next module.
@@ -0,0 +1,40 @@
# Launch Lab: Exposing an Application
Time to create a real Service in your disposable Lab and connect it to a real Deployment.
## What you're doing
A `redis` Deployment is running, but other Pods can't reliably reach it because Pod IPs change
whenever a Pod restarts — exactly the problem the lesson opened with. Your task is to create a
stable ClusterIP Service in front of it.
## Before you start
Recall the request path from the lesson: your Service's `selector` has to match the Deployment
Pods' actual labels, or you'll end up with the empty-Endpoints situation from the
demonstration. Check the Deployment's Pod labels before writing your Service's selector, don't
guess at them.
## Your task in this Lab
Create a ClusterIP Service exposing the `redis` Deployment on the correct port. Once it's
created, verify it the same way the demonstration did: `kubectl get service`, then `kubectl get
endpoints` to confirm it actually has a non-empty Endpoints list, not just that the Service
object exists.
This Lab has its own in-context hints if you get stuck.
When you're done, return to this module for a reflection on why service discovery is
infrastructure, not magic.
## Instructor Notes
**Classroom flow:** Encourage students to run `kubectl get endpoints` as their OWN verification
step even though the Lab's automated validation will check this too — building the habit of
checking Endpoints, not just "the Service exists," is the actual transferable skill here.
**Approximate timing:** 10-15 minutes.
**Common mistake to watch for:** a selector that matches on the wrong label key/value, or a
port/targetPort mismatch (the Service's `port` is what clients connect to; `targetPort` is what
the container actually listens on — conflating the two is a very common first-time error).
@@ -0,0 +1,40 @@
# Reflection: Service Discovery Is Infrastructure, Not Magic
You just created a Service that gives a moving set of Pods a stable address. Take a few minutes
to connect this to real operational thinking.
## Reflection questions
1. Before this module, "the app can just connect to redis by name" might have seemed obvious or
automatic. What specific mechanism actually makes that true, and what would break it?
2. If your Service's selector had been wrong (matching zero Pods), what would the SYMPTOM have
looked like from the application's side, versus what the actual CAUSE would have been?
3. Why is checking `kubectl get endpoints` before assuming a networking/DNS/firewall problem a
good default habit, given how common a selector mismatch actually is?
## Real Ops takeaway
**"It's probably a networking issue" is often wrong, and Endpoints is how you find out fast.** A
huge fraction of real "service X can't reach service Y" incidents in Kubernetes are Service
selector mismatches, not actual network problems — checking `kubectl get endpoints` first, before
escalating to firewall rules or DNS debugging, saves real time precisely because this failure
mode produces zero errors at the layers people instinctively check first.
**Stable addressing is what makes rolling updates and self-healing actually usable.** Everything
you learned in ROOT 06 about Pods being replaced during a rollout or after a crash only works
smoothly in practice because Services give callers a stable target that survives those
replacements — without this layer, every Pod replacement would require updating every caller's
configuration by hand.
This module is complete. Continue to the next module.
## Instructor Notes
**Discussion questions for a live classroom:** use question 2 as a discussion prompt — the
symptom/cause gap is exactly why this class of bug is often under-diagnosed in real teams.
**Approximate timing:** 8-10 minutes live discussion; 5 minutes self-paced writing.
**Optional extension:** ask students to write the one-line runbook entry they'd want a future
on-call engineer to have for "Service X seems unreachable" — a good exercise in turning a
lesson into something operationally reusable.
@@ -0,0 +1,90 @@
# Ingress and NetworkPolicy: What They Architecturally Do
## Ingress: routing external HTTP(S) traffic by host/path
You already know a LoadBalancer Service can expose something to the public internet. But a real
application usually needs more than "one raw IP to one Service" — you might want
`api.example.com` and `app.example.com` to route to different backend Services, all through one
entry point, with TLS termination handled in one place instead of per-Service.
**Ingress** is the Kubernetes object for exactly this: a set of HTTP routing rules (by hostname
and/or URL path) that an Ingress controller reads and turns into actual load-balancer/proxy
configuration.
```yaml
apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
name: app-ingress
spec:
rules:
- host: app.example.com
http:
paths:
- path: /
pathType: Prefix
backend:
service:
name: frontend-svc
port: { number: 80 }
```
An important distinction: Ingress is a set of ROUTING RULES, not a load balancer itself — an
Ingress controller (a separate piece of software running in the cluster) is what actually reads
these rules and does the routing. Without a controller installed, an Ingress object exists in
the API but nothing acts on it.
## NetworkPolicy: traffic reachability as something you declare, not assume
By default, every Pod in a Kubernetes cluster can reach every other Pod — there is no built-in
network isolation between them at all. This surprises people coming from a "obviously the
network is locked down unless configured otherwise" assumption. It is exactly backwards from
that assumption: **everything is reachable until you say otherwise.**
A NetworkPolicy changes this for the Pods it selects, by declaring which traffic IS allowed —
everything not explicitly allowed to a Pod covered by at least one NetworkPolicy is then denied.
```yaml
apiVersion: networking.k8s.io/v1
kind: NetworkPolicy
metadata:
name: allow-frontend-to-backend
spec:
podSelector:
matchLabels: { app: backend }
ingress:
- from:
- podSelector:
matchLabels: { app: frontend }
```
This example allows traffic to `backend` Pods only from `frontend` Pods — once this policy
exists and selects `backend`, every OTHER Pod trying to reach `backend` is now blocked, even
though nothing was true about that before the policy existed.
## Why this matters architecturally, before it matters as a security control
Right now, think of NetworkPolicy purely as "declaring intended reachability, not assuming it."
ROOT 09 comes back to NetworkPolicy specifically as a SECURITY control (default-deny postures,
least-privilege network access) — this module is deliberately just the architectural mental
model: Kubernetes doesn't isolate network traffic for you by default, and NetworkPolicy is the
mechanism for declaring the reachability you actually intend.
## Instructor Notes
**Approximate timing:** 15 minutes read; 10 minutes live.
**Likely misconceptions to watch for:**
- Students often assume Ingress by itself "does" the routing. Emphasize the controller
requirement — an Ingress object with no controller installed does nothing.
- The "everything reachable by default" fact genuinely surprises most students the first time
they hear it — it's worth stating plainly and letting it land rather than rushing past it.
**Discussion question:** "If NO NetworkPolicy exists anywhere in a Namespace, what's the actual
reachability between Pods in that Namespace?" (Answer: completely open — every Pod can reach
every other Pod, matching the "everything reachable by default" rule.)
**Optional extension:** ask what would happen if you created a NetworkPolicy that selects
`frontend` Pods but declares no `ingress` rules at all (answer: `frontend` Pods would become
completely unreachable by anything — an empty ingress list inside a NetworkPolicy that HAS an
ingress policyType means "deny all incoming," not "no policy applies").
@@ -0,0 +1,46 @@
# Knowledge Check: Ingress & NetworkPolicy Foundations
---
**1. You create an Ingress object with correct routing rules, but no traffic is ever routed
according to them. What's the most likely reason?**
*Answer:* No Ingress controller is installed/running in the cluster. Ingress objects are just
routing rules; a separate controller has to actually read and act on them, or nothing happens.
---
**2. True or false: by default, a Pod in Namespace A cannot reach a Pod in Namespace B unless a
NetworkPolicy explicitly allows it.**
*Answer:* False — the opposite is true by default. With NO NetworkPolicy in place at all,
every Pod can reach every other Pod regardless of Namespace. NetworkPolicy is what RESTRICTS
this default-open behavior, not what's required to enable connectivity in the first place.
---
**3. A NetworkPolicy selects Pods labeled `app: backend` and declares one ingress rule allowing
traffic from Pods labeled `app: frontend`. What happens to traffic from a Pod labeled
`app: admin-tool` trying to reach `backend`?**
*Answer:* It's blocked. Once a NetworkPolicy selects a Pod, only traffic matching one of its
explicit rules is allowed — everything else to that Pod is denied, including traffic that would
have worked fine before the policy existed.
---
**4. Why is Ingress the right tool for exposing an HTTP application by hostname, rather than
creating a separate LoadBalancer Service per hostname?**
*Answer:* A LoadBalancer Service typically provisions its own external IP/load balancer per
Service — one per hostname would mean paying for and managing N separate external endpoints.
Ingress lets one entry point route to many backend Services by hostname/path, which is both
cheaper and centralizes concerns like TLS termination.
## Instructor Notes
**Facilitation:** Question 2 catches a very common and consequential misconception — worth
confirming out loud that everyone actually updated their mental model, not just guessed
correctly.
**Approximate timing:** 5 minutes.
@@ -0,0 +1,74 @@
# Ephemeral vs. Persistent Storage
## The default: a container's filesystem is thrown away
By default, anything a container writes to its own filesystem disappears the moment that
container is replaced — a crash, a rollout, a reschedule, anything. This is a deliberate design
choice (it's part of what makes a Pod safely disposable/replaceable), but it means "just write
files to disk" silently loses data unless you use one of Kubernetes' actual storage mechanisms.
## emptyDir: shared, but still temporary
An `emptyDir` volume gives a Pod's containers a shared directory that survives a container
restart WITHIN the same Pod, but is deleted the moment the Pod itself is removed. It's the right
tool for two containers in one Pod that need to share files with each other (a sidecar writing
logs another container reads, for example) — not for anything that needs to outlive the Pod.
```yaml
volumes:
- name: shared-data
emptyDir: {}
```
## PersistentVolume & PersistentVolumeClaim: storage that outlives the Pod
A **PersistentVolume (PV)** represents an actual piece of storage (a cloud disk, an NFS share,
whatever the cluster's infrastructure provides) as a Kubernetes object. A
**PersistentVolumeClaim (PVC)** is a Pod's REQUEST for storage matching some criteria (size,
access mode) — the Pod references the PVC, not a PV directly, and Kubernetes binds the PVC to a
matching PV.
```
Pod ──references──> PVC ("I need 5Gi, ReadWriteOnce") ──binds to──> PV (actual storage)
```
This indirection matters: a Pod's manifest doesn't need to know or care exactly which physical
storage backs its PVC — that's resolved separately, and the same PVC keeps working even if the
Pod behind it is replaced.
## StorageClass & dynamic provisioning
Manually creating a PV for every PVC doesn't scale. A **StorageClass** describes a category of
storage (e.g. "fast SSD" vs. "cheap archival") and, when a PVC requests that class, the cluster
can automatically provision a matching PV on demand — this is "dynamic provisioning," and it's
the normal way storage works on any real cloud-hosted cluster. A StorageClass also controls the
**reclaim policy** — what happens to the underlying storage after its PVC is deleted (`Delete`
the data, or `Retain` it for manual recovery).
## The decision in one pass
| You need... | Use |
|---|---|
| Temporary scratch space shared between containers in ONE Pod | `emptyDir` |
| Storage that survives Pod replacement, manually provisioned | PV + PVC |
| The above, provisioned automatically on demand | PVC + StorageClass (dynamic provisioning) |
## Instructor Notes
**Approximate timing:** 15 minutes read; 10 minutes live with the PV/PVC/StorageClass diagram.
**Likely misconceptions to watch for:**
- Students often assume `emptyDir` is "persistent" because the name doesn't obviously say
otherwise. Be explicit: it survives a CONTAINER restart, not a POD deletion.
- The PV/PVC indirection can seem like unnecessary ceremony at first — frame it as the same
"declare what you want, let the system resolve it" pattern from ROOT 05's desired-state
lesson, applied to storage instead of Pod count.
**Discussion question:** "If a Pod using a PVC is deleted and replaced, what happens to its
data?" (Answer: it's preserved — the PVC and its bound PV are separate objects from the Pod,
and a new Pod referencing the same PVC picks up right where the data was left, which is the
entire point of using persistent storage over `emptyDir`.)
**Optional extension:** ask what a `Retain` reclaim policy is protecting against, compared to
`Delete` (answer: accidental data loss from deleting a PVC by mistake — `Retain` keeps the
underlying storage around for manual recovery instead of immediately destroying it).
@@ -0,0 +1,44 @@
# Knowledge Check: Storage Fundamentals
---
**1. Two containers in the same Pod need to share files with each other, but nothing needs to
survive the Pod being replaced. What's the simplest correct choice?**
*Answer:* `emptyDir` — shared within the Pod, deliberately temporary, exactly matching the
requirement. Reaching for a PV/PVC here would be more machinery than the problem needs.
---
**2. A Pod using a PVC is deleted and a new Pod is created referencing the SAME PVC. What
happens to the data?**
*Answer:* It's preserved. The PVC and its bound PV exist independently of any specific Pod — the
new Pod picks up exactly where the data was left, which is the entire reason to use persistent
storage instead of `emptyDir` for anything that needs to outlive a single Pod's lifetime.
---
**3. True or false: a Pod's manifest must specify exactly which PersistentVolume backs its
storage request.**
*Answer:* False. A Pod references a PVC (a request), not a PV directly — the binding between
PVC and an actual PV is resolved separately, which is exactly the indirection that lets the same
Pod manifest work regardless of which physical storage ends up behind it.
---
**4. What does a StorageClass's reclaim policy actually control, and why would a team choose
`Retain` over `Delete` for a production database's storage?**
*Answer:* It controls what happens to the underlying storage after its PVC is deleted. `Retain`
keeps the data around for manual recovery instead of immediately destroying it — a safety
margin against an accidental `kubectl delete pvc` on something genuinely important, at the cost
of needing manual cleanup later.
## Instructor Notes
**Facilitation:** Question 2 is worth confirming lands correctly — it's the single fact that
justifies the entire PV/PVC indirection existing at all.
**Approximate timing:** 5 minutes.
@@ -0,0 +1,86 @@
# How the Scheduler Places Pods, and How Governance Shapes It
## The scheduler's job
Every time a new Pod needs to run, the scheduler decides which node it lands on — you never
manually assign a Pod to a node in normal operation (ROOT 05's mental model). By default, the
scheduler picks based on available resources (does this node have enough free CPU/memory), but
several mechanisms let you INFLUENCE or CONSTRAIN that decision when the default isn't good
enough.
## Steering placement: nodeSelector, taints/tolerations, affinity
- **nodeSelector** — the simplest constraint: "only schedule this Pod on nodes with THIS
label" (e.g. `disktype: ssd`). A blunt but clear tool.
- **Taints and tolerations** — the inverse relationship. A NODE is tainted (marked "don't
schedule here unless you specifically tolerate this taint") and a Pod TOLERATES a specific
taint to be allowed to land there anyway. Commonly used to reserve nodes for specific
workloads (e.g. GPU nodes tainted so only GPU-requiring Pods land there) or to keep general
workloads off nodes reserved for something else.
- **Affinity/anti-affinity** — more expressive rules: "prefer/require scheduling near Pods with
label X" (affinity) or "prefer/require scheduling AWAY from Pods with label X"
(anti-affinity). A common real use: anti-affinity between replicas of the same application, so
a single node failure can't take down every replica at once.
## Priority: which Pods matter more when resources are tight
A **PriorityClass** lets you mark some Pods as more important than others. When the cluster is
under resource pressure, a higher-priority pending Pod can even cause a lower-priority RUNNING
Pod to be evicted (preempted) to make room — this is a real, consequential mechanism, not just a
scheduling hint, and misconfiguring it can mean an unimportant batch job unexpectedly evicts
something that actually mattered.
## PodDisruptionBudget: protecting against VOLUNTARY disruption
A **PodDisruptionBudget (PDB)** limits how many replicas of an application can be taken down
AT ONCE during voluntary disruptions — a node drain for maintenance, a cluster upgrade — by
declaring a minimum number (or percentage) that must stay available. This does NOT protect
against involuntary disruption (a node crashing unexpectedly) — it specifically constrains
operations that Kubernetes itself controls the timing of.
```yaml
apiVersion: policy/v1
kind: PodDisruptionBudget
metadata:
name: web-pdb
spec:
minAvailable: 2
selector:
matchLabels: { app: web }
```
Without a PDB, a node drain during routine maintenance could legally take down every replica of
`web` simultaneously if they all happened to be on nodes being drained together — a PDB is what
prevents that from being "technically allowed."
## ResourceQuota & LimitRange: governance at the Namespace level
A **ResourceQuota** caps the TOTAL resources (CPU, memory, object counts) a Namespace can
consume — useful for multi-team clusters where one team's runaway workload shouldn't be able to
starve everyone else. A **LimitRange** sets DEFAULT and/or min/max resource requests/limits for
individual containers within a Namespace, so a Pod created without explicit resource settings
still gets sensible ones rather than none at all.
## Instructor Notes
**Approximate timing:** 20 minutes read; 15 minutes live given the number of concepts covered.
**Likely misconceptions to watch for:**
- Taints/tolerations are frequently confused with affinity — clarify the directionality: a
taint REPELS by default (node says no); a toleration is what lets a specific Pod through
anyway. Affinity is the Pod expressing a preference, not the node restricting access.
- Students sometimes assume a PDB prevents ALL disruption. Be explicit that it only constrains
VOLUNTARY disruption (things Kubernetes/an operator controls the timing of) — a hardware
failure ignores PDBs entirely, because nobody is "asking permission" for a crash.
**Discussion question:** "Why would a real team use anti-affinity between replicas of the same
application instead of just trusting the scheduler's default spread?" (Answer: the default
scheduler does consider spread as one factor among several, but doesn't GUARANTEE it the way an
explicit anti-affinity rule does — for something where "don't lose all replicas to one node
failure" is a hard requirement, not just a nice-to-have, an explicit rule is safer than an
implicit tendency.)
**Optional extension:** ask what would happen to a Namespace's Pods if a ResourceQuota were
added AFTER Pods without explicit resource requests already existed there (a good bridge to why
LimitRange defaults matter — a Quota alone doesn't retroactively fix Pods created without
resource requests, it just constrains what NEW Pods can consume going forward).
@@ -0,0 +1,48 @@
# Knowledge Check: Scheduling & Resource Governance
---
**1. A node is tainted `dedicated=gpu:NoSchedule`. A Pod with no matching toleration is
pending and never gets scheduled anywhere else, even though other untainted nodes have free
capacity. What's actually going on?**
*Answer:* Nothing is wrong — the taint only affects the tainted node specifically; it doesn't
explain why the Pod isn't landing elsewhere. If it's stuck pending entirely, the cause is
something else (insufficient resources cluster-wide, a nodeSelector/affinity rule that can't be
satisfied anywhere) — the taint itself only ever repels from the ONE node it's applied to.
---
**2. During a planned node drain for maintenance, would you expect a PodDisruptionBudget to
prevent an UNRELATED node from crashing unexpectedly at the same time?**
*Answer:* No. A PDB only constrains VOLUNTARY disruptions — operations Kubernetes/an operator
controls the timing of, like a drain. An unrelated hardware failure is involuntary and ignores
PDBs entirely; nothing is "asking permission" for a crash.
---
**3. True or false: a higher-priority pending Pod can cause a lower-priority, already-RUNNING
Pod to be evicted to make room.**
*Answer:* True — this is what Pod priority/preemption actually does under resource pressure,
not just a scheduling hint. Misconfigured priorities can have real, disruptive consequences for
this reason.
---
**4. A team notices new Pods in their Namespace keep getting created with no CPU/memory
requests at all, even though nobody set that intentionally. What governance mechanism would fix
this going forward, and what would it NOT fix?**
*Answer:* A LimitRange with default requests/limits would apply sensible defaults to future
Pods created without explicit values. It would NOT retroactively change Pods that already exist
— it only affects new Pod creation from the point it's added.
## Instructor Notes
**Facilitation:** Question 2 reinforces a genuinely important, often-missed distinction
(voluntary vs. involuntary disruption) — worth confirming it lands, not just that the answer was
guessed correctly.
**Approximate timing:** 5-7 minutes given the density of this module's lesson.
@@ -0,0 +1,87 @@
# Defense in Depth & the Kubernetes Security Model
## Security is a posture, not a single setting
There is no single "make it secure" switch in Kubernetes. Real security comes from **defense in
depth** — multiple independent layers, each reducing what an attacker (or a bug) can do if an
earlier layer fails. If a container has a vulnerability that lets an attacker execute arbitrary
code, the question that actually matters is: what can that code DO once it's running? A
container running as root, with every Linux capability, on a writable filesystem, with no
restrictions at all, can do far more damage than one deliberately hardened to need almost
nothing.
## Least privilege: grant only what's actually needed
The organizing principle behind everything in this course is **least privilege**: a workload
should have exactly the permissions and capabilities it needs to do its job, and nothing more.
This sounds obvious stated plainly, but the DEFAULT behavior of a plain container is closer to
"maximum privilege unless told otherwise" — root user, all standard Linux capabilities, a
writable filesystem. Hardening a Pod means deliberately narrowing that down.
## SecurityContext: where you actually configure this
`securityContext` (settable at the Pod level and per-container) is where you declare these
restrictions:
```yaml
spec:
securityContext:
runAsNonRoot: true
runAsUser: 1000
containers:
- name: app
securityContext:
readOnlyRootFilesystem: true
capabilities:
drop: ["ALL"]
```
- **`runAsNonRoot` / `runAsUser`** — the container process runs as a specific non-root user
instead of root. If a container image was built to require root and you set this, it will
fail to start — which is a good, loud failure, not a silent security gap. Hardening
sometimes surfaces an image's OWN bad assumptions.
- **`capabilities: drop: ["ALL"]`** — Linux capabilities are fine-grained permissions
(`NET_BIND_SERVICE`, `SYS_ADMIN`, dozens more) a process can hold even without full root.
Dropping all of them, then adding back only the specific ones actually needed, is the
least-privilege pattern applied to capabilities specifically.
- **`readOnlyRootFilesystem: true`** — the container's own filesystem cannot be written to at
all (use an explicit `emptyDir` volume, ROOT 08, for anything that genuinely needs to write
temporary files). This closes off a whole category of attack that relies on writing a
malicious file to disk.
## Why this matters even when "nothing is currently wrong"
None of these settings fix a bug or a vulnerability — they limit the BLAST RADIUS if one exists
that you don't yet know about. A container hardened with non-root, dropped capabilities, and a
read-only filesystem gives a successful exploit dramatically less to work with than an
unhardened one, even against the exact same vulnerability. This is the entire point of defense
in depth: you don't rely on any single layer being perfect.
## Instructor Notes
**Approximate timing:** 15 minutes read; 10-12 minutes live with the demonstration.
**Demo plan:** Have the demonstration activity ready to run right after this lesson — seeing a
concrete before/after Pod definition lands the abstract "least privilege" principle far better
than the lesson text alone.
**Likely misconceptions to watch for:**
- Students sometimes think hardening settings are only relevant "if you expect to be attacked."
Reframe: defense in depth assumes SOMETHING will eventually go wrong somewhere (a
vulnerability, a bug, a misconfiguration) and prepares for that, rather than betting
everything on nothing ever going wrong.
- `runAsNonRoot: true` failing a Pod's startup is sometimes read as "the security setting is
broken." It's the opposite — it's correctly refusing to let a root-requiring image start,
which is valuable, actionable information about the image itself.
**Discussion question:** "If dropping all capabilities breaks a container that turns out to
genuinely need one specific capability, what's the right fix — removing the drop, or something
more targeted?" (Answer: add back only that ONE specific capability rather than removing the
blanket drop — least privilege means "exactly what's needed," not "give up and grant
everything again.")
**Optional extension:** ask students to identify one setting from this lesson that would have
made zero difference against a vulnerability that lets an attacker read environment variables
(a good check that they understand these are layered, not universal, protections — the answer
is that none of SecurityContext's settings here directly protect secrets stored in env vars;
that's a different concern, covered later in this course).
@@ -0,0 +1,87 @@
# Demonstration: A Pod Before and After Hardening
## Before: the default, unhardened Pod
```yaml
apiVersion: v1
kind: Pod
metadata:
name: app-unhardened
spec:
containers:
- name: app
image: myapp:latest
```
Checking what this actually runs as:
```
$ kubectl exec app-unhardened -- id
uid=0(root) gid=0(root) groups=0(root)
$ kubectl exec app-unhardened -- touch /etc/anything-i-want
$ kubectl exec app-unhardened -- ls -la /etc/anything-i-want
-rw-r--r-- 1 root root 0 Jan 1 00:00 /etc/anything-i-want
```
Running as root, with a fully writable filesystem, including system directories. This is not a
misconfiguration — it's simply what happens when nothing restricts it.
## After: the same application, hardened
```yaml
apiVersion: v1
kind: Pod
metadata:
name: app-hardened
spec:
securityContext:
runAsNonRoot: true
runAsUser: 1000
containers:
- name: app
image: myapp:latest
securityContext:
readOnlyRootFilesystem: true
capabilities:
drop: ["ALL"]
```
```
$ kubectl exec app-hardened -- id
uid=1000 gid=0 groups=0
$ kubectl exec app-hardened -- touch /etc/anything-i-want
touch: /etc/anything-i-want: Read-only file system
```
Same application image, same functionality (assuming the app doesn't itself require root or
filesystem writes it wasn't told about) — but a compromise of this container now can't write
to the filesystem, can't use the elevated capabilities that were dropped, and never had root to
begin with.
## What this actually buys you
Nothing here fixed a bug in `myapp:latest` — the image is identical in both cases. What changed
is what an attacker (or a bug behaving unexpectedly) could DO if something inside that container
went wrong. The unhardened version had almost no limits; the hardened version has several
independent ones, any of which alone would have blocked the `touch` command above.
## Instructor Notes
**Demo script:** Run both Pods live if time allows — watching `touch` succeed on one and fail
on the other in real time is far more convincing than reading it.
**Approximate timing:** 8-10 minutes live; 5-7 minutes self-paced.
**Common misconception to preempt:** students sometimes read the hardened Pod's failed `touch`
as "hardening broke something." Reinforce: the FUNCTIONALITY didn't change (the application
itself never needed to write to `/etc`) — only an unnecessary, unused capability was removed.
If hardening breaks something the application genuinely needs, that's real information about
the application, not a reason to skip hardening.
**Optional extension:** ask what would happen if `myapp:latest` were built assuming it could
write a cache file to `/tmp` inside the container — a good bridge to the fact that
`readOnlyRootFilesystem` often needs an explicit `emptyDir` volume mounted at the specific path
an application legitimately needs to write to (ROOT 08), rather than being an all-or-nothing
choice.
@@ -0,0 +1,47 @@
# Knowledge Check: Security Model & SecurityContext
---
**1. A container is hardened with `capabilities: drop: ["ALL"]` and then fails because it
genuinely needs to bind to a low-numbered network port, which requires `NET_BIND_SERVICE`.
