ced4568andClaude Sonnet 5
60fbf0c385
Pre-Phase-1 platform work, approved and tested earlier but not yet committed: - Terminal banner: "RootNode Academy Lab — node: k8s-lab", upstream KubeKosh attribution left untouched in footer/README/LICENSE. - RootNode curriculum mode: scenarios/rootnode-path.json (Foundation -> Workloads -> Networking -> Configuration -> Troubleshooting -> Real Ops -> Capstone), built from existing scenario content grouped by category, no new scenarios invented. New GET /api/curriculum/path endpoint. - Student roster + per-student progress: instructor-roster, pick-your-name login (no password), students/environments-adjacent progress table migrated to a (student_id, scenario_id) composite key so practice progress and exam sessions are isolated per student instead of one global bucket. New /api/roster, /api/login endpoints. - scenarios/data/*.json: added isolation_type metadata (shared_namespace vs ephemeral_cluster) from an audit of which scenarios execute cluster-scoped or node-level commands. This was Tier-1-isolation groundwork that got superseded same-day by the full-ephemeral-per-student architecture (see docs/LAB_ARCHITECTURE.md) — the field is kept as descriptive metadata only, per the note now in scenarios/SCHEMA.md. Not wasted: it's an accurate audit of which scenarios touch cluster-scoped resources, useful independent of isolation model. - .gitignore added (node_modules/, frontend/dist/, *.db, /data/, .env) — none existed before; without it, npm installs during testing would have landed in a commit. Known limitation still open: no frontend UI for any of this yet (login screen, roster-add form, curriculum view) — API-only. No auth on the roster-add endpoint. Co-Authored-By: Claude Sonnet 5 <[email protected]>
41 lines
1.7 KiB
JSON
41 lines
1.7 KiB
JSON
{
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"id": "daemonset-mcq",
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"title": "Understanding DaemonSets",
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"category": "Workloads",
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"isolation_type": "shared_namespace",
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"difficulty": "Easy",
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"type": "mcq",
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"weight": 3,
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"description": "## Understanding DaemonSets\n\nYour team wants to deploy a **log collector agent** that must run on **every node** in the cluster, including any nodes added in the future.\n\nWhich Kubernetes resource is the best fit?",
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"options": [
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{
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"id": "a",
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"text": "A `Deployment` with `replicas` set to the number of nodes"
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},
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{
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"id": "b",
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"text": "A `StatefulSet` with `replicas` matching the node count"
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},
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{
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"id": "c",
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"text": "A `DaemonSet`, which automatically places one pod per node and adapts as nodes join or leave"
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},
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{
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"id": "d",
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"text": "A `CronJob` that runs `kubectl create pod` on each node every minute"
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}
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],
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"correct_option": "c",
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"explanation": "A **DaemonSet** guarantees that exactly one copy of a pod runs on every (or selected) node. As nodes are added to the cluster, the DaemonSet controller automatically schedules the pod on them; when nodes are removed, the pods are garbage-collected. Classic use cases: log shippers (Fluentd, Filebeat), monitoring agents (Prometheus Node Exporter), and CNI plugins. A Deployment with fixed replicas does NOT guarantee one-pod-per-node coverage.",
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"hints": [
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{
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"title": "When to use a DaemonSet",
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"body": "DaemonSets are ideal for cluster-level infrastructure: log collection, metrics agents, node monitoring, and CNI/CSI plugins that need to run on every node.",
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"command": "kubectl explain daemonset.spec"
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}
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],
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"setup_commands": [],
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"default_namespace": "default",
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"teardown_commands": []
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}
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