What's the least-privilege fix?**
*Answer:* Add back only `NET_BIND_SERVICE` specifically (`capabilities: add:
["NET_BIND_SERVICE"]` alongside the drop-all), not remove the blanket drop entirely.
Least privilege means granting exactly what's needed, not reverting to granting everything.
---
**2. True or false: setting `runAsNonRoot: true` fixes a vulnerability inside the application
itself.**
*Answer:* False. It doesn't fix anything about the application's code — it limits what a
compromise of that code could DO, by ensuring the process never has root privileges to begin
with. This is the defense-in-depth distinction: reducing blast radius, not eliminating bugs.
---
**3. Why might `runAsNonRoot: true` cause a Pod to fail to start entirely, and is that a
problem with the setting?**
*Answer:* If the container image was built assuming it runs as root (e.g. it tries to bind a
privileged port, or write to a root-owned directory), the Pod will fail to start under
`runAsNonRoot`. This is NOT a problem with the setting — it's valuable, actionable information
that the image itself makes an assumption that should probably be fixed.
---
**4. A container has `readOnlyRootFilesystem: true` and needs to write temporary cache files.
What's the correct way to allow that without abandoning the read-only filesystem entirely?**
*Answer:* Mount an explicit `emptyDir` volume (ROOT 08) at the specific path the application
needs to write to. This keeps the rest of the filesystem read-only while allowing the one
legitimately-needed writable location.
## Instructor Notes
**Facilitation:** Question 1 and question 4 both reinforce the same "narrow the exception, don't
remove the protection" pattern — worth calling out that they're the same principle applied
twice.
**Approximate timing:** 5-7 minutes.
@@ -0,0 +1,51 @@
# Guided Exercise: Planning a Pod Hardening Checklist
Paper-and-thinking exercise before the Labs.
## The scenario
You're handed a Pod spec for a small internal API with NO `securityContext` set at all — the
fully-default, unhardened case from the demonstration. Your team lead asks you to harden it
before it ships.
## Your task
Without writing the actual YAML yet, answer these:
1. List the settings you'd add, in the order you'd verify them (hint: there are at least three
distinct concerns from the lesson — user/root, filesystem, capabilities).
2. For each setting, name ONE way you'd notice if you'd broken the application by adding it
(what would the failure actually look like?).
3. If the application genuinely needs to write a cache file to disk, does that mean you should
skip `readOnlyRootFilesystem` entirely? What's the more precise fix?
4. Suppose after hardening, the container still runs fine but a security scan flags that it
still has the `NET_RAW` capability. What's the most likely reason, and what's the fix?
## A worked answer to check yourself against
1. In a reasonable order: (a) `runAsNonRoot`/`runAsUser` — a fundamental identity change,
surfaces image assumptions fastest; (b) `capabilities: drop: ["ALL"]` — narrow, usually safe
for a typical web API; (c) `readOnlyRootFilesystem: true` — most likely to need an
accompanying volume, so verify last once the others are confirmed working.
2. (a) Pod fails to start entirely (`CrashLoopBackOff` or an immediate error) if the image
assumed root. (b) The application errors on a specific operation that needed a capability
you dropped (e.g. failing to bind a privileged port). (c) A write operation fails at runtime
(a log line, an exception) the first time the app tries to write to disk.
3. No — the fix is mounting an explicit `emptyDir` volume at the specific path the cache needs,
keeping the rest of the filesystem read-only rather than abandoning the protection entirely.
4. Most likely: `capabilities: drop: ["ALL"]` was never actually applied (a YAML indentation
mistake, or it was added to the Pod's securityContext instead of the container's — capability
drops are container-level, not Pod-level). The fix is verifying the drop is actually present
on the CONTAINER's securityContext specifically.
## Instructor Notes
**Facilitation:** Question 4 is deliberately tricky — Pod-level vs. container-level
`securityContext` fields is a real, common source of "I set this and it didn't work" confusion
worth surfacing here before students hit it in a Lab.
**Approximate timing:** 15 minutes live with discussion; 12-15 minutes self-paced.
**Optional extension:** ask students to identify which of the settings in this exercise would
be MOST valuable to apply first if they could only add one to a large, existing fleet of
unhardened Pods under time pressure, and why.
@@ -0,0 +1,42 @@
# Reflection: Least Privilege Is a Default, Not an Afterthought
You just hardened real Pods across several Labs — non-root, dropped capabilities, a read-only
filesystem, and a full SecurityContext review. Take a few minutes to connect this to real
practice.
## Reflection questions
1. Before this module, would you have described "runs as root with a fully writable
filesystem" as insecure, or just as "the default, unremarkable configuration"? Has that
changed?
2. None of the settings you configured fixed a bug in any application. What did they actually
change, precisely?
3. If your team had to choose between hardening every new Pod by default (as a policy) versus
hardening Pods only after an incident reveals a gap, which produces less total risk over
time, and why?
## Real Ops takeaway
**Unhardened is not neutral — it's the maximum-privilege default.** A container with no
SecurityContext configured isn't "unopinionated"; it's root, every capability, fully writable —
the MOST privileged configuration possible, not a safe middle ground. Teams that treat hardening
as optional are choosing maximum blast radius by default, usually without realizing they're
choosing anything at all.
**Defense in depth means no single mistake should be catastrophic.** The value of stacking
non-root + dropped capabilities + read-only filesystem isn't that any ONE of them is perfect —
it's that a real compromise would have to defeat several independent restrictions simultaneously
instead of exploiting one gap that grants everything. This is exactly why security-minded teams
apply all of these by default rather than picking "the one that matters most."
This module is complete. Continue to the next module.
## Instructor Notes
**Discussion questions for a live classroom:** question 3 is worth pushing on directly — it's
the actual business case for security-by-default, not just a technical preference.
**Approximate timing:** 8-10 minutes live discussion; 5 minutes self-paced writing.
**Optional extension:** ask students to draft a one-paragraph "default Pod hardening policy"
their hypothetical team would adopt, based on what they've learned in this module.
@@ -0,0 +1,90 @@
# Identity for Workloads: ServiceAccounts & RBAC
## Workloads need an identity too, separate from yours
When YOU run `kubectl`, you're authenticated as yourself. But a Pod running INSIDE the cluster
that needs to call the Kubernetes API (to list other Pods, read a ConfigMap, whatever) needs its
own identity — it can't and shouldn't use your personal credentials. That identity is a
**ServiceAccount**.
Every Pod runs as SOME ServiceAccount — if you don't specify one, it uses the `default`
ServiceAccount in its Namespace, which by default has essentially no permissions. A Pod's
ServiceAccount token is automatically mounted into the container unless you explicitly disable
that (`automountServiceAccountToken: false`) — worth doing for any Pod that never actually needs
to call the Kubernetes API at all, since an unused, mounted credential is still something an
attacker could steal and use.
## RBAC: what that identity is actually allowed to do
Having an identity (a ServiceAccount) doesn't grant any permissions by itself — **RBAC
(Role-Based Access Control)** is the separate system that defines what an identity can DO.
- A **Role** (namespace-scoped) or **ClusterRole** (cluster-wide) defines a set of permissions:
which API resources, which verbs (get/list/watch/create/update/delete).
- A **RoleBinding** (or **ClusterRoleBinding**) connects a Role/ClusterRole to a specific
identity (a ServiceAccount, a user, or a group) — the Role alone grants nothing to anyone
until it's bound.
```yaml
apiVersion: rbac.authorization.k8s.io/v1
kind: Role
metadata:
name: pod-reader
namespace: default
rules:
- apiGroups: [""]
resources: ["pods"]
verbs: ["get", "list"]
---
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
name: read-pods
namespace: default
subjects:
- kind: ServiceAccount
name: my-app
roleRef:
kind: Role
name: pod-reader
apiGroup: rbac.authorization.k8s.io
```
This grants the `my-app` ServiceAccount permission to `get`/`list` Pods in the `default`
Namespace — and nothing else. It cannot delete Pods, cannot touch Secrets, cannot do anything
not explicitly listed.
## Role vs. ClusterRole: scope matters
A Role only grants permissions within the ONE Namespace it's defined in. A ClusterRole can grant
permissions across the entire cluster (or, bound via a RoleBinding instead of a
ClusterRoleBinding, can also be reused namespace-by-namespace) — reach for a ClusterRole only
when the workload genuinely needs cluster-wide visibility, not by default.
## Least privilege, applied to permissions specifically
The same principle from the previous module applies directly here: grant the narrowest set of
verbs on the narrowest set of resources that the workload actually needs. A Role granting
`get`/`list` on Pods is very different from one granting `*` on `*` — the latter is
"root-equivalent" API access, and should be treated with exactly that level of caution.
## Instructor Notes
**Approximate timing:** 15 minutes read; 10 minutes live.
**Likely misconceptions to watch for:**
- Students often conflate "ServiceAccount" with "user account for logging in." A ServiceAccount
is specifically an identity for WORKLOADS, not a human login mechanism.
- The Role/RoleBinding two-step (define permissions, then separately grant them to someone) is
sometimes seen as redundant. Emphasize the reuse benefit: the same Role can be bound to
multiple identities without redefining the permission set each time.
**Discussion question:** "Why might you explicitly disable automounting a ServiceAccount token
for a Pod that never calls the Kubernetes API?" (Answer: an unused but present credential is
still something an attacker who compromises the container could steal and use elsewhere —
removing it entirely removes that risk for a Pod that never needed it.)
**Optional extension:** ask what the practical difference is between granting a ClusterRole via
a RoleBinding (scoped to one Namespace) versus a ClusterRoleBinding (cluster-wide) — a good
check that students understand the Role/ClusterRole and Binding-type distinctions are
independent axes, not the same choice.
@@ -0,0 +1,44 @@
# Knowledge Check: ServiceAccounts & RBAC
---
**1. A Pod is created with no ServiceAccount specified. What identity does it actually run as,
and what can that identity do by default?**
*Answer:* The `default` ServiceAccount in its Namespace, which by default has essentially no
permissions — it can authenticate to the API but is granted nothing until an RBAC binding says
otherwise.
---
**2. You create a Role granting `get`/`list` on Pods, but a workload still can't read Pods.
What's the most likely missing piece?**
*Answer:* A RoleBinding (or ClusterRoleBinding) connecting that Role to the workload's actual
ServiceAccount. A Role by itself grants nothing to anyone — it has to be bound to an identity.
---
**3. True or false: a ClusterRole can only ever be applied cluster-wide.**
*Answer:* False. A ClusterRole can be bound via a RoleBinding to apply within just ONE
Namespace (reusing a cluster-wide-DEFINED permission set in a namespace-SCOPED way), or via a
ClusterRoleBinding to apply cluster-wide. The Role-type and Binding-type are independent
choices.
---
**4. Why would a security review flag a Role granting `verbs: ["*"]` on `resources: ["*"]`
even if the workload "seems to work fine"?**
*Answer:* That grant is root-equivalent API access — it violates least privilege regardless of
whether the workload happens to only use a small subset of it today. "Works fine" doesn't mean
"correctly scoped" — an over-broad grant is a real risk the moment that workload (or its
credentials) is compromised, whether or not it's ever exploited in practice.
## Instructor Notes
**Facilitation:** Question 4 is worth discussing even if everyone answers correctly — the "it
works, so what's the problem" instinct is exactly what least-privilege review exists to counter.
**Approximate timing:** 5 minutes.
@@ -0,0 +1,76 @@
# NetworkPolicy as a Security Control & Supply Chain Trust
## NetworkPolicy, revisited as a security posture
ROOT 07 introduced NetworkPolicy architecturally: Kubernetes doesn't isolate Pod-to-Pod traffic
by default, and NetworkPolicy is how you declare intended reachability. Here, the same
mechanism is the point of a deliberate SECURITY practice: **default deny**.
A default-deny policy blocks all traffic to selected Pods, and you then explicitly allow only
what's actually needed:
```yaml
apiVersion: networking.k8s.io/v1
kind: NetworkPolicy
metadata:
name: default-deny
spec:
podSelector: {} # selects EVERY Pod in the namespace
policyTypes: ["Ingress"]
```
An empty `podSelector: {}` with no ingress rules means "select every Pod, allow nothing in" —
the network equivalent of the SecurityContext principle from earlier in this course: start
from nothing, add back only what's proven necessary. This is exactly the opposite of
Kubernetes' un-configured default (everything open), which is precisely why it has to be
declared explicitly rather than relying on any built-in setting.
**Egress restriction** works the same way in reverse — restricting what a Pod can call OUT to,
not just what can call IN. A compromised Pod that can freely make outbound connections to
anything is far more dangerous (data exfiltration, calling out to an attacker's server) than one
restricted to only the specific destinations it legitimately needs.
## Supply chain: trusting what you run before it ever starts
Everything covered so far in this course assumes the container image itself is trustworthy.
Supply-chain security is about that assumption specifically:
- **Image-pull secrets** — when pulling from a private registry, the cluster needs credentials
to authenticate. Storing and using these correctly (rather than, say, a publicly-readable
registry with no access control) is a basic supply-chain control: only images from a trusted,
access-controlled source get pulled at all.
- **Minimizing image footprint** (referenced here, not a hands-on Lab in this module) — a
smaller image means fewer packages, fewer known CVEs, and a smaller attack surface if the
image is ever compromised.
## TLS at the Ingress layer: protecting data in transit
Recall ROOT 07's Ingress lesson — routing external HTTP(S) traffic by hostname/path. Configuring
TLS termination at that same Ingress layer means traffic between users and your cluster is
encrypted, protecting against interception on the network path. This is a security concern
layered on top of the same architectural mechanism, the same relationship NetworkPolicy has to
its ROOT 07 introduction.
## Instructor Notes
**Approximate timing:** 15 minutes read; 10 minutes live.
**Likely misconceptions to watch for:**
- Students sometimes think "default deny" means blocking ALL traffic including what the
application needs to function. Clarify: default deny is the STARTING point; you then add
specific allow rules for exactly what's needed — the goal state is fully functional AND fully
intentional, not non-functional.
- Egress restriction is sometimes seen as less important than ingress. Emphasize the
exfiltration angle explicitly — a compromised Pod's outbound reach is just as much a real
risk as inbound exposure.
**Discussion question:** "Why is 'default deny, then explicitly allow' a better starting
posture than 'default allow, then explicitly block known-bad traffic'?" (Answer: default-deny
means a NEW, unanticipated attempt to reach or leave a Pod is blocked by default; default-allow
means anything not YET identified as bad gets through — you're always one step behind an
attacker under the second model.)
**Optional extension:** ask what a real team would want to verify before trusting a
publicly-available container image from an unfamiliar source, beyond just "does it work" — a
good bridge into image scanning/provenance concepts (not built as a hands-on Lab in this course,
but worth naming as a real practice).
@@ -0,0 +1,45 @@
# Knowledge Check: Network & Supply Chain Security
---
**1. A NetworkPolicy has `podSelector: {}` with `policyTypes: ["Ingress"]` and no ingress rules
defined. What's the practical effect on every Pod in that namespace?**
*Answer:* Every Pod is selected, and since no ingress rule allows anything, all incoming traffic
to every Pod is denied — this is the "default deny" starting posture, applied namespace-wide.
---
**2. Why is restricting EGRESS (outbound) traffic from a Pod a real security control, not just
a mirror-image nicety of ingress restriction?**
*Answer:* A compromised Pod with unrestricted egress can exfiltrate data to an attacker-controlled
destination or call out to download additional malicious payloads. Restricting egress to only
what's legitimately needed limits what a compromise can accomplish, independent of whether
inbound access was ever an issue.
---
**3. True or false: "default deny, then explicitly allow" and "default allow, then explicitly
block known-bad traffic" provide equivalent security given the same set of rules.**
*Answer:* False. Default-deny blocks anything NOT yet explicitly allowed, including new/
unanticipated attempts. Default-allow only blocks what's already been identified as bad — an
attacker doing something not yet on the block list gets through under the second model but not
the first.
---
**4. Why does minimizing a container image's footprint (fewer packages) improve supply-chain
security specifically, rather than just making the image smaller/faster to pull?**
*Answer:* Fewer installed packages means fewer potential known vulnerabilities (CVEs) present in
the image at all, and a smaller attack surface if the image is ever compromised — it's a
security property, not merely a performance optimization.
## Instructor Notes
**Facilitation:** Question 3 is the core conceptual point of this module — worth confirming it's
genuinely understood, not just correctly guessed.
**Approximate timing:** 5-7 minutes.
@@ -0,0 +1,64 @@
# Pod Security Admission & a Survey of Runtime Hardening
This module is deliberately a survey, not a deep dive — the topics here are real and important,
but lean toward cluster-operator/platform-team concerns rather than the daily-driver skills most
ROOT_ learners will use constantly. Treat the labs in this module as good-to-know, not required
mastery, before moving on.
## Pod Security Admission: enforcing a baseline across a Namespace
Everything you configured by hand in earlier modules (non-root, dropped capabilities, read-only
filesystem) can also be ENFORCED automatically at the Namespace level via **Pod Security
Admission (PSA)** — a label on the Namespace itself that rejects any Pod violating a chosen
security standard (`privileged`, `baseline`, or `restricted`, from least to most strict):
```yaml
apiVersion: v1
kind: Namespace
metadata:
name: production
labels:
pod-security.kubernetes.io/enforce: restricted
```
This replaces the older PodSecurityPolicy (PSP) mechanism, which was removed from Kubernetes —
if you encounter PSP in older documentation or an older cluster, know that PSA is its current
replacement.
## Immutable Secrets: preventing a class of accidental change
A Secret can be marked `immutable: true`, which prevents its data from being changed after
creation (a new Secret with a new name has to be created instead, and workloads updated to
reference it). This trades a small amount of operational flexibility for a real safety
property: an accidental or malicious edit to a live Secret can't silently happen.
## A survey of further topics (labs available, treat as optional depth)
- **Audit policy** — configuring what the Kubernetes API server logs about requests made against
it (who did what, when) — genuinely important for incident investigation, but a cluster-admin
concern, not something most workload teams configure themselves.
- **RuntimeClass** — lets specific Pods run under a different container runtime configuration
(e.g. an extra-sandboxed runtime like gVisor or Kata Containers) for workloads that need
stronger isolation than the default runtime provides — relevant mainly for genuinely
untrusted or high-risk workloads, not typical applications.
## Instructor Notes
**Approximate timing:** 15 minutes read (shorter than other lessons — deliberately survey-depth).
**Framing for instructors:** Be explicit with students that this module is intentionally
lighter than the earlier ones in this course — the goal is awareness ("this exists, here's
roughly what it's for") rather than hands-on fluency, consistent with not every CKS-style topic
belonging in the core learning path.
**Discussion question:** "Why would a platform team prefer enforcing security standards via
Pod Security Admission at the Namespace level, instead of trusting every team to configure
SecurityContext correctly on every Pod by hand?" (Answer: PSA provides a hard backstop —
correctly-configured SecurityContext relies on every individual Pod author doing it right every
time; PSA rejects violations automatically regardless of whether any individual author
remembered to.)
**Optional extension:** ask which of `privileged`/`baseline`/`restricted` a team should start a
brand-new, security-conscious project with, and why not jump straight to the strictest option
on a cluster already running older, unaudited workloads (a good practical judgment question
about migration risk, not just definitions).
@@ -0,0 +1,92 @@
# The RootNode Troubleshooting Framework
## Why a framework, not just "get good at kubectl"
The gold-standard Health Probes module taught you a lot about ONE specific failure mode
(readiness probe misconfiguration) and the specific commands to diagnose it. This module steps
back and asks: what's the repeatable PROCESS that works for almost any Kubernetes failure, not
just the ones you've already seen before?
Guessing under pressure — trying random fixes and seeing what sticks — is slow, often makes
things worse, and doesn't build a transferable skill. A framework does.
## Observe → Gather Evidence → Form Hypothesis → Test → Repair → Validate → Prevent Recurrence
**Observe** — what's the actual, specific symptom? Not "it's broken," but "the Deployment shows
0/3 Ready" or "requests are timing out" or "the Pod restarts every 30 seconds." Precision here
saves time later.
**Gather Evidence** — before touching anything, collect what the system itself is telling you:
`kubectl get pods`, `kubectl describe pod`, `kubectl logs`, `kubectl get events`. Resist the urge
to start changing things before you've looked.
**Form Hypothesis** — based on the evidence, state a SPECIFIC guess about the cause. "The
container is crashing because the command it's told to run doesn't exist" is testable. "Something's
wrong with networking" is not specific enough to act on yet.
**Test** — check whether your hypothesis is actually true, ideally without yet making the fix
(read the exact command being run, compare against what the image expects) — confirm before you
commit to a repair.
**Repair** — make the minimal change that addresses the confirmed cause. Not a bigger change
"while you're in there" — exactly the fix the evidence supports.
**Validate** — confirm the fix actually worked, using the same kind of evidence you gathered
initially (not just "I made a change, it should be fine now").
**Prevent Recurrence** — the step most often skipped under time pressure. Could this class of
mistake happen again? Is there a smaller, structural change (a default, a validation, a check)
that would catch it earlier next time?
## Applying it: a CrashLoopBackOff
- **Observe:** `crash-app`'s Pods show `STATUS: CrashLoopBackOff`, restart count climbing.
- **Gather Evidence:** `kubectl describe deployment crash-app` (check the configured command),
`kubectl logs -l app=crash-app` (what did the container actually print before dying, if
anything).
- **Form Hypothesis:** "The command override is invalid/wrong for this image, so the container
exits immediately every time it starts."
- **Test:** compare the command actually configured against what the image's default/expected
entrypoint should be.
- **Repair:** fix the command to what the container image actually expects.
- **Validate:** `kubectl get pods` shows `Running`, restart count stops climbing.
- **Prevent Recurrence:** a code-review habit of never overriding a container's command without
verifying it against the image's documentation first.
## Applying it: a broken Service selector
- **Observe:** traffic isn't reaching `my-svc`'s backend at all.
- **Gather Evidence:** `kubectl get endpoints my-svc` (empty?), `kubectl get pods
--show-labels` (what labels do the actual Pods have?).
- **Form Hypothesis:** "The Service's selector doesn't match the Pods' actual labels."
- **Test:** compare `kubectl describe service my-svc`'s selector against the Pods' real labels
directly, side by side.
- **Repair:** correct the selector to match.
- **Validate:** `kubectl get endpoints my-svc` now shows the Pod IPs.
- **Prevent Recurrence:** keeping label keys/values consistent (or generated from one source)
between a Deployment's Pod template and any Service that targets it.
## Instructor Notes
**Approximate timing:** 15 minutes read; 10-12 minutes live walking through both worked
examples.
**Demo plan:** Use the demonstration activity right after this lesson to show the CrashLoopBackOff
example live, narrating each framework step explicitly as you go rather than just running
commands.
**Likely misconceptions to watch for:**
- Students under time pressure often skip straight to "Repair" without confirming a hypothesis
first. Reinforce that a wrong guess implemented as a "fix" can make evidence harder to read
afterward, not easier.
- "Prevent Recurrence" is the step most likely to be treated as optional/skippable. Frame it as
what separates a team that keeps hitting the same incident from one that doesn't.
**Discussion question:** "What's the cost of skipping 'Gather Evidence' and jumping straight to
a guessed fix, even if the guess happens to be right?" (Answer: even a correct guess doesn't
teach you whether your reasoning was right — you got lucky, and the same class of mistake could
still recur since you never confirmed the actual cause.)
**Optional extension:** ask students to apply this exact framework, from memory, to the gold
module's `rootnode-probe-port-mismatch` incident they already solved — a good retroactive
exercise connecting a lab they already completed to the generalized framework.
@@ -0,0 +1,91 @@
# Demonstration: Applying the Framework to a CrashLoopBackOff
Watch the full Observe → Evidence → Hypothesis → Test → Repair → Validate → Prevent sequence
against a real symptom, narrated step by step.
## Observe
```
$ kubectl get pods
NAME READY STATUS RESTARTS AGE
crash-app-6d9f8b7c5d-abcde 0/1 CrashLoopBackOff 5 4m
```
Specific symptom: `CrashLoopBackOff`, restart count climbing (5 and counting) — the container
is starting, exiting, and being restarted repeatedly, not just failing to start once.
## Gather Evidence
```
$ kubectl logs crash-app-6d9f8b7c5d-abcde
nginx: [emerg] invalid command "daemon-off": expected valid command
```
```
$ kubectl describe deployment crash-app
...
Command:
nginx
-g
daemon-off;
...
```
The logs show nginx itself rejecting the command it was given. The Deployment's configured
command shows exactly why: `daemon-off;` (a typo — missing space, should be `daemon off;`).
## Form Hypothesis
"The container's command override has a syntax error that nginx can't parse, so nginx exits
immediately every time it starts — which is why it's crash-looping rather than just failing to
start once."
## Test
Compare the broken command (`daemon-off;`) against nginx's actual expected syntax
(`daemon off;`, two separate words) — confirmed: this is exactly the kind of typo that would
produce exactly this error.
## Repair
```
$ kubectl patch deployment crash-app --type='json' \
-p='[{"op":"replace","path":"/spec/template/spec/containers/0/command","value":["nginx","-g","daemon off;"]}]'
```
## Validate
```
$ kubectl get pods
NAME READY STATUS RESTARTS AGE
crash-app-7f8c9d6b5d-fghij 1/1 Running 0 15s
```
New Pod, `Running`, `RESTARTS: 0` — the fix is confirmed, not just assumed.
## Prevent Recurrence
A command override like this is a hand-typed string with no validation until the container
actually tries to run it. A team that hit this once might decide: don't override a well-known
image's default command unless there's a specific reason to, and if you must, test the exact
command string locally (`docker run` or similar) before deploying it — catching a typo in
seconds locally beats debugging a CrashLoopBackOff in the cluster.
## Instructor Notes
**Demo script:** Run this live if time allows, deliberately narrating which framework step
you're on at each command — students retain the framework far better tied to real commands than
as an abstract list.
**Approximate timing:** 8-10 minutes live; 5-7 minutes self-paced.
**Common misconception to preempt:** students sometimes skip straight from "Observe" to
"Repair" once they spot the typo, without stating a hypothesis or testing it. Reinforce that
even an "obvious" fix benefits from the explicit hypothesis step — it's what makes the eventual
Validate step meaningful (you're confirming a SPECIFIC claim, not just "trying something").
**Optional extension:** ask what evidence you'd gather differently if the logs had been
completely empty instead of showing a clear nginx error (a good bridge to cases where the
container dies before it can log anything at all — `kubectl describe pod`'s Events section
becomes the primary evidence source in that case, same as the gold module's probe-mismatch
lesson).
@@ -0,0 +1,50 @@
# Knowledge Check: The Troubleshooting Framework
---
**1. You spot what looks like an obvious typo causing a failure and fix it immediately without
writing down a hypothesis first. What's the actual cost of skipping that step, even if the fix
works?**
*Answer:* You don't get a confirmed, testable claim about the cause — if the fix happens to
"work" for an unrelated reason (a coincidental restart, a different underlying issue also
resolving), you'd have no way to distinguish that from your fix actually being correct. The
hypothesis step is what makes Validate meaningful.
---
**2. During the "Gather Evidence" step for a CrashLoopBackOff, which two commands give you the
most direct evidence, and what does each one tell you that the other doesn't?**
*Answer:* `kubectl logs` (what the container itself printed, if anything, before exiting) and
`kubectl describe pod`/`describe deployment` (the container's actual configuration, plus recent
Events). Logs show application-level output; describe/Events show what Kubernetes itself
observed and configured — a crash with no logs at all often means the failure happened before
the application could log anything, which describe/Events can still reveal.
---
**3. True or false: "Prevent Recurrence" only applies to major incidents, not small
one-off mistakes like a typo.**
*Answer:* False. A small mistake that recurs repeatedly across a team becomes a real, ongoing
cost even if no single instance is severe — the framework applies the same reasoning regardless
of incident size: could a small, structural change catch this earlier next time?
---
**4. A broken Service selector (endpoint-fix-task's scenario) and a CrashLoopBackOff
(crashloop-fix's scenario) are very different failures. What's the SAME about how you'd
approach both?**
*Answer:* The same seven-step framework — Observe the specific symptom, Gather Evidence before
guessing, form a specific testable Hypothesis, Test it, make the minimal Repair the evidence
supports, Validate with the same kind of evidence you started with, and consider how to Prevent
Recurrence. The framework doesn't change; only the specific commands and evidence do.
## Instructor Notes
**Facilitation:** Question 4 is the whole point of this module — make sure it's discussed even
if answered correctly, since it's the transferability claim the entire framework rests on.
**Approximate timing:** 5-7 minutes.
@@ -0,0 +1,88 @@
# The RootNode Incident-Response Framework
## This module feels different on purpose
Everything before ROOT 12 asked you to complete an exercise. This module asks something
different: **you are responsible for this environment.** The incidents in this module are
modeled on real operational failures — not textbook exercises designed to teach one clean
concept, but the kind of messy, "why is this actually broken" situations a real on-call engineer
gets paged for.
## Detect → Triage → Diagnose → Mitigate → Recover → Verify → Learn
This is a lightweight incident-response framework — not enterprise incident management
tooling, just a way of thinking that scales down to "one engineer, one broken thing" as well as
it scales up to a real incident-response team.
**Detect** — something alerted you (a monitoring page, a user report, or in this Lab's case,
the scenario telling you something is wrong). You know an incident exists before you know what
it is.
**Triage** — how bad is this, right now, before you dive into root cause? Is anything actively
getting worse? Is this affecting one thing or cascading into others? Triage decides how urgently
you act, before you fully understand why.
**Diagnose** — this is where ROOT 10's troubleshooting framework (Observe, Gather Evidence, Form
Hypothesis, Test) does its work — the specific mechanics of finding the actual cause.
**Mitigate** — the fastest safe action that stops things from getting worse, which is not always
the same as the final fix. Sometimes mitigation and repair are the same step; sometimes
mitigation buys time (e.g. temporarily reducing load) while a proper fix is prepared.
**Recover** — restore the system to its actual working state — not just "stopped getting worse"
but genuinely operational again.
**Verify** — confirm recovery with real evidence, the same discipline as ROOT 10's Validate
step. "I think it's fixed" is not the same as checking.
**Learn** — what would prevent this exact class of incident from happening again? This is where
`rootnode-enforce-limits` picks up directly after `rootnode-runaway-monitor` — not a separate
topic, but the deliberate "Learn" step of the SAME incident, made into its own scenario.
## What this module will NOT tell you
The specific fixes for each incident are not in this lesson, and instructor notes on the
individual incident activities go deeper than what's shown here — this module gives you the
FRAMEWORK for approaching an unfamiliar incident, not a cheat sheet for these specific four.
That's deliberate: a framework you had to apply yourself is one you'll actually remember under
real pressure.
## Instructor Notes
**Lesson goal:** Set the tone shift for this entire module — from "complete an exercise" to
"you own this." This lesson is short by design; the real teaching happens through the incidents
themselves.
**Approximate timing:** 15 minutes read; 10 minutes live framing discussion.
**Preparation:** Read each incident's own instructor notes (in the Lab activities below) before
teaching this module live — several contain deeper solution guidance not repeated here,
specifically so students still have to work for it.
**Demonstration plan:** Not applicable to this framing lesson — the four incidents themselves
serve as the demonstrations.
**Likely misconceptions to watch for:**
- Students sometimes treat "Mitigate" and "Recover" as the same step. They can be, but aren't
always — worth naming a real-world example (rolling back a bad deploy mitigates immediately;
fully recovering might still require redeploying the CORRECT version afterward).
- "Learn" is the step most likely to get skipped once a Lab is marked complete. Explicitly
connect it to why `rootnode-enforce-limits` exists as its own scenario.
**Questions to ask students:** "Which step of this framework do you think real teams are worst
at, under real pressure, and why?" (There's no single right answer — the goal is getting
students to reason about incident response as a discipline, not just a checklist.)
**When to let a student struggle vs. provide a hint:** These incidents are intentionally less
guided than earlier modules. Let a student sit with "I don't know where to start" for a few
minutes before nudging — the discomfort of a genuinely unfamiliar failure is part of what this
module is teaching. Redirect toward the Diagnose step's ROOT 10 framework if truly stuck, rather
than pointing at the specific fix.
**Optional extension:** ask students to write a two-sentence incident summary for
`rootnode-runaway-monitor` as if posting it to a real team channel — Detect/Diagnose/Recover in
plain language, no jargon.
**Expected takeaway:** A framework applied under pressure beats improvisation, even for
engineers who are technically skilled enough to eventually stumble into the right answer anyway
— the framework is what makes the RIGHT answer arrive faster and more reliably.
@@ -0,0 +1,47 @@
# Post-Incident Reflection: What Real Ops Actually Feels Like
You just worked through four incidents that "own it, don't just complete it" framing described.
Take a few minutes to reflect on the module as a whole, not just any single incident.
## Reflection questions
1. Which of the four incidents took the longest to even understand what was actually wrong,
before you got to fixing anything? What made diagnosis slower there than the others?
2. `rootnode-runaway-monitor` and `rootnode-enforce-limits` are the same underlying incident,
split into "fix it now" and "prevent it forever." Which one did you find more satisfying to
solve, and why do you think real teams sometimes skip the second one under time pressure?
3. If you were handing these four incidents off to a teammate mid-shift, what's the one-sentence
summary you'd give for each, so they could pick up without re-diagnosing from scratch?
4. Compare how this module felt to the earlier, more guided modules in ROOT_. What specifically
was different about the experience, not just the difficulty?
## Real Ops takeaway
**"It's fixed" and "it won't happen again" are two different jobs, and skipping the second one
is how the same incident recurs.** `rootnode-enforce-limits` exists as its own scenario
specifically to make this point structurally, not just rhetorically — the immediate fix and the
prevention work are genuinely separate efforts, and a real team's incident isn't actually closed
until both are done.
**Being handed an unfamiliar, under-specified problem is the actual job.** Every other module in
ROOT_ told you roughly what concept you were about to practice. This one didn't — and that gap
is deliberate, because real production incidents don't come with a syllabus telling you which
concept they're testing. The framework from this module's opening lesson is what you reach for
instead of a hint system.
This module is complete. If a Capstone is part of your program, its readiness module is next.
## Instructor Notes
**Discussion questions for a live classroom:** question 2 is the module's core point — spend
real time on it rather than treating it as a quick check-the-box question.
**Approximate timing:** 10-12 minutes live discussion; 8 minutes self-paced writing.
**Optional extension:** ask students to identify which incident from this module most closely
resembles something they'd expect to encounter in an actual job, and why — grounds the module in
something beyond the classroom.
**Expected takeaway:** Real operational work is less about knowing every possible failure mode
in advance and more about having a repeatable process for approaching the ones you've never
seen before.
@@ -0,0 +1,72 @@
# What the Capstone Measures & How the Draw Works
## What the RootNode Capstone is actually testing
The Capstone is not a test of memorized `kubectl` syntax. It's a 90-minute operational
assessment weighted heavily toward RootNode's own Real Ops incident scenarios — it's checking
whether you can DO the thing ROOT_ has been building toward: diagnose and repair real,
under-specified problems using the frameworks and skills from every course before it, under a
clock, without step-by-step guidance.
If you've completed ROOT 05 through ROOT 12 honestly (not just clicked through), the Capstone is
testing exactly what you've already practiced — just without a lesson telling you which concept
is about to be tested.
## How the scenario draw works
The Capstone draws a mix of:
- **Required scenarios** — every attempt includes RootNode's own Real Ops incidents (the same
scenarios from ROOT 12, though a fresh attempt against them, not literally the same completed
attempt carried over).
- **Randomly drawn scenarios** — a smaller number of additional scenarios, randomly selected
from broader pools spanning workloads, configuration, and troubleshooting.
This means two students taking the Capstone will very likely see a different exact mix of
random scenarios, while both always face the same core Real Ops incidents. The exact scenario
IDs and the random draw itself are never published in advance — see the next lesson for why
that's intentional, not withheld information.
## What "unlocked" actually means
The Capstone doesn't unlock just because you decided you're ready — it unlocks when the
platform confirms, server-side, that you've genuinely completed every prerequisite stage
(Foundation, Workloads, Networking, Configuration, Troubleshooting, and Real Ops). This isn't a
UI suggestion you can bypass; it's enforced the same way everywhere you'd try to start it. If
you see a "locked" message, the platform is telling you something true about your actual
progress, not gatekeeping arbitrarily.
## What completion means
Passing the Capstone requires resolving every scenario in your specific draw — this is recorded
as a real, permanent achievement (`capstone_completed`) tied to your account, the same
achievement mechanism that recorded every stage completion before it. It's the platform's own
confirmation that you can operate a Kubernetes environment under exam conditions, not just that
you clicked through a curriculum.
## Instructor Notes
**Lesson goal:** Set accurate expectations before a student attempts the real assessment —
reduce anxiety from not knowing "what kind of thing" the Capstone tests, without revealing any
specific content.
**Approximate timing:** 10 minutes read; 8-10 minutes live.
**Preparation:** None beyond having completed ROOT 12 yourself if teaching this live, so you can
speak concretely about the Real Ops incidents' style without naming specifics from the current
draw pool.
**Likely misconceptions to watch for:**
- Students sometimes think "random draw" means the Capstone is inconsistent/unfair between
attempts. Clarify: the REQUIRED Real Ops scenarios are constant across every attempt; only a
smaller supplementary set is randomized.
- "It's locked, so something's broken" — reinforce that a locked Capstone is the platform
correctly reporting incomplete prerequisites, not a bug.
**Questions to ask students:** "Which ROOT_ course do you feel least confident about right now?
What would you do about that before attempting the Capstone?" — a good self-assessment prompt
that ties directly into the next lesson's time-management content.
**Expected takeaway:** The Capstone measures real operational capability built across the whole
ROOT_ sequence — approaching it as "one more scenario to guess your way through" misses the
point of everything that led up to it.
@@ -0,0 +1,66 @@
# Time Management & Troubleshooting Strategy Under a Clock
## 90 minutes, several scenarios — budget before you start
Once the Capstone begins, the clock is running against the whole attempt, not per scenario.
Spending 60 of your 90 minutes perfectly solving one incident, then rushing (or failing to
attempt) the remaining ones, is a worse outcome than solving most scenarios well within a
reasonable time each. Before diving into the first incident, take 60 seconds to look at how many
scenarios you're facing and roughly divide your available time — treat that budget as a real
constraint, not a suggestion.
## Apply the frameworks you already have — don't invent a new approach under pressure
You've already practiced two frameworks across ROOT_:
- **Observe → Gather Evidence → Form Hypothesis → Test → Repair → Validate → Prevent Recurrence**
(ROOT 10) for the mechanics of diagnosing a specific technical failure.
- **Detect → Triage → Diagnose → Mitigate → Recover → Verify → Learn** (ROOT 12) for the
broader "you own this incident" framing.
Under time pressure, the temptation is to abandon structure and start guessing. Resist it — the
frameworks exist precisely because they're FASTER than guessing once you've internalized them,
not slower. Reach for the same habits: read `kubectl describe`/Events before assuming, state
what you think is wrong before changing anything, verify after you fix.
## When to move on
If you're genuinely stuck on one scenario well past its budgeted time with no new evidence
emerging, it is a legitimate strategic choice to move to a different scenario and return later
if time allows — partial credit on more scenarios can beat a perfect score on fewer. This isn't
giving up; it's the same triage instinct from the incident-response framework, applied to your
own time as a resource.
## What's genuinely allowed
Everything you've used throughout ROOT_ Labs remains available: `kubectl` and its full command
set, the Lab's own in-context hints (if the specific scenario offers them), and your own notes
from earlier modules. There is no expectation of memorizing anything you'd normally look up —
the Capstone tests operational judgment and diagnostic process, not recall of obscure flags.
## Instructor Notes
**Lesson goal:** Reduce a common source of avoidable Capstone underperformance — poor time
allocation — separately from technical skill gaps.
**Approximate timing:** 10 minutes read; 8 minutes live.
**Demonstration plan:** If teaching this live, consider a quick show-of-hands: "who has ever
spent way too long on one problem and run out of time for an easier one elsewhere?" — normalizes
the behavior this lesson is trying to prevent.
**Likely misconceptions to watch for:**
- Students sometimes think asking for more time or pausing mid-scenario is against the rules.
Clarify based on your actual classroom/platform policy rather than assuming — this varies by
delivery mode and isn't something this lesson should guess at.
**Questions to ask students:** "If you had to guess right now, which TYPE of scenario (not a
specific one) do you think would eat the most of your time, and why?" — surfaces self-awareness
about weak areas before the real attempt.
**When to let a student struggle vs. provide a hint:** This lesson itself needs no struggle —
it's orientation, not a challenge. Save "let them struggle" judgment for the actual Capstone
attempt.
**Expected takeaway:** Time management under the Capstone's clock is a skill you can prepare for
explicitly, separate from and in addition to the technical skills the rest of ROOT_ built.
@@ -0,0 +1,58 @@
# Readiness Check: Are You Actually Ready?
This isn't a graded quiz — it's a genuine self-assessment before you attempt something you can't
easily "retry with different answers memorized." Answer each honestly.
---
**1. Can you explain, without looking it up, the difference between a liveness probe and a
readiness probe, and diagnose which one is failing from `kubectl get pods` output alone?**
*If no:* revisit ROOT 10's gold-standard Health Probes module before attempting the Capstone —
this exact distinction shows up in Real Ops-style incidents.
---
**2. Given a Service with zero Endpoints, do you know the first two commands you'd run to find
out why, without being told which module this relates to?**
*If no:* revisit ROOT 07's Services & Service Discovery module.
---
**3. Can you apply the Observe → Evidence → Hypothesis → Test → Repair → Validate → Prevent
framework to an unfamiliar failure you've never specifically seen before, not just to the exact
examples from the lesson?**
*If no:* this is worth practicing deliberately — pick any Practice-tab scenario you haven't done
yet and narrate the framework out loud to yourself while solving it.
---
**4. Have you completed the Real Ops incidents in ROOT 12 for real — diagnosed and repaired
them yourself, not looked up the answer?**
*If no:* do this before attempting the Capstone. The required scenarios in every Capstone
attempt are drawn from exactly this style of incident.
---
**5. Do you have a rough time-budget plan for a 90-minute, multi-scenario attempt?**
*If no:* re-read the time-management lesson in this module before you begin.
## What to do if you answered "no" to more than one
That's genuinely useful information, not a failure — it tells you specifically where to spend
your remaining prep time. Go back to the relevant module, do the work for real, and come back
to this check again before attempting the Capstone.
## Instructor Notes
**Facilitation:** In a live classroom, this works well as private/individual reflection rather
than a group discussion — the value is honest self-assessment, not a public performance.
**Approximate timing:** 5-8 minutes.
**Expected takeaway:** Readiness is something a student can genuinely self-assess against
concrete, specific criteria — not a vague feeling of confidence.
@@ -0,0 +1,42 @@
# Readiness Reflection: What Completion Means
Before you move toward the actual Capstone attempt, take a moment to reflect on the whole ROOT_
journey up to this point.
## Reflection questions
1. Think back to ROOT 05's opening lesson on desired state. How differently would you explain
that concept now, after everything since, compared to how you understood it the first time?
2. Which single module across ROOT_ changed how you approach a problem the most — not which was
most interesting, but which actually changed your behavior when something breaks?
3. What does passing the Capstone mean to you, beyond a completion record on the platform?
## What completion actually represents
A `capstone_completed` achievement isn't a certificate claiming you've memorized Kubernetes
trivia. It's the platform's record that you demonstrated, under real time pressure, without
step-by-step guidance, that you can diagnose and repair real operational problems using
frameworks you internalized rather than looked up in the moment. That's a materially different
and more durable skill than passing a multiple-choice exam about Kubernetes objects.
## When you're ready
There's no "perfect" moment where every module feels fully mastered — that's normal. If the
readiness check in the previous activity mostly came back "yes," and you've done the Real Ops
incidents for real, you're ready to attempt it. The Capstone will unlock automatically once the
platform confirms your prerequisite stages are genuinely complete — when you see it unlocked,
that's the platform's own confirmation, not just this module's.
This module is complete. Good luck.
## Instructor Notes
**Discussion questions for a live classroom:** question 2 tends to produce genuinely varied,
interesting answers across a cohort — worth having students share out loud if time allows.
**Approximate timing:** 8-10 minutes live discussion; 5 minutes self-paced writing.
**Preparation:** None — this is a closing/orientation activity, not a technical one.
**Expected takeaway:** Completing ROOT_'s Kubernetes sequence is a real, demonstrable skill
change, not just curriculum progress — the Capstone is where that becomes visible and provable.
+11
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@@ -64,6 +64,17 @@ connects what was just taught to the incident the student is about to solve, wit
the scenario's own hints/solution — the Lab's own progressive hints stay the only place the
actual answer path lives.
### Classifying near-duplicate or advanced scenarios (Phase 6B)
When two scenarios teach essentially the same concept (e.g. `pod-security-context` and
`cks-pod-security-context`), don't wire both as required core labs — pick the better-fitting one
as CORE and mark the other `is_required = false` as INDEPENDENT PRACTICE (see
`docs/ROOT_CURRICULUM_COVERAGE_MATRIX.md`'s "duplicate concepts identified" for worked examples).
Likewise, a genuinely harder or more niche scenario (CKS-exam-style, a less commonly needed
skill) belongs as `is_required = false` GUIDED/ADVANCED practice, not force-fit into the
required core path just because it exists — see `docs/COURSE_CONTENT_MODEL.md`'s optional-vs-
required section for how this affects module completion.
## 9. Knowledge check
A handful of self-check questions with answers shown inline (not a graded exam — that's what the
+44
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@@ -84,6 +84,16 @@ decided, and it never invents new state for anything that's independently verifi
Course and module completion are pure aggregates over their activities' completion (`total`/
`completed`/`pct`/`complete` — see `totals()`), never separately stored.
### Optional vs. required activities (Phase 6B)
`module_activities.is_required` (defaults `true`) lets a module distinguish CORE teaching from
GUIDED/INDEPENDENT-practice duplicates and ADVANCED/optional extras — see
`docs/ROOT_CURRICULUM_COVERAGE_MATRIX.md`'s classification scheme, used throughout ROOT 09. A
module's `complete` flag is true once every REQUIRED activity is done; an incomplete optional
activity never blocks it, though `total`/`pct` still count every activity, required or not.
Every Phase 6A activity has `is_required = true` (the column's default) — this is purely
additive, nothing that was complete before Phase 6B becomes incomplete now.
## 5. Prerequisite/locking rule
A course or module lists `prerequisites` (an array of other course/module ids). It's locked if
@@ -109,6 +119,40 @@ stop, regardless of its `status`. Use `draft` for genuinely unfinished authoring
want a student to see at all yet; use `status = planned` for an honest "not built yet" that's
fine to be visible.
## 6b. Content versioning (Phase 6B §21)
Follows the exact same convention `assessment_definitions`/`programs` already established — a
plain incrementing `version` integer, bumped by hand, informational rather than enforced:
- **A typo-only edit** (fixing a spelling mistake, a broken link, rewording a sentence without
changing its meaning) does NOT require a version bump — nothing about what a student is being
taught or held to changed.
- **A semantic edit** (changing a learning objective, swapping a lab's `scenario_id`, changing
`completion_behavior`, adding/removing/reordering activities in a way that changes what
"complete" means) SHOULD bump `version` on the affected row(s) — see
`023_phase6b_curriculum.sql`'s own `version = version + 1` on every row it semantically
changes (resequencing, prerequisite changes, `is_required` changes).
- **What happens to existing completions**: nothing, automatically. Unlike an assessment
session (which snapshots the definition version it was drawn against, because a session is a
point-in-time timed attempt), a course/module/activity's completion is derived LIVE every time
it's read (`course-progress.js`) from the CURRENT row plus the student's progress/achievements/
activity_completions — there is no snapshot to invalidate. A `manual_marker` completion
(`activity_completions`) is keyed by `activity_id`, which is stable across a version bump
(the id doesn't change, only its content/metadata does) — so a student's prior "I did this"
record stays valid even after a semantic edit, exactly like editing a scenario's own
Markdown description doesn't retroactively un-complete it in `progress`.
- **Scenario references across versions**: a `lab` activity's `scenario_id` is just a string
reference into `scenarios/data/*.json` — if that scenario file itself changes, the activity
automatically reflects the new content next time it's loaded (same as every other consumer of
`curriculum.js`'s cache). If an activity's `scenario_id` itself is changed to point at a
DIFFERENT scenario, that's a semantic edit (bump the version) and — depending on intent — may
warrant a new `activity_id` instead of mutating the existing one, so a student's prior
completion of the OLD scenario isn't silently reinterpreted as completion of the new one.
- **What this deliberately does NOT build**: no content-revision history table, no diffing, no
"students who saw v1 vs v2" cohort tracking. If a future phase needs that level of rigor
(e.g. for compliance/audit reasons), it's a real, separate feature — not something to bolt
onto a plain integer column.
## 7. Why this doesn't touch Phase 1-5 systems
No column was added to `scenarios/*.json`, `assessment_definitions`, `achievements`,
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the gold module's real lesson content, launches a real Lab, the Lab's own `setup_commands`
stand up the broken deployment, a real `kubectl patch` fixes it, and the module completes and
unlocks the next one) — both against a live stack.
## 18. ROOT_ Curriculum Authoring & Coverage Expansion (Phase 6B)
Full design: `docs/PHASE6B_ROOT_CURRICULUM_EXPANSION.md`, plus
`docs/ROOT_CURRICULUM_COVERAGE_MATRIX.md` and `docs/ROOT_CAPSTONE_READINESS.md`.
- **What it is:** 13 new teaching modules across ROOT 05-10/12/Capstone
(`023_phase6b_curriculum.sql`), built entirely from the 98-scenario inventory Phase 6A already
catalogued — no new scenarios needed. ROOT 08/09 moved from PLANNED to PARTIAL; scenario
coverage in structured curriculum went from 44/98 to 88/98 (89.8%), verified by direct query,
not estimated. 3 modules (plus the pre-existing gold standard) reach the full READY bar; every
other new module is honestly PARTIAL, missing a demonstration or guided exercise, documented
per-module rather than glossed over.
- **`is_required`** (new `module_activities` column, defaults `true`): distinguishes CORE
teaching from GUIDED/INDEPENDENT-practice duplicates and ADVANCED/optional extras — a module
is complete once every REQUIRED activity is done; an incomplete optional one never blocks it.
Every Phase 6A activity is unaffected (defaults to required).
- **The capstone server-side unlock fix:** `POST /api/assessments/:id/start` never checked
`unlock_rule` before this phase — a direct API call could start the capstone before its
prerequisite stages were complete, even though the UI never exposed that path. Fixed by
binding to the same `computeCurriculumState()` gate `GET /api/capstone` already used. See
`docs/ROOT_CAPSTONE_READINESS.md` §4 for the full story, including a pre-existing gap this
fix exposed in `e2e-phase5b.js`'s own capstone test (fixed alongside).
- **Tested, not just designed:** `platform/test/e2e-phase6b.js` (24 checks: new-module
hierarchy, prerequisite chains through the newly-inserted front-door modules, the
optional-vs-required completion rule, the capstone bypass fix in both directions, persistence/
isolation/RBAC/draft-hiding proven against the new content) and
`infra/scripts/drills/test-phase6b-root-course-rehearsal.js` (11 checks, real k3s: a student
walks a brand-new module — ROOT 07 Services & Service Discovery — end to end including a real
`kubectl expose` against a live cluster, plus an instructor narrative proving Curriculum view,
Prepare Labs, and classroom tooling all still work against the expanded curriculum).
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# Phase 6B — ROOT_ Curriculum Authoring & Coverage Expansion
**Status: PHASE 6B COMPLETE. 13 NEW TEACHING MODULES AUTHORED ACROSS ROOT 05-10/12/CAPSTONE.
CAPSTONE SERVER-SIDE UNLOCK ENFORCEMENT FIXED. VALIDATED AGAINST A REAL LAB.**
Phase 6A built the course/module/activity content model and one gold-standard module. Phase 6B
is the primary content-authoring phase: real, substantial teaching content across the
Kubernetes/operations portion of `root_`, built strictly from the existing 98-scenario
inventory — no new scenarios were needed or created (see §7).
## 1. What was authored
13 new modules across 7 courses, all evidence-mapped in `docs/ROOT_CURRICULUM_COVERAGE_MATRIX.md`:
| Course | New module(s) | Depth |
|---|---|---|
| ROOT 05 | Kubernetes Mental Model & Core Objects | **READY** — full gold-standard pattern |
| ROOT 06 | Deployments, Scaling & Updates | **READY** — full gold-standard pattern |
| ROOT 06 | Jobs, CronJobs & DaemonSets | PARTIAL — lesson + knowledge check + labs |
| ROOT 07 | Services & Service Discovery | **READY** — full gold-standard pattern |
| ROOT 07 | Ingress & NetworkPolicy Foundations | PARTIAL — lesson + knowledge check + labs |
| ROOT 08 | Storage Fundamentals | PARTIAL — lesson + knowledge check + labs |
| ROOT 08 | Scheduling & Resource Governance | PARTIAL — lesson + knowledge check + labs |
| ROOT 09 | Security Model & SecurityContext | **READY** — full gold-standard pattern + guided/independent/advanced practice |
| ROOT 09 | ServiceAccounts & RBAC | PARTIAL — lesson + knowledge check + labs |
| ROOT 09 | Network & Supply Chain Security | PARTIAL — lesson + knowledge check + labs |
| ROOT 09 | Cluster Hardening & Runtime Security | PARTIAL — survey-depth lesson + labs |
| ROOT 10 | The RootNode Troubleshooting Framework | PARTIAL — lesson + demonstration + knowledge check + labs |
| ROOT 12 | Incident-response framing added to the existing Real Ops module | PARTIAL — framework lesson + reflection wrapping the existing incidents |
| ROOT Capstone | Capstone Readiness | **READY** — orientation module, see `docs/ROOT_CAPSTONE_READINESS.md` |
3 modules reach **READY** by the honest bar in `docs/COURSE_AUTHORING_STANDARD.md` (introduction,
objectives, concept lesson, demonstration, knowledge check, guided practice, lab, reflection,
instructor notes, estimated duration, all present) — plus the pre-existing gold-standard Health
Probes module, unchanged. Every other new module is honestly **PARTIAL**: real lesson content
and real labs, missing one or more of demonstration/guided-exercise (documented per-module in the
coverage matrix, not glossed over).
ROOT 08 and ROOT 09 moved from **PLANNED** to **PARTIAL** at the course level — real content now
exists where Phase 6A left them structurally empty.
## 2. The is_required extension (Phase 6B, not Phase 6A)
`module_activities.is_required` (new column, defaults `true` — every Phase 6A activity is
unaffected) lets a module distinguish CORE activities from GUIDED/INDEPENDENT-practice
duplicates and ADVANCED/optional extras (ROOT 09's CKS-style content, mostly). A module is
"complete" once every REQUIRED activity is done — an incomplete optional activity never blocks
it, though it still counts toward the displayed percent. See `docs/COURSE_CONTENT_MODEL.md`'s
updated completion-rules section.
## 3. The capstone server-side unlock fix
Full detail in `docs/ROOT_CAPSTONE_READINESS.md` §4. Summary: `POST /api/assessments/
:definitionId/start` previously never checked `unlock_rule` — a direct API call could start the
capstone before its prerequisite stages were genuinely complete, even though the UI never
exposed a way to trigger this. Fixed by binding to the same `computeCurriculumState()` gate
`GET /api/capstone` already used. Found while fixing this: `e2e-phase5b.js`'s own capstone test
had been passing only because of this exact gap (it never completed the `real-ops` stage before
attempting to start) — fixed alongside the platform code, not routed around.
## 4. Content quality bar applied honestly
No module was marked READY merely for having activity rows, headings, or scenario references.
The ROOT 08/09 storage/scheduling/security modules are real, substantive lessons with real
knowledge checks — but without a demonstration or guided exercise, they're PARTIAL, not READY,
by this project's own stated standard. See the coverage matrix for the specific gap in each.
## 5. Scenario coverage before/after
Verified by direct query against `module_activities.scenario_id`, not estimated.
Before Phase 6B: 44 of 98 scenarios wired into structured curriculum (all via Phase 6A's
mechanical mapping of `rootnode-path.json`'s existing stages).
After Phase 6B: **88 of 98 scenarios (89.8%) now in structured curriculum** — 44 newly wired
this phase: `deployment-rollback` (added to ROOT 06 m02 as hands-on rollback practice
alongside its lesson), `job-task`, `cronjob-task` (ROOT 06 m03); `nodeport-task`,
`dns-resolution-mcq` (ROOT 07 m01), `ingress-task`, `network-policy` (ROOT 07 m04);
`emptydir-pod`, `pv-pvc-mount`, `pvc-dynamic-task`, `storageclass-mcq` (ROOT 08 m01),
`node-label-selector`, `node-taint-toleration`, `pod-affinity-mcq`, `priority-class-task`,
`pod-disruption-budget-task`, `resource-quota-ns`, `limitrange-task` (ROOT 08 m02);
`cks-non-root-enforce`, `cks-drop-capabilities`, `cks-readonly-filesystem`,
`cks-pod-security-context`, `cks-seccomp-profile`, `cks-apparmor-profile`,
`pod-security-context` (ROOT 09 m01); `serviceaccount-pod`, `cks-automount-token`, `rbac-role`,
`cks-rbac-clusterrole`, `cks-rbac-least-privilege`, `rbac-clusterrole` (ROOT 09 m02);
`cks-network-policy`, `cks-egress-namespace`, `cks-tls-ingress`, `cks-image-pull-secret`,
`networkpolicy-egress`, `cks-network-policy-metadata` (ROOT 09 m03); `cks-psa-namespace`,
`cks-immutable-secret`, `cks-runtime-class`, `cks-audit-policy` (ROOT 09 m04); `crashloop-fix`,
`endpoint-fix-task` (ROOT 10 m03), `container-logging-mcq` (ROOT 10 m02, existing bank).
**10 scenarios remain unwired**, each with a specific, documented reason rather than an
oversight: `cluster-upgrade-mcq`, `etcd-backup-mcq` (ROOT 11/DevOps territory, explicitly out of
Phase 6B's authoring scope); 7 CKS-style MCQs classified as ASSESSMENT BANK material
(`cks-mcq-api-server`, `cks-mcq-audit-policy`, `cks-mcq-kubelet-auth`, `cks-mcq-psp-replacement`,
`cks-mcq-runtime-security`, `cks-mcq-sandboxing`, `cks-mcq-image-footprint`) — recall-style
questions better suited to a future structured exam pool than hands-on core teaching, flagged
for that future use rather than silently dropped; and `readiness-probe-task` — a real, unused
candidate for independent practice in ROOT 06 or ROOT 10 that this phase simply didn't get to,
honestly left for Phase 6C rather than force-mapped at the last minute. Quality of mapping, not
percentage, drove every placement decision — see the coverage matrix's "duplicate concepts
identified" section for how near-duplicate scenarios were handled deliberately rather than both
force-fit into "core."
## 6. Knowledge-check and guided-exercise approach
Every new knowledge check uses scenario-interpretation and reasoning questions ("A Deployment
has three replicas but the Service has zero endpoints — which part of the system should you
inspect first, and why?"), never "what command was shown two paragraphs ago." Every guided
exercise bridges lesson to lab without revealing the lab's answer — modeled directly on the
existing gold module's own guided exercise. No new knowledge-check engine capability was needed;
the existing Markdown + manual-marker model was sufficient throughout.
## 7. Why no new scenarios were created
Every learning objective this phase authored had a suitable existing scenario — the 54-scenario
unused bank Phase 6A inventoried was exactly the content Phase 6B needed. No objective was found
that genuinely required new hands-on lab content with no existing scenario able to serve it, so
no new `rootnode-*` scenario was created this phase (see the authorization's explicit
justification bar in its §17 — none of the three required conditions were met for any specific
gap identified during authoring).
## 8. What Phase 6B deliberately did not build
Per the authorization's explicit scope line: `init_`/`compile_` curriculum, deep authoring of
ROOT 01-04 or ROOT 11 (both remain structurally PLANNED, as Phase 6A left them — genuinely no
scenario content exists for either), a Parent Portal, payments, public registration, an AI
tutor, chat/video/voice, proctoring, a mobile app, certificates, a multi-host scheduler,
production deployment changes, an LMS/CMS, a WYSIWYG authoring system, or complex drip
scheduling. The Provisioner, Gateway, Lab Router, student/instructor authentication, enrollment
architecture, and notification architecture were not redesigned — the one fix made
(capstone unlock) was the smallest correct change to the assessment engine's existing route,
not a redesign of the engine itself.
## 9. Test results
- `e2e-phase6b.js`: **24 passed, 0 failed.**
- `test-phase6b-root-course-rehearsal.js` (real k3s Lab, real `kubectl expose`, real classroom
tooling): **11 passed, 0 failed.**
- Full regression (2A/2B/3A/3B/5A/5B/5C/6A), each run in isolation per the convention Phase 6A
established — see the final report for the run-by-run result and the two pre-existing test
gaps found and fixed along the way (in `e2e-phase5b.js` and `e2e-phase6a.js`, both caused by
this phase's own intentional, documented behavior changes, not by a defect).
## 10. Known limitations / recommended Phase 6C scope
- ROOT 06/07/08/09/10's PARTIAL modules are missing a demonstration and/or guided exercise —
the natural next authoring pass, module by module, using the 3 READY modules as templates.
- ROOT 09's 7 ASSESSMENT-BANK-classified MCQs are inventoried but not yet wired into an actual
assessment definition.
- ROOT 11 (DevOps & Platform Engineering) remains entirely PLANNED — no scenario content exists
anywhere in this repository for CI/CD, IaC, or GitOps concepts; a future phase would need to
either author new `rootnode-*` scenarios for it or explicitly scope it out of `root_`.
- The Capstone Readiness module's completion is intentionally independent of the real capstone's
unlock gate (see `docs/ROOT_CAPSTONE_READINESS.md` §3) — worth revisiting only if a future
phase has a concrete reason to couple them, not as a default assumption.
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activity tree (lessons, demonstrations, knowledge checks, guided exercises, labs,
reflections, assessments/capstone) instead of just a bare scenario id list — the same tree an
instructor-led classroom student sees, consumed through the identical `buildCourseTree()`.
See `docs/COURSE_CONTENT_MODEL.md` and `docs/PHASE6A_ROOT_COURSE_FOUNDATION.md`.
See `docs/COURSE_CONTENT_MODEL.md` and `docs/PHASE6A_ROOT_COURSE_FOUNDATION.md`. **Populated
with real teaching content across most of the Kubernetes/operations courses in Phase 6B** —
see `docs/PHASE6B_ROOT_CURRICULUM_EXPANSION.md`. The architecture itself (this closed gap)
didn't change; what a self-paced student actually finds inside it did.
## What Phase 4.1 deliberately did NOT do here
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# ROOT Capstone Readiness
Phase 6B §9/§10 — the instructional runway that prepares a student for the existing
`rootnode-capstone` assessment, and the server-side fix that makes its unlock rule actually
enforced. This document does not redesign the capstone engine itself (`assessments.js`,
`013_assessments.sql`) — see `docs/PHASE3B_LEARNING_AND_ASSESSMENT.md` for that.
## 1. The Capstone Readiness module
`root-capstone-m02-capstone-readiness` (sequenced BEFORE the real capstone module,
`root-capstone-m01-operate-and-recover`, within the `root-capstone` course) — 4 activities:
1. **Lesson — What the Capstone Measures & How the Draw Works.** Explains the required-vs-random
scenario draw, what "unlocked" means, and what completion records. Never publishes the exact
scenario IDs in the current pool or any answer.
2. **Lesson — Time Management & Troubleshooting Strategy Under a Clock.** Budgeting the 90
minutes, reusing the ROOT 10/ROOT 12 frameworks under pressure, and when to move on from a
stuck scenario.
3. **Knowledge check — Readiness Check: Are You Actually Ready?** A genuine self-assessment
(not a graded quiz) against concrete criteria, pointing back to specific ROOT_ modules for
any "no" answer.
4. **Reflection — What Completion Means.** Connects passing the Capstone to a durable,
demonstrated skill rather than a completion checkbox.
This module derives its own completion the same way every other lesson-only module does
(`activity_completions`, `manual_marker`) — it is intentionally NOT a prerequisite the real
capstone assessment engine checks before allowing a start (see §3 below for why these two gates
are deliberately independent).
## 2. What was NOT built
No answers, no exact scenario IDs from the current pool, no capstone-specific hint content
beyond what the Lab's own progressive hints already provide. No new assessment engine, no
second capstone, no readiness "score." This is orientation content, not a shadow exam.
## 3. Why readiness-module completion and the real unlock gate are independent
The real capstone start (`POST /api/assessments/rootnode-capstone/start`) is gated by the
curriculum path's own `unlock_rule` — all 6 content stages of `rootnode-path.json` complete
(Foundation, Workloads, Networking, Configuration, Troubleshooting, Real Ops) — computed by
`computeCurriculumState()` (`curriculum-rules.js`), the exact same function `GET /api/capstone`
already used to display lock state. Whether a student has viewed or completed the Capstone
Readiness module has NO bearing on this gate.
This is deliberate, not an oversight: hard-locking the real assessment behind a CONTENT-MODEL
module (course_modules/module_activities) would mean the security-critical enforcement boundary
lives in two different systems that could drift out of sync — the curriculum-path unlock_rule
(Postgres-backed, achievement-derived, already proven) and the course-content prerequisite chain
(newer, additive, built for teaching sequencing rather than security enforcement). Keeping them
independent means: the readiness module is free to be completed early, late, or skipped by a
student who's already prepared some other way, while the real gate remains exactly as strict as
`docs/PHASE3B_LEARNING_AND_ASSESSMENT.md` originally specified.
## 4. The server-side unlock enforcement fix (Phase 6B §10)
**The gap** (documented in `docs/PHASE6A_ROOT_COURSE_FOUNDATION.md` §10): `POST /api/assessments/
:definitionId/start` (`learning-routes.js`) checked only that the assessment definition existed
and was `status = 'active'` — it never checked `unlock_rule` at all. `GET /api/capstone`
correctly computed and displayed lock state, and the student UI never exposed a "start" action
while locked, but a direct POST to the start route bypassed the check entirely. Student UI state
was the only thing standing between a student and an early capstone attempt.
**The fix**: the start route now resolves whether the requested definition is the curriculum
path's OWN configured capstone (`path.stages.find(s => s.type === 'capstone' && s
.capstone_assessment_id === definition.assessment_definition_id)`), and if so, computes the
exact same `computeCurriculumState()` gate `/api/capstone` already relies on. A `locked` gate
now returns a clean `403 { error: 'locked', message, blocking_stage_ids }` — the same
`blocking_stage_ids` shape `/api/capstone` already exposes, so a client integrating against this
route gets consistent, already-documented error shape rather than a new one. No internal state
beyond the stage ids that are actually incomplete is ever returned.
**What is NOT gated**: any assessment definition the curriculum path does NOT name as its
capstone (e.g. `rootnode-quick-assessment`) is completely unaffected — the check only ever
triggers for the one definition the path itself points at via `capstone_assessment_id`.
**What remains valid**: no existing `assessment_sessions` row, no achievement, no enrollment
completion record was touched by this fix — it only affects a NEW start attempt going forward.
A student who already legitimately completed the capstone before this fix keeps that record
exactly as it was.
**Regression coverage**: `platform/test/e2e-phase6b.js` proves both directions — a direct start
attempt before prerequisites are met is rejected (`403 locked`), and a legitimately unlocked
attempt (all 6 stages genuinely complete) still succeeds and completes normally. A pre-existing
gap was also found and fixed in `e2e-phase5b.js`'s own capstone-completion test, which had never
included the `real-ops` stage in its completion loop — it was passing only because the very
bug this phase fixes let an incomplete curriculum still start the capstone. See that test file's
own comment for detail.
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# ROOT_ Curriculum Coverage Matrix
Phase 6B §1 — maps every scenario Phase 6B puts to structured use, with an intentional reason
for each placement (not coverage-percentage padding). Built from
`docs/ROOT_CURRICULUM_INVENTORY.md`'s evidence. Statuses: **READY** (a student can actually
learn from it end to end — see `docs/COURSE_AUTHORING_STANDARD.md`'s bar), **PARTIAL** (real
lesson + labs, missing one or more of demonstration/knowledge-check/guided-exercise), **PLANNED**
(structure only, no content), **GAP** (no suitable scenario exists at all).
## Duplicate concepts identified (handled explicitly, not silently mapped twice)
- `pod-security-context` (generic) vs. `cks-pod-security-context` (CKS-flavored) — same concept.
`cks-pod-security-context` is the CORE guided lab (ROOT 09 m01); `pod-security-context` is
classified INDEPENDENT PRACTICE (a second, optional rep).
- `rbac-clusterrole` (generic) vs. `cks-rbac-clusterrole` (CKS-flavored) — same concept.
`cks-rbac-clusterrole` is CORE (ROOT 09 m02); `rbac-clusterrole` is INDEPENDENT PRACTICE.
- `network-policy` (generic, foundational) vs. `cks-network-policy` (CKS default-deny framing) vs.
`networkpolicy-egress` (generic egress) — three related but distinct angles, deliberately split
across two courses: `network-policy` teaches the ARCHITECTURAL concept in ROOT 07 (what a
NetworkPolicy is/does); `cks-network-policy`/`cks-egress-namespace`/`networkpolicy-egress`
teach it as a SECURITY CONTROL in ROOT 09 (default-deny posture, least-privilege network
access) — not a duplicate once the teaching angle is made explicit, so both are CORE in their
respective course, not one marked redundant.
## ROOT 05 — Kubernetes Foundations
| Module | Objective | Lesson | Demo | KC | Guided | Scenario(s) | Assessment | Real Ops | Status |
|---|---|---|---|---|---|---|---|---|---|
| m02 Kubernetes Mental Model & Core Objects (NEW) | Explain what Kubernetes solves, the control-plane/worker/desired-state model, and navigate Pods/Namespaces/labels with kubectl | Yes | Yes | Yes | Yes | pod-basics-mcq, namespaces-basics, labels-selectors-mcq, kubectl-essentials-mcq (existing, re-sequenced as this module's guided path) | — | "declarative config drifts back to desired state after manual edits" | **READY** |
| m01 Pods & kubectl Basics (existing) | Mechanical kubectl fluency across the Foundation stage's 20 scenarios | No | No | No | No | all 20 Foundation scenarios | — | — | PARTIAL (unchanged from Phase 6A — m02 above is the new front door; m01's labs remain a practice bank behind it) |
`m02` is sequenced BEFORE `m01` (prerequisite: none; `m01`'s prerequisite becomes `m02`) so a
student meets the mental model before the bare-lab bank, per this phase's core principle.
## ROOT 06 — Kubernetes Application Workloads
| Module | Objective | Lesson | Demo | KC | Guided | Scenario(s) | Real Ops | Status |
|---|---|---|---|---|---|---|---|---|
| m02 Deployments, Scaling & Updates (NEW) | Explain why Deployments/ReplicaSets exist, perform a rolling update, and reason about rollback | Yes | Yes | Yes | Yes | deploy-nginx, scale-deployment, rolling-update-task, deployment-rollback (newly wired — Workloads & Scheduling bucket, belongs here not ROOT 08) | "a bad rollout with no rollback plan turns a deploy into an outage" | **READY** |
| m03 Jobs, CronJobs & DaemonSets (NEW) | Distinguish one-shot Jobs, scheduled CronJobs, and per-node DaemonSets from long-running Deployments | Yes | No | Yes | No | job-task, cronjob-task (newly wired), jobs-cronjobs-mcq, daemonset-mcq | "a cleanup Job that never completes silently exhausts cluster resources" | PARTIAL (lesson+KC authored; no separate demo/guided — labs carry the practice) |
| m01 Deployments & Workloads (existing) | Bare-lab bank, Workloads stage's original 8 scenarios | No | No | No | No | (unchanged) | — | PARTIAL (unchanged) |
## ROOT 07 — Kubernetes Networking & Configuration
| Module | Objective | Lesson | Demo | KC | Guided | Scenario(s) | Real Ops | Status |
|---|---|---|---|---|---|---|---|---|
| m03 Services & Service Discovery (NEW) | Explain the Service/Endpoints/DNS request path and choose the right Service type | Yes | Yes | Yes | Yes | services-mcq, expose-service-basics, nodeport-task, dns-resolution-mcq (newly wired) | "a Service with zero endpoints looks identical to network failure from the outside" | **READY** |
| m04 Ingress & NetworkPolicy Foundations (NEW) | Explain how Ingress routes external traffic and what a NetworkPolicy architecturally does | Yes | No | Yes | No | ingress-task, network-policy (newly wired) | "traffic reachability should be intentional, not incidental" | PARTIAL |
| m02 Configuration & Secrets (existing) | Bare-lab bank | No | No | No | No | (unchanged) | — | PARTIAL (unchanged) |
| m01 Services & Networking (existing) | Bare-lab bank, folded conceptually under m03 above | No | No | No | No | (unchanged) | — | PARTIAL (unchanged) |
## ROOT 08 — Kubernetes Storage & Scheduling (newly wired this phase — was PLANNED)
| Module | Objective | Lesson | Demo | KC | Guided | Scenario(s) | Real Ops | Status |
|---|---|---|---|---|---|---|---|---|
| m01 Storage Fundamentals (NEW) | Explain ephemeral vs. persistent storage and how PV/PVC/StorageClass fit together | Yes | No | Yes | No | emptydir-pod, pv-pvc-mount, pvc-dynamic-task, storageclass-mcq | "a Pod restart on ephemeral storage silently loses data no one told the team about" | PARTIAL |
| m02 Scheduling & Resource Governance (NEW) | Explain how the scheduler places Pods and how quotas/limits/priority shape that placement | Yes | No | Yes | No | node-label-selector, node-taint-toleration, pod-affinity-mcq, priority-class-task, pod-disruption-budget-task, resource-quota-ns, limitrange-task | "an eviction during a voluntary disruption without a PDB can take down every replica at once" | PARTIAL |
`cluster-upgrade-mcq` and `etcd-backup-mcq` (Cluster Administration bucket) are left
**PRACTICE-ONLY** — they're genuine cluster-operator content but conceptually belong with ROOT 11
(DevOps & Platform Engineering, out of Phase 6B's authoring scope per the authorization), not
storage/scheduling. Mapping them here just to raise a coverage number would violate this
document's own "quality over percentage" rule.
## ROOT 09 — Kubernetes Security (newly wired this phase — was PLANNED)
Not built as 22 disconnected CKS tasks. Four modules, foundational → advanced:
| Module | Focus | Classification of its scenarios | Status |
|---|---|---|---|
| m01 Security Model & SecurityContext (NEW) | Defense in depth, least privilege, non-root/capabilities/read-only-fs | CORE: cks-pod-security-context, cks-non-root-enforce, cks-drop-capabilities, cks-readonly-filesystem. GUIDED: cks-seccomp-profile. ADVANCED: cks-apparmor-profile. INDEPENDENT: pod-security-context (dup, see above) | **READY** |
| m02 ServiceAccounts & RBAC (NEW) | Identity for workloads, least-privilege permissions | CORE: serviceaccount-pod, cks-automount-token, rbac-role, cks-rbac-clusterrole, cks-rbac-least-privilege. INDEPENDENT: rbac-clusterrole (dup, see above) | PARTIAL (lesson authored; no separate demo/guided) |
| m03 Network & Supply Chain Security (NEW) | NetworkPolicy as a security control, image/registry trust, TLS ingress | CORE: cks-network-policy, cks-egress-namespace, cks-tls-ingress, cks-image-pull-secret. GUIDED: networkpolicy-egress. ADVANCED: cks-network-policy-metadata. ASSESSMENT BANK: cks-mcq-image-footprint | PARTIAL |
| m04 Cluster Hardening & Runtime Security (NEW) | Pod Security Admission, audit policy, runtime sandboxing — survey-level, not daily-driver core | CORE: cks-psa-namespace, cks-immutable-secret. ADVANCED: cks-audit-policy, cks-runtime-class. ASSESSMENT BANK: cks-mcq-api-server, cks-mcq-audit-policy, cks-mcq-kubelet-auth, cks-mcq-psp-replacement, cks-mcq-runtime-security, cks-mcq-sandboxing | PARTIAL |
"ASSESSMENT BANK" scenarios are intentionally NOT wired as required module activities — they're
recall-style MCQs well suited to a future structured exam pool (`rootnode-quick-assessment`-style
definition), not hands-on core teaching. Not wired into `module_activities` this phase; flagged
here so a future phase doesn't have to re-discover them.
## ROOT 10 — Kubernetes Troubleshooting & Observability
The gold-standard Health Probes module (`root-10-m01`) is **preserved unmodified** — it's the
template, not a page to be made "consistent" with anything else.
| Module | Objective | Lesson | Demo | KC | Guided | Scenario(s) | Real Ops | Status |
|---|---|---|---|---|---|---|---|---|
| m01 Health Probes & Troubleshooting (existing, UNCHANGED) | — | Yes | Yes | Yes | Yes | rootnode-probe-port-mismatch | Yes | **READY** |
| m03 The RootNode Troubleshooting Framework (NEW) | Apply Observe→Evidence→Hypothesis→Test→Repair→Validate→Prevent to a CrashLoopBackOff and a broken Service | Yes | Yes | Yes | No | crashloop-fix, endpoint-fix-task, container-logging-mcq (newly wired) | "a repeatable framework beats guessing under a 2am page" | PARTIAL (no separate guided exercise — the framework lesson + demo carry that role) |
| m02 General Troubleshooting (existing) | Bare-lab bank | No | No | No | No | (unchanged) | — | PARTIAL (unchanged) |
## ROOT 12 — RootNode Real Ops
| Module | Objective | Lesson | Scenario(s) | Framing | Status |
|---|---|---|---|---|---|
| m01 Real Ops Incidents (existing, extended with framing) | Apply Detect→Triage→Diagnose→Mitigate→Recover→Verify→Learn to real incidents | Yes (new incident-response framework lesson) | rootnode-runaway-monitor, broken-deployment, rootnode-probe-port-mismatch (reused), rootnode-enforce-limits | Each lab gets a short incident-context intro + post-incident reflection (not full lesson/demo/KC per incident — see `docs/PHASE6B_ROOT_CURRICULUM_EXPANSION.md` for why) | PARTIAL |
`rootnode-real-ops` bundle contains exactly these 4 scenario ids (verified against
`scenarios/bundles/rootnode-real-ops.json`) — no additional upstream scenario was intentionally
included there beyond what `rootnode-path.json`'s `real-ops` stage already lists.
## ROOT CAPSTONE
| Module | Content | Status |
|---|---|---|
| m01 Operate and Recover (existing) | The real `rootnode-capstone` assessment | PARTIAL (unchanged — assessment engine, not lesson content) |
| m02 Capstone Readiness (NEW) | What the capstone measures, prerequisites, how the timed/random draw works, time management, troubleshooting strategy, what completion means — derives real readiness from curriculum state, never publishes the draw or answers | **READY** |
## Scenarios deliberately left out of structured curriculum entirely
`cluster-upgrade-mcq`, `etcd-backup-mcq` (ROOT 11 territory, out of scope), and the 6
ASSESSMENT-BANK-classified CKS MCQs above (not yet wired to an actual assessment definition —
future work, not silently dropped). All remain reachable via the existing Practice tab/bundles,
unaffected by any of this.
+12
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@@ -207,3 +207,15 @@ ROOT 07/08/09/10 can draw on in Phase 6B, not content that needs to be invented:
- No DevOps/CI/CD/IaC/GitOps scenario content exists (ROOT 11 is necessarily 100% PLANNED).
- No Linux-fundamentals, Git, or Docker-specific scenario content exists (ROOT 01-04 are
necessarily 100% PLANNED) — everything in `scenarios/data/` is Kubernetes/CKS content.
## 8. Phase 6B update — scenario coverage after curriculum authoring
Phase 6B wired 44 more of the scenarios above into structured curriculum (verified by direct
query against `module_activities.scenario_id`, not estimated): **88 of 98 scenarios (89.8%)**
are now in structured curriculum, up from 44 at the end of Phase 6A. The remaining 10 —
`cluster-upgrade-mcq`, `etcd-backup-mcq` (ROOT 11 territory), 7 CKS-style MCQs classified as
future ASSESSMENT BANK material, and `readiness-probe-task` (a genuine, documented gap for
Phase 6C) — are listed with their specific reasons in
`docs/PHASE6B_ROOT_CURRICULUM_EXPANSION.md` §5. The full course-by-course mapping, including
which scenarios were classified CORE/GUIDED/INDEPENDENT/ADVANCED/ASSESSMENT-BANK and why, lives
in `docs/ROOT_CURRICULUM_COVERAGE_MATRIX.md` — this file is intentionally not duplicated there.
+14 -9
View File
@@ -9,6 +9,11 @@ All 13 rows below are `courses` under the ONE existing program, `root-kubernetes
(`programs` table, unchanged — see §"why one program, not thirteen" below). Every status claim
here is grounded in `docs/ROOT_CURRICULUM_INVENTORY.md`, not aspirational.
**Updated for Phase 6B** (`platform/api/migrations/023_phase6b_curriculum.sql`,
`docs/PHASE6B_ROOT_CURRICULUM_EXPANSION.md`): ROOT 08 and 09 moved from PLANNED to PARTIAL, and
6 courses gained new teaching modules — the module-level detail and evidence for every new
placement lives in `docs/ROOT_CURRICULUM_COVERAGE_MATRIX.md`, not duplicated here.
## Course sequence
| # | Course | Status | Why |
@@ -17,15 +22,15 @@ here is grounded in `docs/ROOT_CURRICULUM_INVENTORY.md`, not aspirational.
| 2 | Linux Administration & Networking | **PLANNED** | Same — no Linux-admin scenario content exists. |
| 3 | Git & Collaborative Development | **PLANNED** | No Git scenario content exists. |
| 4 | Containers & Docker | **PLANNED** | No Docker-specific scenario content exists (the Lab itself runs k3s, but no student-facing "learn Docker" scenarios exist). |
| 5 | Kubernetes Foundations | **PARTIAL** | Real content: the existing "Foundation" stage's 20 scenarios, wrapped as one module (`root-05-m01-pods-and-kubectl-basics`). No teaching lesson content authored yet — bare labs only. |
| 6 | Kubernetes Application Workloads | **PARTIAL** | The existing "Workloads" stage's 8 scenarios, one module. Bare labs only. |
| 7 | Kubernetes Networking & Configuration | **PARTIAL** | The existing "Networking" (2) and "Configuration" (5) stages, two modules. Bare labs only. |
| 8 | Kubernetes Storage & Scheduling | **PLANNED** | Real scenario content exists (PV/PVC, StorageClass, taints/tolerations, PDB — see inventory §5) but is not yet wired into a module. Deliberately left PLANNED rather than fabricating a module shell with no honest content behind it — Phase 6B. |
| 9 | Kubernetes Security | **PLANNED** | A substantial 22-scenario CKS-style bank exists (RBAC, PSA, network policy, supply chain, runtime hardening) but is not yet wired into a module — Phase 6B. |
| 10 | Kubernetes Troubleshooting & Observability | **PARTIAL** | Contains the Phase 6A gold-standard module (READY) plus the existing "Troubleshooting" stage's remaining 5 scenarios as a second, bare-lab module. |
| 11 | DevOps & Platform Engineering Foundations | **PLANNED** | No CI/CD/IaC/GitOps scenario content exists anywhere in this repository. |
| 12 | RootNode Real Ops | **PARTIAL** | The existing "RootNode: Real Ops" stage's 4 scenarios (3 RootNode-authored + 1 generic), one module. Bare labs, no teaching content — the gold module already gives one of these four (`rootnode-probe-port-mismatch`) a full teaching treatment elsewhere; this module exercises it again alongside the other three, deliberately (see module notes below). |
| 13 | ROOT Capstone — Operate and Recover a Production-Like Environment | **PARTIAL** | The existing, fully working `rootnode-capstone` assessment (90 min, mixed required/random pool). No capstone orientation/briefing lesson authored yet. |
| 5 | Kubernetes Foundations | **PARTIAL** | Phase 6B added a READY front-door module (`root-05-m00-kubernetes-mental-model` — full lesson/demo/knowledge-check/guided-exercise/lab/reflection) sequenced before the existing 20-scenario bare-lab bank (`root-05-m01`), which now sits behind it. |
| 6 | Kubernetes Application Workloads | **PARTIAL** | Phase 6B added a READY `root-06-m02-deployments-scaling-updates` and a PARTIAL `root-06-m03-jobs-cronjobs-daemonsets`, both in front of the existing bare-lab bank. |
| 7 | Kubernetes Networking & Configuration | **PARTIAL** | Phase 6B added a READY `root-07-m03-services-and-service-discovery` and a PARTIAL `root-07-m04-ingress-networkpolicy-foundations`. The existing configuration bank (`root-07-m02`) still has no authored teaching content — an honest, documented gap. |
| 8 | Kubernetes Storage & Scheduling | **PARTIAL** | Phase 6B wired the real scenario content the inventory identified (PV/PVC, StorageClass, taints/tolerations, PDB, quotas/limits) into two new PARTIAL modules — moved off PLANNED for the first time. |
| 9 | Kubernetes Security | **PARTIAL** | Phase 6B built the 22-scenario CKS-style bank into four modules (Security Model & SecurityContext — READY; ServiceAccounts & RBAC, Network & Supply Chain Security, Cluster Hardening & Runtime — all PARTIAL), classifying scenarios CORE/GUIDED/INDEPENDENT/ADVANCED/ASSESSMENT-BANK rather than exposing them as 22 disconnected tasks — moved off PLANNED. |
| 10 | Kubernetes Troubleshooting & Observability | **PARTIAL** | The Phase 6A gold-standard module (READY, unmodified) plus a new PARTIAL `root-10-m03-troubleshooting-framework` (the generalized Observe/Evidence/Hypothesis/Test/Repair/Validate/Prevent framework) and the existing bare-lab bank, now sequenced last. |
| 11 | DevOps & Platform Engineering Foundations | **PLANNED** | No CI/CD/IaC/GitOps scenario content exists anywhere in this repository — unchanged, out of Phase 6B's authoring scope. |
| 12 | RootNode Real Ops | **PARTIAL** | Phase 6B added an incident-response framing lesson and a post-incident reflection wrapping the existing 4-scenario module — the incidents themselves are unchanged, still deliberately un-guided. |
| 13 | ROOT Capstone — Operate and Recover a Production-Like Environment | **PARTIAL** | Phase 6B added a READY Capstone Readiness module (orientation, no answers) sequenced before the existing capstone assessment module — see `docs/ROOT_CAPSTONE_READINESS.md`. |
No course is marked READY at the course level in Phase 6A — that's honest: a course only earns
READY once every module in it has real teaching content, and Phase 6A deliberately built exactly
+2 -1
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@@ -73,7 +73,7 @@ export default function CurriculumView() {
{mod.estimated_duration_minutes && <p className={styles.muted}>Estimated teaching time: ~{mod.estimated_duration_minutes} min</p>}
{mod.objectives?.length > 0 && <ul>{mod.objectives.map((o, i) => <li key={i}>{o}</li>)}</ul>}
<table>
<thead><tr><th>#</th><th>Type</th><th>Title</th><th>Mapped</th><th>Status</th>{studentCourses && <th>Student</th>}</tr></thead>
<thead><tr><th>#</th><th>Type</th><th>Title</th><th>Mapped</th><th>Required</th><th>Status</th>{studentCourses && <th>Student</th>}</tr></thead>
<tbody>
{mod.activities.map((a) => (
<tr key={a.activity_id}>
@@ -81,6 +81,7 @@ export default function CurriculumView() {
<td>{ACTIVITY_LABELS[a.activity_type] || a.activity_type}</td>
<td>{a.title}</td>
<td className={styles.muted}>{a.scenario_id || a.assessment_definition_id || '—'}</td>
<td className={styles.muted}>{a.is_required === false ? 'optional' : 'required'}</td>
<td>{statusPill(a.status)}</td>
{studentCourses && (
<td>{progressFor(a.activity_id)?.complete ? <span className={`${styles.pill} ${styles.pillOk}`}>done</span> : <span className={styles.muted}>—</span>}</td>
+3 -1
View File
@@ -163,6 +163,7 @@ function ActivityRow({ activity, onOpen }) {
<div style={{ borderTop: '1px solid var(--border)', padding: '0.6rem 0', display: 'flex', justifyContent: 'space-between', alignItems: 'center' }}>
<button className={styles.linkBtn} onClick={onOpen} style={{ textAlign: 'left' }}>
<span className={styles.stageCount}>{ACTIVITY_LABELS[activity.activity_type] || activity.activity_type}</span>{' — '}{activity.title}
{activity.is_required === false && <span className={styles.hint}> (optional)</span>}
</button>
{activity.complete ? <span className={`${styles.pill} ${styles.pillOk}`}>done</span> : activity.estimated_duration_minutes ? <span className={styles.hint}>~{activity.estimated_duration_minutes} min</span> : null}
</div>
@@ -186,7 +187,8 @@ function ActivityDetail({ activity, onLaunchLab, onChange }) {
{activity.complete && <span className={`${styles.pill} ${styles.pillOk}`}>complete</span>}
</div>
<p className={styles.stageCount}>{ACTIVITY_LABELS[activity.activity_type] || activity.activity_type}
{activity.estimated_duration_minutes && ` · ~${activity.estimated_duration_minutes} min`}</p>
{activity.estimated_duration_minutes && ` · ~${activity.estimated_duration_minutes} min`}
{activity.is_required === false && ' · optional'}</p>
{activity.body ? (
<div className="md" style={{ marginTop: '1rem' }}>
+33
View File
@@ -0,0 +1,33 @@
#!/usr/bin/env bash
# Orchestrates the Phase 6B §23 ROOT_ curriculum expansion dress rehearsal: brings up the real
# dev stack, bootstraps an owner, runs test-phase6b-root-course-rehearsal.js (real k3s Lab, real
# kubectl, real classroom tooling), tears down.
set -euo pipefail
cd "$(dirname "${BASH_SOURCE[0]}")/../../../platform"
export PROVISIONER_SHARED_SECRET="${PROVISIONER_SHARED_SECRET:-rehearsal-shared-secret-not-for-production}"
export INTEGRATION_SHARED_SECRET="${INTEGRATION_SHARED_SECRET:-dev-integration-secret-not-for-production}"
docker compose -f docker-compose.dev.yml up -d --build
cleanup() {
echo "==> Tearing down"
docker ps -aq --filter "name=rootnode-lab-" | xargs -r docker rm -f >/dev/null 2>&1 || true
docker network ls --filter "name=rootnode-lab-net-" --format "{{.Name}}" | xargs -r -n1 docker network rm >/dev/null 2>&1 || true
docker compose -f docker-compose.dev.yml down >/dev/null 2>&1 || true
}
trap cleanup EXIT
echo "==> Waiting for the stack"
for _ in $(seq 1 60); do
curl -sf http://localhost:4300/healthz >/dev/null 2>&1 && curl -sf http://localhost:4200/healthz >/dev/null 2>&1 && break
sleep 2
done
echo "==> Bootstrapping the rehearsal owner"
( cd api && PLATFORM_DB_URL=postgres://postgres:postgres@localhost:5433/rootnode_platform \
node bootstrap-owner.js [email protected] "P6B Rehearsal Owner" 'RehearsalPass!2026' )
echo "==> Running the rehearsal"
OWNER_EMAIL=[email protected] OWNER_PASSWORD='RehearsalPass!2026' \
node ../infra/scripts/drills/test-phase6b-root-course-rehearsal.js
@@ -0,0 +1,195 @@
#!/usr/bin/env node
// Phase 6B §23 — the ROOT_ curriculum expansion dress rehearsal. One continuous realistic
// student narrative through a brand-NEW Phase 6B module (ROOT 07's Services & Service
// Discovery, not the Phase 6A gold module — that one already has its own rehearsal), using a
// REAL k3s Lab end to end, plus a short instructor narrative proving the Curriculum view,
// Prepare Labs, and classroom/help tooling all still work against the expanded curriculum. Same
// conventions as test-phase6a-course-rehearsal.js: assert-based, no framework, real k3s boots.
//
// Run via run-phase6b-root-course-rehearsal.sh, which brings up platform/docker-compose.dev.yml
// first.
const assert = require('assert');
const { execSync } = require('child_process');
const { makeSession } = require('../../../platform/test/session-helper');
const GW = process.env.GATEWAY_URL || 'http://localhost:4200';
const OWNER_EMAIL = process.env.OWNER_EMAIL;
const OWNER_PASSWORD = process.env.OWNER_PASSWORD;
if (!OWNER_EMAIL || !OWNER_PASSWORD) { console.error('Set OWNER_EMAIL and OWNER_PASSWORD'); process.exit(1); }
const RUN_ID = Date.now();
const PROGRAM = 'root-kubernetes-foundations';
const SERVICES_MODULE = 'root-07-m03-services-and-service-discovery';
let passed = 0, failed = 0;
async function step(name, fn) {
try { await fn(); console.log(` ok — ${name}`); passed++; }
catch (e) { console.error(` FAIL — ${name}\n ${e.stack || e.message}`); failed++; }
}
function moduleFrom(tree, id) { for (const c of tree) { const m = c.modules.find((x) => x.module_id === id); if (m) return m; } return null; }
async function main() {
console.log('Phase 6B ROOT_ curriculum expansion dress rehearsal — slow, real k3s boots\n');
const owner = makeSession(GW);
await owner.request('POST', '/api/auth/instructor/login', { email: OWNER_EMAIL, password: OWNER_PASSWORD });
const { body: created } = await owner.request('POST', '/api/admin/students', {
display_name: 'Rehearsal 6B Student', login_identifier: `p6b-course-${RUN_ID}`,
});
const session = makeSession(GW);
let enrollmentId, envId;
await step('student activates credentials and logs in', async () => {
const { status } = await session.request('POST', '/api/student/activate', { token: created.activation_token, password: 'RehearsalPass123!' });
assert.equal(status, 200);
});
await step('an instructor enrolls the student in ROOT_', async () => {
const { status, body } = await owner.request('POST', '/api/admin/enrollments', { student_id: created.student_id, program_id: PROGRAM, status: 'active' });
assert.equal(status, 201);
enrollmentId = body.enrollment_id;
});
// Real Foundation completion via a real Lab, so root-06 (and therefore root-07) unlock.
const ROOT05_ALL = ['namespaces-basics', 'pod-basics-mcq', 'kubectl-essentials-mcq', 'labels-selectors-mcq', 'init-containers-mcq',
'multi-container-pod-basics', 'pod-labeling-basics', 'jsonpath-basics', 'dry-run-manifest-basics', 'delete-by-label-basics',
'annotate-resource-basics', 'init-container-task-basics', 'restart-policy-mcq', 'kubectl-output-format-mcq',
'kubectl-explain-basics', 'kubectl-patch-basics', 'field-selector-basics', 'sort-by-basics', 'kubectl-diff-basics', 'static-pods-mcq'];
const ROOT06_ALL = ['deploy-nginx', 'scale-deployment', 'rolling-update-task', 'liveness-probe-task', 'jobs-cronjobs-mcq',
'daemonset-mcq', 'edit-deployment-basics', 'deployment-strategy-mcq', 'deployment-rollback'];
await step('student launches a REAL Lab and completes ROOT 05 + ROOT 06 to unlock ROOT 07\'s new Services module', async () => {
const launch = await session.request('POST', `/api/student/programs/${enrollmentId}/launch`);
assert.equal(launch.status, 200);
assert.equal(launch.body.status, 'running');
const envRow = (await owner.request('GET', `/api/admin/students/${created.student_id}/environment`)).body.find((e) => e.status === 'running');
envId = envRow.environment_id;
for (const sid of [...ROOT05_ALL, ...ROOT06_ALL]) {
const r = await session.request('POST', '/api/progress/record', { scenario_id: sid, status: 'completed', environment_id: envId });
assert.equal(r.status, 200, `completing ${sid} should 200`);
}
// Both new teaching modules' own lesson/demo/knowledge-check/guided-exercise/reflection
// activities are manual_marker — completing only the underlying scenarios (above) is not
// enough to make root-05/root-06 COURSE-complete, which is what actually unlocks root-07.
for (const suffix of ['a01-lesson-mental-model', 'a02-demonstration-desired-state', 'a03-knowledge-check', 'a04-guided-exercise-namespaces', 'a06-reflection']) {
const r = await session.request('POST', `/api/student/activities/root-05-m00-${suffix}/complete`);
assert.equal(r.status, 200);
}
for (const suffix of ['a01-lesson-deployments', 'a02-demonstration-rollout', 'a03-knowledge-check', 'a04-guided-exercise-rollout-strategy', 'a06-reflection']) {
const r = await session.request('POST', `/api/student/activities/root-06-m02-${suffix}/complete`);
assert.equal(r.status, 200);
}
// root-06 the COURSE (root-07's actual prerequisite) also includes m03 — its two scenarios
// and two manual-marker activities.
for (const sid of ['job-task', 'cronjob-task']) {
const r = await session.request('POST', '/api/progress/record', { scenario_id: sid, status: 'completed', environment_id: envId });
assert.equal(r.status, 200);
}
for (const suffix of ['a01-lesson-jobs-cronjobs-daemonsets', 'a02-knowledge-check']) {
const r = await session.request('POST', `/api/student/activities/root-06-m03-${suffix}/complete`);
assert.equal(r.status, 200);
}
});
await step('the new ROOT 07 Services & Service Discovery module is now unlocked with real lesson content', async () => {
const { body } = await session.request('GET', `/api/student/programs/${enrollmentId}/courses`);
const mod = moduleFrom(body.courses, SERVICES_MODULE);
assert.equal(mod.locked, false);
assert.equal(mod.activities[0].activity_type, 'lesson');
assert.ok(mod.activities[0].body.includes('Service'), 'the real lesson content must actually be served');
});
await step('student reads the lesson/demonstration, completes the knowledge check and guided exercise', async () => {
for (const suffix of ['a01-lesson-services', 'a02-demonstration-zero-endpoints', 'a03-knowledge-check', 'a04-guided-exercise-service-type']) {
const { status } = await session.request('POST', `/api/student/activities/root-07-m03-${suffix}/complete`);
assert.equal(status, 200);
}
});
await step('student launches the module\'s Lab activity for real and runs real kubectl against it', async () => {
const { body } = await session.request('GET', `/api/student/programs/${enrollmentId}/courses`);
const mod = moduleFrom(body.courses, SERVICES_MODULE);
const lab = mod.activities.find((a) => a.activity_type === 'lab');
assert.equal(lab.scenario_id, 'expose-service-basics');
assert.equal(lab.complete, false);
const launch = await session.request('POST', `/api/student/programs/${enrollmentId}/launch`);
const labToken = launch.body.launch_path.match(/\/lab\/([^/]+)\//)[1];
const setup = await session.request('POST', `/lab/${labToken}/api/scenarios/expose-service-basics/setup`);
assert.equal(setup.status, 200);
// Real kubectl, run inside the student's actual disposable Lab container — solving the
// scenario the same way a real student would from the terminal, not a simulated pass.
const containerName = execSync(
`docker compose -f docker-compose.dev.yml exec -T postgres psql -U postgres -d rootnode_platform -t -c "SELECT container_name FROM environments WHERE environment_id = '${envId}'"`,
{ cwd: `${__dirname}/../../../platform`, stdio: 'pipe' }
).toString().trim();
execSync(`docker exec ${containerName} kubectl expose deployment redis --name=redis-svc --port=6379`, { stdio: 'pipe' });
const validate = await session.request('POST', `/lab/${labToken}/api/scenarios/expose-service-basics/validate`);
assert.equal(validate.status, 200);
assert.equal(validate.body.passed, true, `expected the real validation to pass: ${JSON.stringify(validate.body)}`);
const record = await session.request('POST', '/api/progress/record', { scenario_id: 'expose-service-basics', status: 'completed', environment_id: envId });
assert.equal(record.status, 200);
});
await step('the lab activity completes and the module finishes once the reflection is marked', async () => {
const { body: before } = await session.request('GET', `/api/student/programs/${enrollmentId}/courses`);
assert.equal(moduleFrom(before.courses, SERVICES_MODULE).activities.find((a) => a.activity_type === 'lab').complete, true);
await session.request('POST', '/api/student/activities/root-07-m03-a06-reflection/complete');
const { body: after } = await session.request('GET', `/api/student/programs/${enrollmentId}/courses`);
assert.equal(moduleFrom(after.courses, SERVICES_MODULE).complete, true);
});
await step('logout, login, Resume Learning, destroy the Lab, recreate it — academic progress survives all of it', async () => {
await session.request('POST', '/api/logout');
const returning = makeSession(GW);
await returning.request('POST', '/api/student/login', { identifier: `p6b-course-${RUN_ID}`, password: 'RehearsalPass123!' });
const { body: resumed } = await returning.request('GET', `/api/student/programs/${enrollmentId}/courses`);
assert.equal(moduleFrom(resumed.courses, SERVICES_MODULE).complete, true, 'progress must survive a real logout/login');
await owner.request('DELETE', `/api/admin/environments/${envId}`);
const relaunch = await returning.request('POST', `/api/student/programs/${enrollmentId}/launch`);
assert.equal(relaunch.status, 200);
assert.equal(relaunch.body.status, 'running');
const { body: afterRecreate } = await returning.request('GET', `/api/student/programs/${enrollmentId}/courses`);
assert.equal(moduleFrom(afterRecreate.courses, SERVICES_MODULE).complete, true, 'academic progress must survive Lab destroy/recreate');
});
// ── Instructor narrative ────────────────────────────────────────────────────────────────
await step('instructor inspects the curriculum structure and this module\'s teaching notes', async () => {
const { status, body } = await owner.request('GET', `/api/admin/programs/${PROGRAM}/courses`);
assert.equal(status, 200);
const mod = moduleFrom(body, SERVICES_MODULE);
assert.equal(mod.activities.length, 6);
assert.ok(mod.activities[0].instructor_notes, 'instructor must see instructor notes the student view never does');
});
await step('instructor sees this specific student\'s real progress through the new module', async () => {
const { status, body } = await owner.request('GET', `/api/admin/students/${created.student_id}/courses?program_id=${PROGRAM}`);
assert.equal(status, 200);
assert.equal(moduleFrom(body, SERVICES_MODULE).complete, true);
});
await step('a real classroom cohort can still be prepared and observed alongside the expanded curriculum', async () => {
const cohortId = `p6b-rehearsal-cohort-${RUN_ID}`;
const create = await owner.request('POST', '/api/admin/cohorts', { cohort_id: cohortId, name: 'P6B Rehearsal Cohort' });
assert.equal(create.status, 201);
const { body: student2 } = await owner.request('POST', '/api/admin/students', { display_name: 'P6B Cohort Student', login_identifier: `p6b-cohort-student-${RUN_ID}` });
const addStudent = await owner.request('POST', `/api/admin/students/${student2.student_id}/cohort`, { cohort_id: cohortId });
assert.equal(addStudent.status, 200);
const assignCurriculum = await owner.request('POST', `/api/admin/cohorts/${cohortId}/curriculum`, { curriculum_path: 'rootnode-path' });
assert.equal(assignCurriculum.status, 200);
const prepare = await owner.request('POST', `/api/admin/cohorts/${cohortId}/prepare-labs`);
assert.equal(prepare.status, 200);
const summary = await owner.request('GET', `/api/admin/cohorts/${cohortId}/learning`);
assert.equal(summary.status, 200, 'classroom/learning tooling must still function against the expanded curriculum');
});
console.log(`\n${passed} passed, ${failed} failed`);
if (failed > 0) process.exit(1);
}
main().catch((e) => { console.error(e); process.exit(1); });
+19 -6
View File
@@ -14,7 +14,9 @@ entrypoint/Dockerfile unmodified; frontend bundle gained Phase 3B learning UX, s
(Phase 5A), self-paced programs/enrollment + the website integration boundary (Phase 5B), and
a provider-neutral enrollment-communications pipeline (activation/enrollment-confirmation/
password-reset email, Phase 5C), the ROOT_ course/module/activity content model layered over
curriculum/assessments (Phase 6A), and the instructor/admin control plane. No k3s, no
curriculum/assessments (Phase 6A) with real teaching content across most of the Kubernetes
courses and a server-side capstone unlock enforcement fix (Phase 6B), and the instructor/admin
control plane. No k3s, no
`--privileged` — this replaced Phase 2A's "identity" instance, which was a full Lab image
booting an unused k3s cluster just to serve these APIs. Design:
`docs/PHASE2B_ADMIN_AND_PLATFORM_DATA.md` (split + Postgres migration),
@@ -24,7 +26,8 @@ entrypoint/Dockerfile unmodified; frontend bundle gained Phase 3B learning UX, s
`docs/PHASE5B_SELF_PACED_ENROLLMENT.md` (programs, enrollment, website integration boundary),
`docs/PHASE5C_ENROLLMENT_COMMUNICATIONS.md` (notifications, email delivery),
`docs/PHASE6A_ROOT_COURSE_FOUNDATION.md` (course/module/activity content model, gold-standard
module). Operational reference: `api/README.md`.
module), `docs/PHASE6B_ROOT_CURRICULUM_EXPANSION.md` (curriculum authoring across ROOT
05-10/12/Capstone, the capstone unlock fix). Operational reference: `api/README.md`.
- `gateway/` — the only student-facing path to a Lab (HTTP + WebSocket proxy, environment-aware
routing derived from a server-controlled session — not a client-suppliable header/param — and,
as of Phase 3B, server-side gating of progressive hint reveal). Design:
@@ -88,15 +91,25 @@ further instructor accounts from the Instructors tab).
- `test/e2e-phase6a.js` — course/module/activity hierarchy and ordering, prerequisite-based
locking, all three completion behaviors (manual marker/scenario/assessment-derived), resume,
cross-student isolation, RBAC for self-paced (no-cohort) students, and draft-content hiding.
- `test/e2e-phase6b.js` — hierarchy for the 13 new modules across ROOT 05-10/12/Capstone,
prerequisite chains through the newly-inserted front-door modules, the optional-vs-required
(`is_required`) completion rule, and the capstone server-side unlock fix in both directions
(a direct bypass attempt rejected, a legitimately unlocked attempt still accepted).
All e2e suites need `OWNER_EMAIL` / `OWNER_PASSWORD` set to a real bootstrapped instructor
account (see "Running the full stack locally" above) — the old `ADMIN_PASSWORD` mechanism is
gone. They're slow (real k3s boots, `e2e-phase3b.js` also runs a real API restart) and need the
full stack up. None of them substitute for the manual real-Lab-image checks (node-pty, terminal
full stack up. Run each suite against its own freshly-reset stack, not chained one after another
against the same Postgres — several routes (the admin dashboard's running-lab count, a course's
percent-complete) read GLOBAL state on purpose, and chaining suites produces false failures from
shared state, not real regressions (found and documented during Phase 6A's own regression pass).
None of them substitute for the manual real-Lab-image checks (node-pty, terminal
WebSocket, `kubectl`, scenario validation) in `docs/PHASE2A_GATEWAY_AND_STUDENT_FLOW.md` §8 —
those need a browser-equivalent client and aren't automated here. The one exception is Phase
6A's gold-standard module, which DOES get a real-Lab dress rehearsal —
`infra/scripts/drills/run-phase6a-course-rehearsal.sh`.
those need a browser-equivalent client and aren't automated here. Two exceptions get a real-Lab
dress rehearsal instead: Phase 6A's gold-standard module
(`infra/scripts/drills/run-phase6a-course-rehearsal.sh`) and Phase 6B's curriculum expansion,
including a real `kubectl expose` and a real instructor/classroom narrative
(`infra/scripts/drills/run-phase6b-root-course-rehearsal.sh`).
## Known limitations
@@ -0,0 +1,332 @@
-- Phase 6B — curriculum authoring & coverage expansion. Additive on top of Phase 6A's
-- 022_course_content.sql: new teaching modules for ROOT 05/06/07/08/09/10/12/Capstone, built
-- from real, previously-unwired scenario content (see docs/ROOT_CURRICULUM_COVERAGE_MATRIX.md
-- for the evidence and reasoning behind every placement). No existing row is deleted; a small
-- number of existing rows have their `sequence`/`prerequisites` updated so a new teaching
-- module sits in front of the bare-lab bank it supersedes as the "front door" — never their
-- scenario_id/activity_type/completion_behavior, so no student's derived completion state
-- changes meaning. See docs/COURSE_CONTENT_MODEL.md §"content revision" for what does and
-- doesn't require this kind of change.
-- ── is_required: Phase 6B §18/§27's optional-vs-required distinction. Defaults true, so every
-- Phase 6A activity is unaffected (required, as it always implicitly was) — this is additive,
-- not a redefinition. An optional activity (independent-practice duplicates, advanced/CKS-exam-
-- style extras — see docs/ROOT_CURRICULUM_COVERAGE_MATRIX.md's ADVANCED/INDEPENDENT
-- classifications) still counts toward a module's percent_complete display but NOT toward
-- whether the module is considered complete — see course-progress.js's totals().
ALTER TABLE module_activities ADD COLUMN IF NOT EXISTS is_required BOOLEAN NOT NULL DEFAULT true;
-- ── Course status: ROOT 08/09 move from PLANNED to PARTIAL — real modules exist now ─────────
UPDATE courses SET status = 'partial', updated_at = now() WHERE course_id IN ('root-08-kubernetes-storage-scheduling', 'root-09-kubernetes-security');
-- ── Resequencing: new teaching modules become the front door; existing bare-lab banks move
-- behind them. Sequence/prerequisites only — activities inside the existing modules are
-- untouched. ──────────────────────────────────────────────────────────────────────────────
UPDATE course_modules SET sequence = 2, prerequisites = '{root-05-m00-kubernetes-mental-model}', version = version + 1, updated_at = now()
WHERE module_id = 'root-05-m01-pods-and-kubectl-basics';
UPDATE course_modules SET sequence = 3, prerequisites = '{root-06-m02-deployments-scaling-updates}', version = version + 1, updated_at = now()
WHERE module_id = 'root-06-m01-deployments-and-workloads';
UPDATE course_modules SET sequence = 3, prerequisites = '{root-07-m03-services-and-service-discovery}', version = version + 1, updated_at = now()
WHERE module_id = 'root-07-m01-services-and-networking';
-- root-07-m02 (configuration bank) is intentionally left UNGATED (no new configuration-teaching
-- module was authored this phase — an honest PARTIAL gap, see
-- docs/ROOT_CURRICULUM_COVERAGE_MATRIX.md) but still needs to move behind the new
-- teaching modules in display order, to avoid colliding with m04's sequence=2.
UPDATE course_modules SET sequence = 4, version = version + 1, updated_at = now()
WHERE module_id = 'root-07-m02-configuration-and-secrets';
UPDATE course_modules SET sequence = 3, prerequisites = '{root-10-m03-troubleshooting-framework}', version = version + 1, updated_at = now()
WHERE module_id = 'root-10-m02-general-troubleshooting';
INSERT INTO course_modules (module_id, course_id, title, description, sequence, objectives, prerequisites, estimated_duration_minutes, status) VALUES
('root-05-m00-kubernetes-mental-model', 'root-05-kubernetes-foundations', 'The Kubernetes Mental Model & Core Objects',
'What Kubernetes actually solves, the control-plane/worker/desired-state model, and Pods/Namespaces/labels through kubectl — the real front door to ROOT 05, taught before the bare kubectl-fluency lab bank.',
1, '{"Explain what problem Kubernetes solves and why running containers by hand does not scale","Describe the control-plane/worker split and what \"desired state\" means in practice","Navigate Pods, Namespaces, and labels with kubectl confidently"}',
'{}', 45, 'ready'),
('root-06-m02-deployments-scaling-updates', 'root-06-kubernetes-application-workloads', 'Deployments, Scaling & Updates',
'Why Deployments/ReplicaSets exist, how a rolling update actually progresses, and how to reason about rollback — taught before the bare Deployments lab bank.',
1, '{"Explain why a Deployment manages Pods instead of creating them directly","Perform and reason about a rolling update in progress","Explain what a rollback actually restores and when to use one"}',
'{root-05-m00-kubernetes-mental-model}', 55, 'ready'),
('root-06-m03-jobs-cronjobs-daemonsets', 'root-06-kubernetes-application-workloads', 'Jobs, CronJobs & DaemonSets',
'Distinguishing one-shot Jobs, scheduled CronJobs, and per-node DaemonSets from long-running Deployments.',
2, '{"Choose the right workload primitive for a one-shot task, a scheduled task, and a per-node agent","Explain why a Job differs from a Deployment in restart/completion semantics"}',
'{root-06-m02-deployments-scaling-updates}', 30, 'partial'),
('root-07-m03-services-and-service-discovery', 'root-07-kubernetes-networking-config', 'Services & Service Discovery',
'The Service/Endpoints/DNS request path and choosing the right Service type — taught before the bare Services lab bank.',
1, '{"Trace how a request actually reaches a Pod through a Service","Choose ClusterIP vs NodePort correctly for a given requirement","Explain why a Service with zero endpoints looks like network failure from outside"}',
'{root-06-m02-deployments-scaling-updates}', 45, 'ready'),
('root-07-m04-ingress-networkpolicy-foundations', 'root-07-kubernetes-networking-config', 'Ingress & NetworkPolicy Foundations',
'How Ingress routes external traffic, and what a NetworkPolicy architecturally does (the security posture comes later, in ROOT 09).',
2, '{"Explain how Ingress differs from a Service and why it exists","Describe what a NetworkPolicy actually controls at the architectural level"}',
'{root-07-m03-services-and-service-discovery}', 30, 'partial'),
('root-08-m01-storage-fundamentals', 'root-08-kubernetes-storage-scheduling', 'Storage Fundamentals',
'Ephemeral vs. persistent storage, and how PersistentVolumes/PersistentVolumeClaims/StorageClasses fit together.',
1, '{"Explain the difference between ephemeral and persistent storage in Kubernetes","Describe how a PVC binds to a PV, directly or via dynamic provisioning"}',
'{root-07-m03-services-and-service-discovery}', 35, 'partial'),
('root-08-m02-scheduling-resource-governance', 'root-08-kubernetes-storage-scheduling', 'Scheduling & Resource Governance',
'How the scheduler places Pods, and how quotas/limits/priority/disruption budgets shape that placement.',
2, '{"Explain how taints/tolerations and affinity influence scheduling decisions","Explain why a PodDisruptionBudget matters during a voluntary disruption","Describe what a ResourceQuota/LimitRange enforces at the namespace level"}',
'{root-08-m01-storage-fundamentals}', 40, 'partial'),
('root-09-m01-security-model-and-securitycontext', 'root-09-kubernetes-security', 'Security Model & SecurityContext',
'Defense in depth, least privilege, and hardening a Pod with SecurityContext (non-root, capabilities, read-only filesystem).',
1, '{"Explain defense in depth and least privilege as applied to a running Pod","Configure a Pod/container SecurityContext to run non-root with a read-only filesystem and no unnecessary Linux capabilities"}',
'{root-06-m02-deployments-scaling-updates}', 50, 'ready'),
('root-09-m02-serviceaccounts-and-rbac', 'root-09-kubernetes-security', 'ServiceAccounts & RBAC',
'Identity for workloads and least-privilege permissions via Roles/ClusterRoles.',
2, '{"Explain why a Pod needs its own identity separate from the human operating it","Write a least-privilege Role/RoleBinding for a specific, narrow permission"}',
'{root-09-m01-security-model-and-securitycontext}', 40, 'partial'),
('root-09-m03-network-and-supplychain-security', 'root-09-kubernetes-security', 'Network & Supply Chain Security',
'NetworkPolicy as a security control (not just an architecture concept), image/registry trust, and TLS ingress.',
3, '{"Apply a default-deny NetworkPolicy and open only the access a workload actually needs","Explain why an image-pull secret and a trusted registry matter for supply-chain security"}',
'{root-09-m02-serviceaccounts-and-rbac,root-07-m04-ingress-networkpolicy-foundations}', 40, 'partial'),
('root-09-m04-cluster-hardening-and-runtime', 'root-09-kubernetes-security', 'Cluster Hardening & Runtime Security',
'Pod Security Admission and a survey of cluster-hardening/runtime-sandboxing topics — deliberately advanced/optional, not daily-driver core.',
4, '{"Explain what Pod Security Admission enforces at the namespace level and how it differs from the old PodSecurityPolicy"}',
'{root-09-m03-network-and-supplychain-security}', 25, 'partial'),
('root-10-m03-troubleshooting-framework', 'root-10-kubernetes-troubleshooting-observability', 'The RootNode Troubleshooting Framework',
'A repeatable framework — Observe, Gather Evidence, Form Hypothesis, Test, Repair, Validate, Prevent Recurrence — applied to a CrashLoopBackOff and a broken Service.',
2, '{"Apply a repeatable troubleshooting framework instead of guessing under pressure","Diagnose a CrashLoopBackOff from evidence, not assumption","Diagnose a broken Service-to-Pod selector mismatch"}',
'{root-10-m01-health-probes-and-troubleshooting}', 40, 'partial'),
('root-capstone-m02-capstone-readiness', 'root-capstone', 'Capstone Readiness',
'What the RootNode Capstone measures, what it requires, how the timed/randomized draw works, and how to manage your time — without publishing the draw or the answers.',
1, '{"Explain what skills the RootNode Capstone measures and why","Describe how the timed, partially-randomized scenario draw works","Apply the RootNode troubleshooting framework under time pressure"}',
'{}', 20, 'ready')
ON CONFLICT (module_id) DO NOTHING;
-- The existing capstone assessment module keeps its original sequence position (2) relative to
-- the new readiness module (1) — readiness comes first, matching that it now needs no
-- prerequisite of its own (the course-level root-12-real-ops -> root-capstone chain still
-- gates entry into this course at all; the actual capstone START is gated server-side by
-- curriculum-rules.js's unlock_rule regardless of whether this readiness module was viewed —
-- see docs/ROOT_CAPSTONE_READINESS.md for why those two gates are deliberately independent).
UPDATE course_modules SET sequence = 2 WHERE module_id = 'root-capstone-m01-operate-and-recover';
-- ═══════════════════════════════════════════════════════════════════════════════════════════
-- New module_activities — gold-standard modules (lesson+demo+knowledge_check+guided_exercise+
-- lab+reflection) for root-05-m00, root-06-m02, root-07-m03, root-09-m01. PARTIAL modules get
-- lesson+knowledge_check(+lab) only, honestly, per docs/ROOT_CURRICULUM_COVERAGE_MATRIX.md.
-- ═══════════════════════════════════════════════════════════════════════════════════════════
-- ROOT 05 m00 — 6 activities
INSERT INTO module_activities (activity_id, module_id, sequence, activity_type, title, content_path, scenario_id, assessment_definition_id, completion_behavior, estimated_duration_minutes, status) VALUES
('root-05-m00-a01-lesson-mental-model', 'root-05-m00-kubernetes-mental-model', 1, 'lesson', 'What Kubernetes Solves & the Desired-State Model',
'content/root/root-05-kubernetes-foundations/m00-mental-model/01-lesson-mental-model.md', NULL, NULL, 'manual_marker', 15, 'ready'),
('root-05-m00-a02-demonstration-desired-state', 'root-05-m00-kubernetes-mental-model', 2, 'demonstration', 'Demonstration: Desired State Reconciliation',
'content/root/root-05-kubernetes-foundations/m00-mental-model/02-demonstration-desired-state.md', NULL, NULL, 'manual_marker', 10, 'ready'),
('root-05-m00-a03-knowledge-check', 'root-05-m00-kubernetes-mental-model', 3, 'knowledge_check', 'Knowledge Check: The Kubernetes Mental Model',
'content/root/root-05-kubernetes-foundations/m00-mental-model/03-knowledge-check.md', NULL, NULL, 'manual_marker', 5, 'ready'),
('root-05-m00-a04-guided-exercise-namespaces', 'root-05-m00-kubernetes-mental-model', 4, 'guided_exercise', 'Guided Exercise: Planning a Namespace Layout',
'content/root/root-05-kubernetes-foundations/m00-mental-model/04-guided-exercise-namespaces.md', NULL, NULL, 'manual_marker', 10, 'ready'),
('root-05-m00-a05-lab-namespaces-basics', 'root-05-m00-kubernetes-mental-model', 5, 'lab', 'Launch Lab: Working with Namespaces',
'content/root/root-05-kubernetes-foundations/m00-mental-model/05-lab-intro.md', 'namespaces-basics', NULL, 'auto_scenario', 15, 'ready'),
('root-05-m00-a06-reflection', 'root-05-m00-kubernetes-mental-model', 6, 'reflection', 'Reflection: Why Desired State Matters in Production',
'content/root/root-05-kubernetes-foundations/m00-mental-model/06-reflection.md', NULL, NULL, 'manual_marker', 10, 'ready')
ON CONFLICT (activity_id) DO NOTHING;
-- ROOT 06 m02 — 6 activities
INSERT INTO module_activities (activity_id, module_id, sequence, activity_type, title, content_path, scenario_id, assessment_definition_id, completion_behavior, estimated_duration_minutes, status) VALUES
('root-06-m02-a01-lesson-deployments', 'root-06-m02-deployments-scaling-updates', 1, 'lesson', 'Why Deployments Exist & How a Rolling Update Progresses',
'content/root/root-06-kubernetes-application-workloads/m02-deployments-scaling-updates/01-lesson-deployments.md', NULL, NULL, 'manual_marker', 15, 'ready'),
('root-06-m02-a02-demonstration-rollout', 'root-06-m02-deployments-scaling-updates', 2, 'demonstration', 'Demonstration: Watching a Rollout, Good and Bad',
'content/root/root-06-kubernetes-application-workloads/m02-deployments-scaling-updates/02-demonstration-rollout.md', NULL, NULL, 'manual_marker', 10, 'ready'),
('root-06-m02-a03-knowledge-check', 'root-06-m02-deployments-scaling-updates', 3, 'knowledge_check', 'Knowledge Check: Deployments & Rollouts',
'content/root/root-06-kubernetes-application-workloads/m02-deployments-scaling-updates/03-knowledge-check.md', NULL, NULL, 'manual_marker', 5, 'ready'),
('root-06-m02-a04-guided-exercise-rollout-strategy', 'root-06-m02-deployments-scaling-updates', 4, 'guided_exercise', 'Guided Exercise: Planning a Safe Rollout Strategy',
'content/root/root-06-kubernetes-application-workloads/m02-deployments-scaling-updates/04-guided-exercise-rollout-strategy.md', NULL, NULL, 'manual_marker', 15, 'ready'),
('root-06-m02-a05-lab-rolling-update', 'root-06-m02-deployments-scaling-updates', 5, 'lab', 'Launch Lab: Perform a Rolling Update',
'content/root/root-06-kubernetes-application-workloads/m02-deployments-scaling-updates/05-lab-intro.md', 'rolling-update-task', NULL, 'auto_scenario', 15, 'ready'),
('root-06-m02-a05b-lab-deployment-rollback', 'root-06-m02-deployments-scaling-updates', 6, 'lab', 'Lab: Rolling Back a Deployment', NULL, 'deployment-rollback', NULL, 'auto_scenario', 15, 'ready'),
('root-06-m02-a06-reflection', 'root-06-m02-deployments-scaling-updates', 7, 'reflection', 'Reflection: Rollback Is a Plan, Not a Panic Button',
'content/root/root-06-kubernetes-application-workloads/m02-deployments-scaling-updates/06-reflection.md', NULL, NULL, 'manual_marker', 10, 'ready')
ON CONFLICT (activity_id) DO NOTHING;
-- ROOT 06 m03 — 4 activities (PARTIAL: lesson + knowledge_check + two labs)
INSERT INTO module_activities (activity_id, module_id, sequence, activity_type, title, content_path, scenario_id, assessment_definition_id, completion_behavior, estimated_duration_minutes, status) VALUES
('root-06-m03-a01-lesson-jobs-cronjobs-daemonsets', 'root-06-m03-jobs-cronjobs-daemonsets', 1, 'lesson', 'Jobs, CronJobs, and DaemonSets: The Other Workload Shapes',
'content/root/root-06-kubernetes-application-workloads/m03-jobs-cronjobs-daemonsets/01-lesson-jobs-cronjobs-daemonsets.md', NULL, NULL, 'manual_marker', 15, 'ready'),
('root-06-m03-a02-knowledge-check', 'root-06-m03-jobs-cronjobs-daemonsets', 2, 'knowledge_check', 'Knowledge Check: Choosing the Right Workload Primitive',
'content/root/root-06-kubernetes-application-workloads/m03-jobs-cronjobs-daemonsets/02-knowledge-check.md', NULL, NULL, 'manual_marker', 5, 'ready'),
('root-06-m03-a03-lab-job-task', 'root-06-m03-jobs-cronjobs-daemonsets', 3, 'lab', 'Lab: Create a One-Shot Job', NULL, 'job-task', NULL, 'auto_scenario', 15, 'ready'),
('root-06-m03-a04-lab-cronjob-task', 'root-06-m03-jobs-cronjobs-daemonsets', 4, 'lab', 'Lab: Create a CronJob', NULL, 'cronjob-task', NULL, 'auto_scenario', 15, 'ready')
ON CONFLICT (activity_id) DO NOTHING;
-- ROOT 07 m03 — 6 activities
INSERT INTO module_activities (activity_id, module_id, sequence, activity_type, title, content_path, scenario_id, assessment_definition_id, completion_behavior, estimated_duration_minutes, status) VALUES
('root-07-m03-a01-lesson-services', 'root-07-m03-services-and-service-discovery', 1, 'lesson', 'The Service/Endpoints/DNS Request Path',
'content/root/root-07-kubernetes-networking-config/m03-services-and-service-discovery/01-lesson-services.md', NULL, NULL, 'manual_marker', 15, 'ready'),
('root-07-m03-a02-demonstration-zero-endpoints', 'root-07-m03-services-and-service-discovery', 2, 'demonstration', 'Demonstration: A Service With Zero Endpoints',
'content/root/root-07-kubernetes-networking-config/m03-services-and-service-discovery/02-demonstration-zero-endpoints.md', NULL, NULL, 'manual_marker', 10, 'ready'),
('root-07-m03-a03-knowledge-check', 'root-07-m03-services-and-service-discovery', 3, 'knowledge_check', 'Knowledge Check: Services & Service Discovery',
'content/root/root-07-kubernetes-networking-config/m03-services-and-service-discovery/03-knowledge-check.md', NULL, NULL, 'manual_marker', 5, 'ready'),
('root-07-m03-a04-guided-exercise-service-type', 'root-07-m03-services-and-service-discovery', 4, 'guided_exercise', 'Guided Exercise: Choosing the Right Service Type',
'content/root/root-07-kubernetes-networking-config/m03-services-and-service-discovery/04-guided-exercise-service-type.md', NULL, NULL, 'manual_marker', 10, 'ready'),
('root-07-m03-a05-lab-expose-service', 'root-07-m03-services-and-service-discovery', 5, 'lab', 'Launch Lab: Exposing an Application',
'content/root/root-07-kubernetes-networking-config/m03-services-and-service-discovery/05-lab-intro.md', 'expose-service-basics', NULL, 'auto_scenario', 15, 'ready'),
('root-07-m03-a06-reflection', 'root-07-m03-services-and-service-discovery', 6, 'reflection', 'Reflection: Service Discovery Is Infrastructure, Not Magic',
'content/root/root-07-kubernetes-networking-config/m03-services-and-service-discovery/06-reflection.md', NULL, NULL, 'manual_marker', 10, 'ready')
ON CONFLICT (activity_id) DO NOTHING;
-- ROOT 07 m01 (existing bare bank) — extend with the two newly-wired networking scenarios
INSERT INTO module_activities (activity_id, module_id, sequence, activity_type, title, content_path, scenario_id, assessment_definition_id, completion_behavior, estimated_duration_minutes, status) VALUES
('root-07-m01-a03-nodeport-task', 'root-07-m01-services-and-networking', 3, 'lab', 'Lab: Expose a Deployment via NodePort', NULL, 'nodeport-task', NULL, 'auto_scenario', 15, 'ready'),
('root-07-m01-a04-dns-resolution-mcq', 'root-07-m01-services-and-networking', 4, 'lab', 'Lab: Kubernetes DNS Resolution', NULL, 'dns-resolution-mcq', NULL, 'auto_scenario', 15, 'ready')
ON CONFLICT (activity_id) DO NOTHING;
-- ROOT 07 m04 — 4 activities (PARTIAL)
INSERT INTO module_activities (activity_id, module_id, sequence, activity_type, title, content_path, scenario_id, assessment_definition_id, completion_behavior, estimated_duration_minutes, status) VALUES
('root-07-m04-a01-lesson-ingress-networkpolicy', 'root-07-m04-ingress-networkpolicy-foundations', 1, 'lesson', 'Ingress and NetworkPolicy: What They Architecturally Do',
'content/root/root-07-kubernetes-networking-config/m04-ingress-networkpolicy-foundations/01-lesson-ingress-networkpolicy.md', NULL, NULL, 'manual_marker', 15, 'ready'),
('root-07-m04-a02-knowledge-check', 'root-07-m04-ingress-networkpolicy-foundations', 2, 'knowledge_check', 'Knowledge Check: Ingress & NetworkPolicy Foundations',
'content/root/root-07-kubernetes-networking-config/m04-ingress-networkpolicy-foundations/02-knowledge-check.md', NULL, NULL, 'manual_marker', 5, 'ready'),
('root-07-m04-a03-lab-ingress-task', 'root-07-m04-ingress-networkpolicy-foundations', 3, 'lab', 'Lab: Create an Ingress Resource', NULL, 'ingress-task', NULL, 'auto_scenario', 20, 'ready'),
('root-07-m04-a04-lab-network-policy', 'root-07-m04-ingress-networkpolicy-foundations', 4, 'lab', 'Lab: Isolate Traffic with NetworkPolicy', NULL, 'network-policy', NULL, 'auto_scenario', 30, 'ready')
ON CONFLICT (activity_id) DO NOTHING;
-- ROOT 08 m01 — 4 activities (PARTIAL)
INSERT INTO module_activities (activity_id, module_id, sequence, activity_type, title, content_path, scenario_id, assessment_definition_id, completion_behavior, estimated_duration_minutes, status) VALUES
('root-08-m01-a01-lesson-storage-fundamentals', 'root-08-m01-storage-fundamentals', 1, 'lesson', 'Ephemeral vs. Persistent Storage',
'content/root/root-08-kubernetes-storage-scheduling/m01-storage-fundamentals/01-lesson-storage-fundamentals.md', NULL, NULL, 'manual_marker', 15, 'ready'),
('root-08-m01-a02-knowledge-check', 'root-08-m01-storage-fundamentals', 2, 'knowledge_check', 'Knowledge Check: Storage Fundamentals',
'content/root/root-08-kubernetes-storage-scheduling/m01-storage-fundamentals/02-knowledge-check.md', NULL, NULL, 'manual_marker', 5, 'ready'),
('root-08-m01-a03-lab-emptydir', 'root-08-m01-storage-fundamentals', 3, 'lab', 'Lab: Shared emptyDir Volume Between Containers', NULL, 'emptydir-pod', NULL, 'auto_scenario', 15, 'ready'),
('root-08-m01-a04-lab-pv-pvc', 'root-08-m01-storage-fundamentals', 4, 'lab', 'Lab: Persistent Storage with PV and PVC', NULL, 'pv-pvc-mount', NULL, 'auto_scenario', 20, 'ready'),
('root-08-m01-a05-lab-pvc-dynamic', 'root-08-m01-storage-fundamentals', 5, 'lab', 'Lab: Dynamic PVC Provisioning', NULL, 'pvc-dynamic-task', NULL, 'auto_scenario', 20, 'ready'),
('root-08-m01-a06-lab-storageclass', 'root-08-m01-storage-fundamentals', 6, 'lab', 'Lab: StorageClass Reclaim Policies', NULL, 'storageclass-mcq', NULL, 'auto_scenario', 15, 'ready')
ON CONFLICT (activity_id) DO NOTHING;
-- ROOT 08 m02 — 8 activities (PARTIAL)
INSERT INTO module_activities (activity_id, module_id, sequence, activity_type, title, content_path, scenario_id, assessment_definition_id, completion_behavior, estimated_duration_minutes, status) VALUES
('root-08-m02-a01-lesson-scheduling', 'root-08-m02-scheduling-resource-governance', 1, 'lesson', 'How the Scheduler Places Pods, and How Governance Shapes It',
'content/root/root-08-kubernetes-storage-scheduling/m02-scheduling-resource-governance/01-lesson-scheduling.md', NULL, NULL, 'manual_marker', 20, 'ready'),
('root-08-m02-a02-knowledge-check', 'root-08-m02-scheduling-resource-governance', 2, 'knowledge_check', 'Knowledge Check: Scheduling & Resource Governance',
'content/root/root-08-kubernetes-storage-scheduling/m02-scheduling-resource-governance/02-knowledge-check.md', NULL, NULL, 'manual_marker', 5, 'ready'),
('root-08-m02-a03-lab-node-label-selector', 'root-08-m02-scheduling-resource-governance', 3, 'lab', 'Lab: Node Labels and nodeSelector', NULL, 'node-label-selector', NULL, 'auto_scenario', 15, 'ready'),
('root-08-m02-a04-lab-node-taint-toleration', 'root-08-m02-scheduling-resource-governance', 4, 'lab', 'Lab: Taints and Tolerations', NULL, 'node-taint-toleration', NULL, 'auto_scenario', 20, 'ready'),
('root-08-m02-a05-lab-pod-affinity', 'root-08-m02-scheduling-resource-governance', 5, 'lab', 'Lab: Pod Affinity vs Anti-Affinity', NULL, 'pod-affinity-mcq', NULL, 'auto_scenario', 20, 'ready'),
('root-08-m02-a06-lab-priority-class', 'root-08-m02-scheduling-resource-governance', 6, 'lab', 'Lab: Pod Priority and PriorityClass', NULL, 'priority-class-task', NULL, 'auto_scenario', 20, 'ready'),
('root-08-m02-a07-lab-pdb', 'root-08-m02-scheduling-resource-governance', 7, 'lab', 'Lab: Configure a PodDisruptionBudget', NULL, 'pod-disruption-budget-task', NULL, 'auto_scenario', 20, 'ready'),
('root-08-m02-a08-lab-resource-quota', 'root-08-m02-scheduling-resource-governance', 8, 'lab', 'Lab: ResourceQuota for a Namespace', NULL, 'resource-quota-ns', NULL, 'auto_scenario', 20, 'ready'),
('root-08-m02-a09-lab-limitrange', 'root-08-m02-scheduling-resource-governance', 9, 'lab', 'Lab: LimitRange for Default Container Limits', NULL, 'limitrange-task', NULL, 'auto_scenario', 20, 'ready')
ON CONFLICT (activity_id) DO NOTHING;
-- ROOT 09 m01 — 8 activities (READY: full gold-standard sequence + independent/guided/advanced practice)
INSERT INTO module_activities (activity_id, module_id, sequence, activity_type, title, content_path, scenario_id, assessment_definition_id, completion_behavior, estimated_duration_minutes, status) VALUES
('root-09-m01-a01-lesson-security-model', 'root-09-m01-security-model-and-securitycontext', 1, 'lesson', 'Defense in Depth & the Kubernetes Security Model',
'content/root/root-09-kubernetes-security/m01-security-model-and-securitycontext/01-lesson-security-model.md', NULL, NULL, 'manual_marker', 15, 'ready'),
('root-09-m01-a02-demonstration-securitycontext', 'root-09-m01-security-model-and-securitycontext', 2, 'demonstration', 'Demonstration: A Pod Before and After Hardening',
'content/root/root-09-kubernetes-security/m01-security-model-and-securitycontext/02-demonstration-securitycontext.md', NULL, NULL, 'manual_marker', 10, 'ready'),
('root-09-m01-a03-knowledge-check', 'root-09-m01-security-model-and-securitycontext', 3, 'knowledge_check', 'Knowledge Check: Security Model & SecurityContext',
'content/root/root-09-kubernetes-security/m01-security-model-and-securitycontext/03-knowledge-check.md', NULL, NULL, 'manual_marker', 5, 'ready'),
('root-09-m01-a04-guided-exercise-hardening-plan', 'root-09-m01-security-model-and-securitycontext', 4, 'guided_exercise', 'Guided Exercise: Planning a Pod Hardening Checklist',
'content/root/root-09-kubernetes-security/m01-security-model-and-securitycontext/04-guided-exercise-hardening-plan.md', NULL, NULL, 'manual_marker', 15, 'ready'),
('root-09-m01-a05-lab-non-root', 'root-09-m01-security-model-and-securitycontext', 5, 'lab', 'Lab: Enforce Non-Root Container', NULL, 'cks-non-root-enforce', NULL, 'auto_scenario', 20, 'ready'),
('root-09-m01-a06-lab-drop-capabilities', 'root-09-m01-security-model-and-securitycontext', 6, 'lab', 'Lab: Drop Linux Capabilities', NULL, 'cks-drop-capabilities', NULL, 'auto_scenario', 20, 'ready'),
('root-09-m01-a07-lab-readonly-filesystem', 'root-09-m01-security-model-and-securitycontext', 7, 'lab', 'Lab: Read-Only Root Filesystem', NULL, 'cks-readonly-filesystem', NULL, 'auto_scenario', 15, 'ready'),
('root-09-m01-a08-lab-pod-security-context', 'root-09-m01-security-model-and-securitycontext', 8, 'lab', 'Lab: Pod Security Context (CKS)', NULL, 'cks-pod-security-context', NULL, 'auto_scenario', 20, 'ready'),
('root-09-m01-a09-reflection', 'root-09-m01-security-model-and-securitycontext', 9, 'reflection', 'Reflection: Least Privilege Is a Default, Not an Afterthought',
'content/root/root-09-kubernetes-security/m01-security-model-and-securitycontext/09-reflection.md', NULL, NULL, 'manual_marker', 10, 'ready'),
('root-09-m01-a10-lab-seccomp-guided', 'root-09-m01-security-model-and-securitycontext', 10, 'lab', 'Lab: Seccomp Profiles (guided practice)', NULL, 'cks-seccomp-profile', NULL, 'auto_scenario', 30, 'ready'),
('root-09-m01-a11-lab-apparmor-advanced', 'root-09-m01-security-model-and-securitycontext', 11, 'lab', 'Lab: AppArmor Profiles (advanced/optional)', NULL, 'cks-apparmor-profile', NULL, 'auto_scenario', 30, 'ready'),
('root-09-m01-a12-lab-pod-security-context-independent', 'root-09-m01-security-model-and-securitycontext', 12, 'lab', 'Lab: Pod Security Context (independent practice)', NULL, 'pod-security-context', NULL, 'auto_scenario', 20, 'ready')
ON CONFLICT (activity_id) DO NOTHING;
-- ROOT 09 m02 — 6 activities (PARTIAL: lesson + KC + core labs + one independent-practice dup)
INSERT INTO module_activities (activity_id, module_id, sequence, activity_type, title, content_path, scenario_id, assessment_definition_id, completion_behavior, estimated_duration_minutes, status) VALUES
('root-09-m02-a01-lesson-serviceaccounts-rbac', 'root-09-m02-serviceaccounts-and-rbac', 1, 'lesson', 'Identity for Workloads: ServiceAccounts & RBAC',
'content/root/root-09-kubernetes-security/m02-serviceaccounts-and-rbac/01-lesson-serviceaccounts-rbac.md', NULL, NULL, 'manual_marker', 15, 'ready'),
('root-09-m02-a02-knowledge-check', 'root-09-m02-serviceaccounts-and-rbac', 2, 'knowledge_check', 'Knowledge Check: ServiceAccounts & RBAC',
'content/root/root-09-kubernetes-security/m02-serviceaccounts-and-rbac/02-knowledge-check.md', NULL, NULL, 'manual_marker', 5, 'ready'),
('root-09-m02-a03-lab-serviceaccount-pod', 'root-09-m02-serviceaccounts-and-rbac', 3, 'lab', 'Lab: ServiceAccount for Pod API Access', NULL, 'serviceaccount-pod', NULL, 'auto_scenario', 20, 'ready'),
('root-09-m02-a04-lab-automount-token', 'root-09-m02-serviceaccounts-and-rbac', 4, 'lab', 'Lab: Disable ServiceAccount Token', NULL, 'cks-automount-token', NULL, 'auto_scenario', 15, 'ready'),
('root-09-m02-a05-lab-rbac-role', 'root-09-m02-serviceaccounts-and-rbac', 5, 'lab', 'Lab: RBAC — Create Role and RoleBinding', NULL, 'rbac-role', NULL, 'auto_scenario', 30, 'ready'),
('root-09-m02-a06-lab-rbac-clusterrole', 'root-09-m02-serviceaccounts-and-rbac', 6, 'lab', 'Lab: Cluster-Level RBAC (CKS)', NULL, 'cks-rbac-clusterrole', NULL, 'auto_scenario', 20, 'ready'),
('root-09-m02-a07-lab-rbac-least-privilege', 'root-09-m02-serviceaccounts-and-rbac', 7, 'lab', 'Lab: RBAC Least Privilege', NULL, 'cks-rbac-least-privilege', NULL, 'auto_scenario', 20, 'ready'),
('root-09-m02-a08-lab-rbac-clusterrole-independent', 'root-09-m02-serviceaccounts-and-rbac', 8, 'lab', 'Lab: ClusterRole and ClusterRoleBinding (independent practice)', NULL, 'rbac-clusterrole', NULL, 'auto_scenario', 20, 'ready')
ON CONFLICT (activity_id) DO NOTHING;
-- ROOT 09 m03 — 6 activities (PARTIAL)
INSERT INTO module_activities (activity_id, module_id, sequence, activity_type, title, content_path, scenario_id, assessment_definition_id, completion_behavior, estimated_duration_minutes, status) VALUES
('root-09-m03-a01-lesson-network-supplychain', 'root-09-m03-network-and-supplychain-security', 1, 'lesson', 'NetworkPolicy as a Security Control & Supply Chain Trust',
'content/root/root-09-kubernetes-security/m03-network-and-supplychain-security/01-lesson-network-supplychain.md', NULL, NULL, 'manual_marker', 15, 'ready'),
('root-09-m03-a02-knowledge-check', 'root-09-m03-network-and-supplychain-security', 2, 'knowledge_check', 'Knowledge Check: Network & Supply Chain Security',
'content/root/root-09-kubernetes-security/m03-network-and-supplychain-security/02-knowledge-check.md', NULL, NULL, 'manual_marker', 5, 'ready'),
('root-09-m03-a03-lab-default-deny', 'root-09-m03-network-and-supplychain-security', 3, 'lab', 'Lab: Default Deny Network Policy', NULL, 'cks-network-policy', NULL, 'auto_scenario', 20, 'ready'),
('root-09-m03-a04-lab-egress-namespace', 'root-09-m03-network-and-supplychain-security', 4, 'lab', 'Lab: Restrict Egress to Namespace', NULL, 'cks-egress-namespace', NULL, 'auto_scenario', 30, 'ready'),
('root-09-m03-a05-lab-egress-networkpolicy-guided', 'root-09-m03-network-and-supplychain-security', 5, 'lab', 'Lab: Egress NetworkPolicy (guided practice)', NULL, 'networkpolicy-egress', NULL, 'auto_scenario', 30, 'ready'),
('root-09-m03-a06-lab-tls-ingress', 'root-09-m03-network-and-supplychain-security', 6, 'lab', 'Lab: Secure Ingress with TLS', NULL, 'cks-tls-ingress', NULL, 'auto_scenario', 30, 'ready'),
('root-09-m03-a07-lab-image-pull-secret', 'root-09-m03-network-and-supplychain-security', 7, 'lab', 'Lab: Private Registry Image Pull Secret', NULL, 'cks-image-pull-secret', NULL, 'auto_scenario', 15, 'ready'),
('root-09-m03-a08-lab-network-policy-metadata-advanced', 'root-09-m03-network-and-supplychain-security', 8, 'lab', 'Lab: Block Cloud Metadata (advanced/optional)', NULL, 'cks-network-policy-metadata', NULL, 'auto_scenario', 30, 'ready')
ON CONFLICT (activity_id) DO NOTHING;
-- ROOT 09 m04 — 4 activities (PARTIAL: survey-level, deliberately lighter)
INSERT INTO module_activities (activity_id, module_id, sequence, activity_type, title, content_path, scenario_id, assessment_definition_id, completion_behavior, estimated_duration_minutes, status) VALUES
('root-09-m04-a01-lesson-cluster-hardening', 'root-09-m04-cluster-hardening-and-runtime', 1, 'lesson', 'Pod Security Admission & a Survey of Runtime Hardening',
'content/root/root-09-kubernetes-security/m04-cluster-hardening-and-runtime/01-lesson-cluster-hardening.md', NULL, NULL, 'manual_marker', 15, 'ready'),
('root-09-m04-a02-lab-psa-namespace', 'root-09-m04-cluster-hardening-and-runtime', 2, 'lab', 'Lab: Pod Security Admission', NULL, 'cks-psa-namespace', NULL, 'auto_scenario', 15, 'ready'),
('root-09-m04-a03-lab-immutable-secret', 'root-09-m04-cluster-hardening-and-runtime', 3, 'lab', 'Lab: Immutable Secrets', NULL, 'cks-immutable-secret', NULL, 'auto_scenario', 15, 'ready'),
('root-09-m04-a04-lab-runtime-class-advanced', 'root-09-m04-cluster-hardening-and-runtime', 4, 'lab', 'Lab: RuntimeClass for Sandboxed Workloads (advanced/optional)', NULL, 'cks-runtime-class', NULL, 'auto_scenario', 20, 'ready'),
('root-09-m04-a05-lab-audit-policy-advanced', 'root-09-m04-cluster-hardening-and-runtime', 5, 'lab', 'Lab: Write a Kubernetes Audit Policy (advanced/optional)', NULL, 'cks-audit-policy', NULL, 'auto_scenario', 30, 'ready')
ON CONFLICT (activity_id) DO NOTHING;
-- ROOT 10 m03 — 5 activities (PARTIAL: lesson + demo + KC + two labs)
INSERT INTO module_activities (activity_id, module_id, sequence, activity_type, title, content_path, scenario_id, assessment_definition_id, completion_behavior, estimated_duration_minutes, status) VALUES
('root-10-m03-a01-lesson-framework', 'root-10-m03-troubleshooting-framework', 1, 'lesson', 'The RootNode Troubleshooting Framework',
'content/root/root-10-kubernetes-troubleshooting-observability/m03-troubleshooting-framework/01-lesson-framework.md', NULL, NULL, 'manual_marker', 15, 'ready'),
('root-10-m03-a02-demonstration-crashloop', 'root-10-m03-troubleshooting-framework', 2, 'demonstration', 'Demonstration: Applying the Framework to a CrashLoopBackOff',
'content/root/root-10-kubernetes-troubleshooting-observability/m03-troubleshooting-framework/02-demonstration-crashloop.md', NULL, NULL, 'manual_marker', 10, 'ready'),
('root-10-m03-a03-knowledge-check', 'root-10-m03-troubleshooting-framework', 3, 'knowledge_check', 'Knowledge Check: The Troubleshooting Framework',
'content/root/root-10-kubernetes-troubleshooting-observability/m03-troubleshooting-framework/03-knowledge-check.md', NULL, NULL, 'manual_marker', 5, 'ready'),
('root-10-m03-a04-lab-crashloop-fix', 'root-10-m03-troubleshooting-framework', 4, 'lab', 'Lab: Fix a CrashLoopBackOff Pod', NULL, 'crashloop-fix', NULL, 'auto_scenario', 20, 'ready'),
('root-10-m03-a05-lab-endpoint-fix', 'root-10-m03-troubleshooting-framework', 5, 'lab', 'Lab: Fix a Broken Service Selector', NULL, 'endpoint-fix-task', NULL, 'auto_scenario', 20, 'ready')
ON CONFLICT (activity_id) DO NOTHING;
-- ROOT 10 m02 (existing bare bank) — extend with the newly-wired logging/monitoring MCQ
INSERT INTO module_activities (activity_id, module_id, sequence, activity_type, title, content_path, scenario_id, assessment_definition_id, completion_behavior, estimated_duration_minutes, status) VALUES
('root-10-m02-a06-container-logging-mcq', 'root-10-m02-general-troubleshooting', 6, 'lab', 'Lab: Container Logging and Monitoring', NULL, 'container-logging-mcq', NULL, 'auto_scenario', 15, 'ready')
ON CONFLICT (activity_id) DO NOTHING;
-- ROOT 12 m01 — a new framework lesson at the FRONT (existing 4 lab activities renumbered
-- +1 to make room; their scenario_id/activity_type/completion_behavior are untouched, so no
-- student's derived completion changes meaning) plus a closing reflection.
UPDATE module_activities SET sequence = sequence + 1, version = version + 1, updated_at = now()
WHERE module_id = 'root-12-m01-real-ops-incidents';
INSERT INTO module_activities (activity_id, module_id, sequence, activity_type, title, content_path, scenario_id, assessment_definition_id, completion_behavior, estimated_duration_minutes, status) VALUES
('root-12-m01-a00-lesson-incident-response', 'root-12-m01-real-ops-incidents', 1, 'lesson', 'The RootNode Incident-Response Framework',
'content/root/root-12-real-ops/m01-real-ops-incidents/00-lesson-incident-response.md', NULL, NULL, 'manual_marker', 15, 'ready'),
('root-12-m01-a99-reflection-post-incident', 'root-12-m01-real-ops-incidents', 6, 'reflection', 'Post-Incident Reflection: What Real Ops Actually Feels Like',
'content/root/root-12-real-ops/m01-real-ops-incidents/99-reflection-post-incident.md', NULL, NULL, 'manual_marker', 10, 'ready')
ON CONFLICT (activity_id) DO NOTHING;
-- Capstone Readiness — 4 activities (READY: informational/orientation, not a lesson-heavy module)
INSERT INTO module_activities (activity_id, module_id, sequence, activity_type, title, content_path, scenario_id, assessment_definition_id, completion_behavior, estimated_duration_minutes, status) VALUES
('root-capstone-m02-a01-lesson-what-it-measures', 'root-capstone-m02-capstone-readiness', 1, 'lesson', 'What the Capstone Measures & How the Draw Works',
'content/root/root-capstone/m02-capstone-readiness/01-lesson-what-it-measures.md', NULL, NULL, 'manual_marker', 10, 'ready'),
('root-capstone-m02-a02-lesson-time-management', 'root-capstone-m02-capstone-readiness', 2, 'lesson', 'Time Management & Troubleshooting Strategy Under a Clock',
'content/root/root-capstone/m02-capstone-readiness/02-lesson-time-management.md', NULL, NULL, 'manual_marker', 10, 'ready'),
('root-capstone-m02-a03-knowledge-check', 'root-capstone-m02-capstone-readiness', 3, 'knowledge_check', 'Readiness Check: Are You Actually Ready?',
'content/root/root-capstone/m02-capstone-readiness/03-knowledge-check.md', NULL, NULL, 'manual_marker', 5, 'ready'),
('root-capstone-m02-a04-reflection-readiness', 'root-capstone-m02-capstone-readiness', 4, 'reflection', 'Readiness Reflection: What Completion Means',
'content/root/root-capstone/m02-capstone-readiness/04-reflection-readiness.md', NULL, NULL, 'manual_marker', 5, 'ready')
ON CONFLICT (activity_id) DO NOTHING;
-- ── Optional activities: guided/independent-practice duplicates and advanced/CKS-exam-style
-- extras (docs/ROOT_CURRICULUM_COVERAGE_MATRIX.md's GUIDED/INDEPENDENT/ADVANCED
-- classifications) count toward a module's displayed progress but not toward whether the
-- module itself is considered complete — see course-progress.js's totals(). Everything not
-- listed here stays required (the column's default), including every Phase 6A activity.
UPDATE module_activities SET is_required = false, version = version + 1, updated_at = now() WHERE activity_id IN (
'root-09-m01-a10-lab-seccomp-guided',
'root-09-m01-a11-lab-apparmor-advanced',
'root-09-m01-a12-lab-pod-security-context-independent',
'root-09-m02-a08-lab-rbac-clusterrole-independent',
'root-09-m03-a05-lab-egress-networkpolicy-guided',
'root-09-m03-a08-lab-network-policy-metadata-advanced',
'root-09-m04-a04-lab-runtime-class-advanced',
'root-09-m04-a05-lab-audit-policy-advanced'
);
+12 -1
View File
@@ -55,16 +55,27 @@ function shapeActivity(activity, ctx, forInstructor) {
scenario_id: activity.scenario_id,
assessment_definition_id: activity.assessment_definition_id,
completion_behavior: activity.completion_behavior,
is_required: activity.is_required,
complete: isActivityComplete(activity, ctx),
body: content?.shared || null,
...(forInstructor ? { instructor_notes: content?.instructorNotes || null } : {}),
};
}
// Phase 6B §18/§27 — an optional activity (independent-practice duplicates, advanced/CKS-exam-
// style extras) counts toward the displayed total/percent but NOT toward whether the module
// itself is "complete." Every Phase 6A activity has is_required=true (the column's default,
// unaffected by this), so this is purely additive — nothing that was complete before becomes
// incomplete now.
function totals(items) {
const total = items.length;
const completed = items.filter((i) => i.complete).length;
return { total, completed, pct: total ? Math.round((completed / total) * 100) : 0, complete: total > 0 && completed === total };
const required = items.filter((i) => i.is_required !== false);
const requiredComplete = required.filter((i) => i.complete).length;
return {
total, completed, pct: total ? Math.round((completed / total) * 100) : 0,
complete: required.length > 0 && requiredComplete === required.length,
};
}
// A prerequisite with zero content (a PLANNED module/course with nothing built yet) can never
+25
View File
@@ -156,6 +156,31 @@ module.exports = function registerLearningRoutes(app, deps) {
);
const definition = rows[0];
if (!definition) return res.status(404).json({ error: 'not_found' });
// Phase 6B §10 — a known Phase 3B gap, documented in docs/PHASE6A_ROOT_COURSE_FOUNDATION.md
// §10: this route only ever checked the definition existed/was active. GET /api/capstone
// computes and displays lock state correctly and the UI never exposes a "start" action while
// locked, but student UI state is not the enforcement boundary — a direct POST here could
// start a capstone session before its prerequisite stages were actually complete. Fixed by
// binding to the SAME gate /api/capstone already derives from the curriculum path's own
// capstone stage (computeCurriculumState), rather than re-parsing definition.unlock_rule
// independently — one computation of "is the capstone unlocked," not two that could drift.
// Only a definition the path actually names as ITS capstone is gated this way; an ordinary
// exam (no capstone stage names it) is unaffected — see e2e-phase6b.js for both cases.
const path = curriculum.loadCurriculumPath();
const capstoneStage = path?.stages.find((s) => s.type === 'capstone' && s.capstone_assessment_id === definition.assessment_definition_id);
if (capstoneStage) {
const progress = await loadProgress(pool, req.studentId);
const capstoneAchievement = await getCapstoneAchievement(pool, req.studentId);
const state = computeCurriculumState(path, progress, capstoneAchievement ? 'completed' : undefined);
if (state.capstone?.status === 'locked') {
return res.status(403).json({
error: 'locked', message: 'Complete the required stages before starting this assessment.',
blocking_stage_ids: state.capstone.blocking_stage_ids,
});
}
}
const cohortId = await studentCohortId(pool, req.studentId);
try {
const session = await assessmentsLib.startSession(pool, { definition, studentId: req.studentId, cohortId });
+8 -1
View File
@@ -38,7 +38,14 @@ const WORKLOADS = ['deploy-nginx', 'scale-deployment', 'rolling-update-task', 'l
const NETWORKING = ['services-mcq', 'expose-service-basics'];
const CONFIGURATION = ['configmap-volume', 'resource-limits-task', 'env-vars-configmap', 'secrets-basics', 'pod-env-vars-inline'];
const TROUBLESHOOTING = ['extract-logs-basics', 'kubectl-cp-basics', 'exec-command-basics', 'node-cordon-basics', 'pod-node-assignment-mcq'];
const ALL_NON_CAPSTONE = [...FOUNDATION, ...WORKLOADS, ...NETWORKING, ...CONFIGURATION, ...TROUBLESHOOTING];
// Phase 6B §10 — REAL_OPS was missing from this list entirely, which this test never noticed
// because POST /api/assessments/:id/start didn't check the capstone's unlock_rule server-side
// before Phase 6B's fix (docs/PHASE6A_ROOT_COURSE_FOUNDATION.md §10). Now that the fix actually
// enforces "all 6 stages complete," a genuine capstone attempt needs all 6, real-ops included —
// completing only 5 of 6 is not a legitimately-unlocked capstone and should not (and now does
// not) be accepted. Found by testing.
const REAL_OPS = ['rootnode-runaway-monitor', 'broken-deployment', 'rootnode-probe-port-mismatch', 'rootnode-enforce-limits'];
const ALL_NON_CAPSTONE = [...FOUNDATION, ...WORKLOADS, ...NETWORKING, ...CONFIGURATION, ...TROUBLESHOOTING, ...REAL_OPS];
let passed = 0, failed = 0;
async function test(name, fn) {
+17 -5
View File
@@ -128,8 +128,10 @@ async function main() {
await test('resume points at the first activity of the first unlocked course', async () => {
const { body } = await casey.request('GET', `/api/student/programs/${enrollmentId}/courses`);
assert.equal(body.resume.course_id, 'root-05-kubernetes-foundations');
assert.equal(body.resume.module_id, 'root-05-m01-pods-and-kubectl-basics');
assert.equal(body.resume.activity_id, 'root-05-m01-pods-and-kubectl-basics-a01-pod-basics-mcq');
// Phase 6B added root-05-m00 (the mental-model module) as the new front door, sequenced
// before the pre-existing bare-lab bank — see docs/PHASE6B_ROOT_CURRICULUM_EXPANSION.md.
assert.equal(body.resume.module_id, 'root-05-m00-kubernetes-mental-model');
assert.equal(body.resume.activity_id, 'root-05-m00-a01-lesson-mental-model');
});
await test('a student cannot mark a lab activity complete manually — only real scenario completion counts', async () => {
@@ -138,8 +140,15 @@ async function main() {
assert.equal(body.error, 'not_manually_completable');
});
await test('completing root-05\'s 20 real scenarios marks the course complete and unlocks root-06', async () => {
await test('completing root-05\'s 20 real scenarios + the Phase 6B mental-model module marks the course complete and unlocks root-06', async () => {
for (const sid of FOUNDATION) await completeScenario(casey, sid);
// Phase 6B's root-05-m00 has its own manual-marker activities (lesson/demonstration/
// knowledge_check/guided_exercise/reflection) that scenario completion alone never
// satisfies — root-05 the COURSE isn't complete until these are marked too.
for (const suffix of ['a01-lesson-mental-model', 'a02-demonstration-desired-state', 'a03-knowledge-check', 'a04-guided-exercise-namespaces', 'a06-reflection']) {
const { status } = await casey.request('POST', `/api/student/activities/root-05-m00-${suffix}/complete`);
assert.equal(status, 200);
}
const { body } = await casey.request('GET', `/api/student/programs/${enrollmentId}/courses`);
const root05 = courseById(body.courses, 'root-05-kubernetes-foundations');
assert.equal(root05.complete, true);
@@ -180,8 +189,11 @@ async function main() {
const goldModule = moduleById(body.courses, 'root-10-m01-health-probes-and-troubleshooting');
assert.equal(goldModule.complete, true);
assert.equal(goldModule.percent_complete, 100);
const nextModule = moduleById(body.courses, 'root-10-m02-general-troubleshooting');
assert.equal(nextModule.locked, false, 'root-10-m02 must unlock once the gold module is complete');
// Phase 6B inserted root-10-m03 (the troubleshooting framework module) between the gold
// module and the pre-existing bare-lab bank — m02's prerequisite is now m03, not m01
// directly. See docs/PHASE6B_ROOT_CURRICULUM_EXPANSION.md.
const frameworkModule = moduleById(body.courses, 'root-10-m03-troubleshooting-framework');
assert.equal(frameworkModule.locked, false, 'root-10-m03 must unlock once the gold module is complete');
});
// ── Assessment/capstone-derived completion (auto_assessment) ────────────────────────────
+326
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@@ -0,0 +1,326 @@
#!/usr/bin/env node
// Phase 6B — ROOT_ curriculum authoring & coverage expansion acceptance test. Covers the NEW
// courses/modules/content this phase added (ROOT 05-10/12/Capstone), the two genuinely new
// mechanisms it introduced (is_required optional-activity handling, and the capstone
// server-side unlock fix), and confirms the underlying Phase 6A engine (completion derivation,
// locking, RBAC, isolation, persistence, draft-hiding) generalizes correctly to the new content
// rather than re-proving every property from scratch against every module (already proven once,
// thoroughly, in e2e-phase6a.js — see that file for the exhaustive per-mechanism coverage).
// Same conventions: assert-based, no framework, live docker-compose.dev.yml stack, no real Lab
// container launched here (infra/scripts/drills/test-phase6b-root-course-rehearsal.js is the
// real-k3s counterpart).
//
// Usage: cd platform && docker compose -f docker-compose.dev.yml up -d
// (cd api && PLATFORM_DB_URL=... node bootstrap-owner.js OWNER_EMAIL "Owner" OWNER_PASSWORD)
// OWNER_EMAIL=... OWNER_PASSWORD=... node test/e2e-phase6b.js
const assert = require('assert');
const { execSync } = require('child_process');
const { makeSession } = require('./session-helper');
const GW = process.env.GATEWAY_URL || 'http://localhost:4200';
const OWNER_EMAIL = process.env.OWNER_EMAIL;
const OWNER_PASSWORD = process.env.OWNER_PASSWORD;
if (!OWNER_EMAIL || !OWNER_PASSWORD) {
console.error('Set OWNER_EMAIL and OWNER_PASSWORD (bootstrap one first with platform/api/bootstrap-owner.js)');
process.exit(1);
}
const RUN_ID = Date.now();
const PROGRAM = 'root-kubernetes-foundations';
// The real ROOT 05 Foundation scenarios (m00 + m01) — completing all of these is what actually
// unlocks ROOT 06 at the course level (courses.prerequisites), same real content
// e2e-phase6a.js/e2e-phase5b.js already drive completion against.
const ROOT05_ALL = ['namespaces-basics', 'pod-basics-mcq', 'kubectl-essentials-mcq', 'labels-selectors-mcq', 'init-containers-mcq',
'multi-container-pod-basics', 'pod-labeling-basics', 'jsonpath-basics', 'dry-run-manifest-basics', 'delete-by-label-basics',
'annotate-resource-basics', 'init-container-task-basics', 'restart-policy-mcq', 'kubectl-output-format-mcq',
'kubectl-explain-basics', 'kubectl-patch-basics', 'field-selector-basics', 'sort-by-basics', 'kubectl-diff-basics', 'static-pods-mcq'];
let passed = 0, failed = 0;
async function test(name, fn) {
try { await fn(); console.log(` ok — ${name}`); passed++; }
catch (e) { console.error(` FAIL — ${name}\n ${e.message}`); failed++; }
}
async function completeScenario(session, scenarioId) {
const { status } = await session.request('POST', '/api/progress/record', { scenario_id: scenarioId, status: 'completed' });
assert.equal(status, 200, `completing ${scenarioId} should 200`);
}
function courseById(courses, id) { return courses.find((c) => c.course_id === id); }
function moduleById(courses, id) { for (const c of courses) { const m = c.modules.find((x) => x.module_id === id); if (m) return m; } return null; }
function findActivity(courses, id) {
for (const c of courses) for (const m of c.modules) { const a = m.activities.find((x) => x.activity_id === id); if (a) return a; }
return null;
}
function psql(sql) {
return execSync(`docker compose -f docker-compose.dev.yml exec -T postgres psql -U postgres -d rootnode_platform -t -c "${sql}"`, { cwd: `${__dirname}/..`, stdio: 'pipe' }).toString().trim();
}
async function main() {
console.log('Phase 6B ROOT_ curriculum expansion acceptance test\n');
const owner = makeSession(GW);
await owner.request('POST', '/api/auth/instructor/login', { email: OWNER_EMAIL, password: OWNER_PASSWORD });
// ── 1-8: hierarchy for every course this phase touched ──────────────────────────────────
let structure;
await test('ROOT 05-10, 12, and Capstone all have the expected new modules, in sequence', async () => {
const { status, body } = await owner.request('GET', `/api/admin/programs/${PROGRAM}/courses`);
assert.equal(status, 200);
structure = body;
const expectations = {
'root-05-kubernetes-foundations': ['root-05-m00-kubernetes-mental-model', 'root-05-m01-pods-and-kubectl-basics'],
'root-06-kubernetes-application-workloads': ['root-06-m02-deployments-scaling-updates', 'root-06-m03-jobs-cronjobs-daemonsets', 'root-06-m01-deployments-and-workloads'],
'root-07-kubernetes-networking-config': ['root-07-m03-services-and-service-discovery', 'root-07-m04-ingress-networkpolicy-foundations', 'root-07-m01-services-and-networking', 'root-07-m02-configuration-and-secrets'],
'root-08-kubernetes-storage-scheduling': ['root-08-m01-storage-fundamentals', 'root-08-m02-scheduling-resource-governance'],
'root-09-kubernetes-security': ['root-09-m01-security-model-and-securitycontext', 'root-09-m02-serviceaccounts-and-rbac', 'root-09-m03-network-and-supplychain-security', 'root-09-m04-cluster-hardening-and-runtime'],
'root-10-kubernetes-troubleshooting-observability': ['root-10-m01-health-probes-and-troubleshooting', 'root-10-m03-troubleshooting-framework', 'root-10-m02-general-troubleshooting'],
'root-12-real-ops': ['root-12-m01-real-ops-incidents'],
'root-capstone': ['root-capstone-m02-capstone-readiness', 'root-capstone-m01-operate-and-recover'],
};
for (const [courseId, moduleIds] of Object.entries(expectations)) {
const course = courseById(structure, courseId);
assert.ok(course, `${courseId} must exist`);
const actualIds = course.modules.map((m) => m.module_id);
assert.deepEqual(actualIds, moduleIds, `${courseId} module order mismatch: ${JSON.stringify(actualIds)}`);
}
});
await test('ROOT 08 and ROOT 09 moved from PLANNED to PARTIAL — real content exists now', async () => {
assert.equal(courseById(structure, 'root-08-kubernetes-storage-scheduling').status, 'partial');
assert.equal(courseById(structure, 'root-09-kubernetes-security').status, 'partial');
});
await test('the gold-standard Health Probes module is byte-for-byte unchanged (still 6 activities, still READY)', async () => {
const gold = moduleById(structure, 'root-10-m01-health-probes-and-troubleshooting');
assert.equal(gold.status, 'ready');
assert.equal(gold.activities.length, 6);
});
await test('activity ordering within every new module is strictly ascending', async () => {
for (const newModuleId of ['root-05-m00-kubernetes-mental-model', 'root-06-m02-deployments-scaling-updates', 'root-07-m03-services-and-service-discovery', 'root-09-m01-security-model-and-securitycontext']) {
const mod = moduleById(structure, newModuleId);
for (let i = 1; i < mod.activities.length; i++) assert.ok(mod.activities[i].sequence > mod.activities[i - 1].sequence, `${newModuleId} activity ordering broken`);
}
});
await test('ROOT 12\'s new framework lesson is first and the new reflection is last, existing labs preserved in between', async () => {
const mod = moduleById(structure, 'root-12-m01-real-ops-incidents');
const types = mod.activities.map((a) => a.activity_type);
assert.deepEqual(types, ['lesson', 'lab', 'lab', 'lab', 'lab', 'reflection']);
const scenarioIds = mod.activities.filter((a) => a.activity_type === 'lab').map((a) => a.scenario_id);
assert.deepEqual(scenarioIds, ['rootnode-runaway-monitor', 'broken-deployment', 'rootnode-probe-port-mismatch', 'rootnode-enforce-limits']);
});
// ── A real self-paced student walking the new content ───────────────────────────────────
const { body: caseyCreate } = await owner.request('POST', '/api/admin/students', { display_name: `E2E-6B-Casey-${RUN_ID}`, login_identifier: `e2e6b-casey-${RUN_ID}` });
let casey = makeSession(GW);
await casey.request('POST', '/api/student/activate', { token: caseyCreate.activation_token, password: 'CaseyPassword123!' });
const { body: enrollCreate } = await owner.request('POST', '/api/admin/enrollments', { student_id: caseyCreate.student_id, program_id: PROGRAM, status: 'active' });
const enrollmentId = enrollCreate.enrollment_id;
await test('ROOT 06/09/10-framework are locked for a freshly-enrolled student', async () => {
const { body } = await casey.request('GET', `/api/student/programs/${enrollmentId}/courses`);
assert.equal(courseById(body.courses, 'root-06-kubernetes-application-workloads').locked, true);
assert.equal(moduleById(body.courses, 'root-09-m01-security-model-and-securitycontext').locked, true);
assert.equal(moduleById(body.courses, 'root-10-m03-troubleshooting-framework').locked, true, 'must stay locked behind the gold module even though it is a different course-level dependency chain');
});
await test('resume points at ROOT 05\'s new mental-model module, not the old bare-lab bank', async () => {
const { body } = await casey.request('GET', `/api/student/programs/${enrollmentId}/courses`);
assert.equal(body.resume.module_id, 'root-05-m00-kubernetes-mental-model');
});
await test('lesson/knowledge_check completion works identically in a brand-new module (root-05-m00)', async () => {
for (const suffix of ['a01-lesson-mental-model', 'a02-demonstration-desired-state', 'a03-knowledge-check', 'a04-guided-exercise-namespaces']) {
const { status } = await casey.request('POST', `/api/student/activities/root-05-m00-${suffix}/complete`);
assert.equal(status, 200);
}
await completeScenario(casey, 'namespaces-basics');
const { status } = await casey.request('POST', '/api/student/activities/root-05-m00-a06-reflection/complete');
assert.equal(status, 200);
const { body } = await casey.request('GET', `/api/student/programs/${enrollmentId}/courses`);
assert.equal(moduleById(body.courses, 'root-05-m00-kubernetes-mental-model').complete, true);
});
await test('completing every ROOT 05 scenario (m00 + m01) unlocks ROOT 06 at the course level', async () => {
for (const sid of ROOT05_ALL) await completeScenario(casey, sid);
const { body } = await casey.request('GET', `/api/student/programs/${enrollmentId}/courses`);
assert.equal(courseById(body.courses, 'root-05-kubernetes-foundations').complete, true);
assert.equal(courseById(body.courses, 'root-06-kubernetes-application-workloads').locked, false);
assert.equal(moduleById(body.courses, 'root-06-m01-deployments-and-workloads').locked, true, 'the bare bank stays gated behind the new m02 specifically');
});
await test('a new scenario wired this phase (job-task, never in Phase 6A) completes an activity correctly', async () => {
await completeScenario(casey, 'job-task');
const { body } = await casey.request('GET', `/api/student/programs/${enrollmentId}/courses`);
assert.equal(findActivity(body.courses, 'root-06-m03-a03-lab-job-task').complete, true);
});
// ── is_required: optional activities count toward percent but never block "complete" ────
await test('an optional activity being incomplete does not block its module from being complete', async () => {
// root-09 is still locked for Casey (needs root-06-m02 complete). Prove the is_required
// rule directly against the seeded data instead: root-09-m01 has 12 activities, 3 of which
// (a10/a11/a12) are is_required=false. Confirm the schema/shape is correct via the admin
// structure view (studentId=null, so nothing is actually complete — this is a pure
// structural check of the is_required flag itself).
const mod = moduleById(structure, 'root-09-m01-security-model-and-securitycontext');
const optional = mod.activities.filter((a) => a.is_required === false);
const required = mod.activities.filter((a) => a.is_required !== false);
assert.equal(optional.length, 3, 'expected exactly 3 optional activities in root-09-m01');
assert.equal(required.length, 9);
});
await test('completing every REQUIRED activity in root-09-m01 marks it complete even with optional activities left undone', async () => {
// Unlock root-09 for Casey: complete the rest of root-06 (m02 + m03's remaining scenarios).
for (const sid of ['deploy-nginx', 'scale-deployment', 'rolling-update-task', 'liveness-probe-task', 'jobs-cronjobs-mcq', 'daemonset-mcq', 'edit-deployment-basics', 'deployment-strategy-mcq', 'deployment-rollback']) {
await completeScenario(casey, sid);
}
await completeScenario(casey, 'cronjob-task');
for (const suffix of ['a01-lesson-deployments', 'a02-demonstration-rollout', 'a03-knowledge-check', 'a04-guided-exercise-rollout-strategy']) {
await casey.request('POST', `/api/student/activities/root-06-m02-${suffix}/complete`);
}
await casey.request('POST', '/api/student/activities/root-06-m02-a06-reflection/complete');
for (const suffix of ['a01-lesson-jobs-cronjobs-daemonsets', 'a02-knowledge-check']) {
await casey.request('POST', `/api/student/activities/root-06-m03-${suffix}/complete`);
}
let tree = (await casey.request('GET', `/api/student/programs/${enrollmentId}/courses`)).body.courses;
assert.equal(moduleById(tree, 'root-09-m01-security-model-and-securitycontext').locked, false, 'root-09 should now be unlocked');
// Complete only the REQUIRED activities in root-09-m01, deliberately skipping the 3 optional ones.
for (const suffix of ['a01-lesson-security-model', 'a02-demonstration-securitycontext', 'a03-knowledge-check', 'a04-guided-exercise-hardening-plan']) {
await casey.request('POST', `/api/student/activities/root-09-m01-${suffix}/complete`);
}
for (const sid of ['cks-non-root-enforce', 'cks-drop-capabilities', 'cks-readonly-filesystem', 'cks-pod-security-context']) await completeScenario(casey, sid);
await casey.request('POST', '/api/student/activities/root-09-m01-a09-reflection/complete');
tree = (await casey.request('GET', `/api/student/programs/${enrollmentId}/courses`)).body.courses;
const mod = moduleById(tree, 'root-09-m01-security-model-and-securitycontext');
assert.equal(mod.complete, true, 'module must be complete once all REQUIRED activities are done, regardless of the 3 optional ones');
assert.equal(mod.percent_complete, Math.round((9 / 12) * 100), 'percent_complete must still reflect ALL activities, optional included');
assert.equal(findActivity(tree, 'root-09-m01-a10-lab-seccomp-guided').complete, false, 'the optional activity itself is correctly still incomplete');
});
// ── Persistence, isolation, RBAC, draft-hiding — proven once against NEW content ────────
await test('progress on new content survives logout and a fresh login', async () => {
await casey.request('POST', '/api/logout');
casey = makeSession(GW);
await casey.request('POST', '/api/student/login', { identifier: `e2e6b-casey-${RUN_ID}`, password: 'CaseyPassword123!' });
const { body } = await casey.request('GET', `/api/student/programs/${enrollmentId}/courses`);
assert.equal(moduleById(body.courses, 'root-05-m00-kubernetes-mental-model').complete, true);
});
const { body: isolatedCreate } = await owner.request('POST', '/api/admin/students', { display_name: `E2E-6B-Isolated-${RUN_ID}`, login_identifier: `e2e6b-isolated-${RUN_ID}` });
const isolated = makeSession(GW);
await isolated.request('POST', '/api/student/activate', { token: isolatedCreate.activation_token, password: 'IsolatedPassword123!' });
const { body: isolatedEnroll } = await owner.request('POST', '/api/admin/enrollments', { student_id: isolatedCreate.student_id, program_id: PROGRAM, status: 'active' });
await test('a second student sees independent progress on the new courses (cross-student isolation)', async () => {
const { body } = await isolated.request('GET', `/api/student/programs/${isolatedEnroll.enrollment_id}/courses`);
assert.equal(moduleById(body.courses, 'root-05-m00-kubernetes-mental-model').complete, false);
assert.equal(courseById(body.courses, 'root-06-kubernetes-application-workloads').locked, true);
});
await test('a draft activity in a new module is hidden from students but visible to instructors', async () => {
psql(`UPDATE module_activities SET visibility = 'draft' WHERE activity_id = 'root-08-m01-a01-lesson-storage-fundamentals'`);
try {
const { body: studentView } = await casey.request('GET', `/api/student/programs/${enrollmentId}/courses`);
const mod = moduleById(studentView.courses, 'root-08-m01-storage-fundamentals');
assert.ok(!mod.activities.some((a) => a.activity_id === 'root-08-m01-a01-lesson-storage-fundamentals'));
const { body: adminView } = await owner.request('GET', `/api/admin/programs/${PROGRAM}/courses`);
const modAdmin = moduleById(adminView, 'root-08-m01-storage-fundamentals');
assert.ok(modAdmin.activities.some((a) => a.activity_id === 'root-08-m01-a01-lesson-storage-fundamentals'));
} finally {
psql(`UPDATE module_activities SET visibility = 'published' WHERE activity_id = 'root-08-m01-a01-lesson-storage-fundamentals'`);
}
});
await test('instructor notes on new content are visible to instructors and never to students', async () => {
const { body: adminView } = await owner.request('GET', `/api/admin/programs/${PROGRAM}/courses`);
const lesson = findActivity(adminView, 'root-09-m01-a01-lesson-security-model');
assert.ok(lesson.instructor_notes && lesson.instructor_notes.includes('Instructor Notes'));
const { body: studentView } = await casey.request('GET', `/api/student/programs/${enrollmentId}/courses`);
const studentLesson = findActivity(studentView.courses, 'root-09-m01-a01-lesson-security-model');
assert.equal(studentLesson.instructor_notes, undefined, 'a student response must never include this key at all');
});
const { body: strayInstructor } = await owner.request('POST', '/api/admin/instructors', { email: `e2e6b-stray-${RUN_ID}@example.com`, display_name: 'Stray Instructor', role: 'instructor', password: 'StrayInstructorPass123!' });
const strayInstructorSession = makeSession(GW);
await strayInstructorSession.request('POST', '/api/auth/instructor/login', { email: `e2e6b-stray-${RUN_ID}@example.com`, password: 'StrayInstructorPass123!' });
await test('a plain instructor with no relationship to the student is forbidden from their new-course progress (self-paced, no cohort)', async () => {
const { status } = await strayInstructorSession.request('GET', `/api/admin/students/${caseyCreate.student_id}/courses?program_id=${PROGRAM}`);
assert.equal(status, 403);
});
await test('owner/admin can see any self-paced student\'s progress on the new courses', async () => {
const { status, body } = await owner.request('GET', `/api/admin/students/${caseyCreate.student_id}/courses?program_id=${PROGRAM}`);
assert.equal(status, 200);
assert.equal(moduleById(body, 'root-05-m00-kubernetes-mental-model').complete, true);
});
// ── Capstone: the server-side unlock fix — the central Phase 6B security fix ───────────
const { body: bypassCreate } = await owner.request('POST', '/api/admin/students', { display_name: `E2E-6B-Bypass-${RUN_ID}`, login_identifier: `e2e6b-bypass-${RUN_ID}` });
const bypass = makeSession(GW);
await bypass.request('POST', '/api/student/activate', { token: bypassCreate.activation_token, password: 'BypassPassword123!' });
const { body: bypassEnroll } = await owner.request('POST', '/api/admin/enrollments', { student_id: bypassCreate.student_id, program_id: PROGRAM, status: 'active' });
await test('direct POST /api/assessments/rootnode-capstone/start is rejected before prerequisites are complete (the fix)', async () => {
const { status, body } = await bypass.request('POST', '/api/assessments/rootnode-capstone/start');
assert.equal(status, 403);
assert.equal(body.error, 'locked');
assert.ok(Array.isArray(body.blocking_stage_ids) && body.blocking_stage_ids.length > 0);
});
await test('an ordinary exam with no unlock_rule is completely unaffected by the fix', async () => {
const { status, body } = await bypass.request('POST', '/api/assessments/rootnode-quick-assessment/start');
assert.equal(status, 201);
assert.ok(body.scenarios.length > 0);
// Clean up the active session so it doesn't block later assertions for this student.
for (const s of body.scenarios) await completeScenario(bypass, s.scenario_id);
});
await test('a legitimately unlocked capstone start is still accepted (the fix does not over-block)', async () => {
const ALL_STAGES = ['pod-basics-mcq', 'kubectl-essentials-mcq', 'labels-selectors-mcq', 'init-containers-mcq', 'namespaces-basics',
'multi-container-pod-basics', 'pod-labeling-basics', 'jsonpath-basics', 'dry-run-manifest-basics', 'delete-by-label-basics',
'annotate-resource-basics', 'init-container-task-basics', 'restart-policy-mcq', 'kubectl-output-format-mcq',
'kubectl-explain-basics', 'kubectl-patch-basics', 'field-selector-basics', 'sort-by-basics', 'kubectl-diff-basics', 'static-pods-mcq',
'deploy-nginx', 'scale-deployment', 'rolling-update-task', 'liveness-probe-task', 'jobs-cronjobs-mcq', 'daemonset-mcq', 'edit-deployment-basics', 'deployment-strategy-mcq',
'services-mcq', 'expose-service-basics',
'configmap-volume', 'resource-limits-task', 'env-vars-configmap', 'secrets-basics', 'pod-env-vars-inline',
'extract-logs-basics', 'kubectl-cp-basics', 'exec-command-basics', 'node-cordon-basics', 'pod-node-assignment-mcq',
'rootnode-runaway-monitor', 'broken-deployment', 'rootnode-probe-port-mismatch', 'rootnode-enforce-limits'];
for (const sid of ALL_STAGES) await completeScenario(bypass, sid);
const { status, body } = await bypass.request('POST', '/api/assessments/rootnode-capstone/start');
assert.equal(status, 201, `expected the now-unlocked capstone to start: ${JSON.stringify(body)}`);
for (const s of body.scenarios) await completeScenario(bypass, s.scenario_id);
const check = await bypass.request('GET', '/api/capstone');
assert.equal(check.body.status, 'completed');
});
await test('the capstone-derived completion is reflected in the course/module content model too', async () => {
const { body } = await bypass.request('GET', `/api/student/programs/${bypassEnroll.enrollment_id}/courses`);
const capstoneActivity = findActivity(body.courses, 'root-capstone-m01-a01-capstone');
assert.equal(capstoneActivity.complete, true);
});
await test('the Capstone Readiness module itself is completable independent of the real assessment', async () => {
const enrollmentIdForCasey = enrollmentId;
for (const suffix of ['a01-lesson-what-it-measures', 'a02-lesson-time-management', 'a03-knowledge-check', 'a04-reflection-readiness']) {
const { status } = await casey.request('POST', `/api/student/activities/root-capstone-m02-${suffix}/complete`);
assert.equal(status, 200);
}
const { body } = await casey.request('GET', `/api/student/programs/${enrollmentIdForCasey}/courses`);
assert.equal(moduleById(body.courses, 'root-capstone-m02-capstone-readiness').complete, true);
});
// ── Content version stability ─────────────────────────────────────────────────────────────
await test('bumping a new module\'s version does not break or drop its content', async () => {
psql(`UPDATE course_modules SET version = version + 1 WHERE module_id = 'root-09-m01-security-model-and-securitycontext'`);
const { body } = await owner.request('GET', `/api/admin/programs/${PROGRAM}/courses`);
const mod = moduleById(body, 'root-09-m01-security-model-and-securitycontext');
assert.equal(mod.activities.length, 12, 'a version bump must never drop activities');
assert.ok(mod.activities[0].body && mod.activities[0].body.length > 300);
});
console.log(`\n${passed} passed, ${failed} failed`);
process.exit(failed ? 1 : 0);
}
main().catch((e) => { console.error('FATAL', e); process.exit(1); });