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kubernetes-operator

Design, build, and operate Kubernetes operators. Use when extending Kubernetes with a custom controller, choosing a framework, designing CRDs, implementing reconciliation loops, or auditing an operator for anti-patterns.

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含まれるファイル(8)

  • SKILL.md7.2 KB
  • references/controller-runtime-patterns.md23.0 KB
  • references/operator-anti-patterns.md21.7 KB
  • references/operator-decisions-and-workflows.md7.4 KB
  • references/operator-pattern-and-crds.md19.1 KB
  • scripts/crd_validator.py18.3 KB
  • scripts/operator_scaffold.py17.5 KB
  • scripts/reconciliation_audit.py16.3 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Kubernetes Operator

End-to-end Kubernetes operator design and construction. Covers the operator pattern (control loops for stateful workloads), CRD design (schema, validation, conversion, status), the reconciliation loop (idempotency, convergence, level- vs edge-triggered), framework selection (controller-runtime / Kubebuilder / operator-SDK / metacontroller), and operational concerns (finalizers, leader election, RBAC scoping, status subresource, observability). Targets Go-based operators (the dominant ecosystem) with notes on alternatives (KOPF, JOSDK, kube-rs).

Core Capabilities

  • Decide whether to write an operator — operator vs Helm vs GitOps vs admission webhook vs Crossplane, and when NOT to build one at all.
  • CRD design — spec/status separation, OpenAPI v3 structural schemas, CEL cross-field validation, versioning, conversion webhooks, status subresource, printer columns, scale subresource.
  • Reconciliation loops — idempotent, level-triggered, converging control loops; phase machines vs always-converge; owner references and garbage collection.
  • Controller-runtime patterns (Go) — skeleton reconcilers, server-side apply, finalizers, leader election, watches/predicates/indexers, error classification, envtest.
  • Framework selection — controller-runtime, Kubebuilder, operator-SDK, Metacontroller, KOPF, JOSDK, kube-rs.
  • Operational hardening — finalizers, leader election, tightened RBAC, status conditions/observedGeneration, Prometheus metrics + structured logging.
  • Anti-pattern audit — 24-entry catalog with severities, detection heuristics, and fixes for production-readiness review.

When to Use

SituationSkill applies
Building a new operator for an internal platform primitiveYes — start with the operator pattern decision
Auditing an existing operator for production-readinessYes — use anti-patterns + scripts/reconciliation_audit.py
Designing CRDs for a custom resourceYes — use CRD design + scripts/crd_validator.py
Deciding "operator vs Helm chart vs plain manifests"Yes — use the decision matrix
Scaffolding a new operator projectYes — scripts/operator_scaffold.py
Debugging a controller that "isn't reconciling"Yes — use reconciliation troubleshooting
Just running someone else's operator (Postgres, Kafka, etc.)Partially — useful for understanding what it does and how to monitor it

Clarify First

Before scaffolding or auditing, confirm these inputs. If any is unknown or vague, ASK — do not assume:

  • Task — scaffold an operator, validate a CRD, or audit a controller (selects operator_scaffold.py vs crd_validator.py vs reconciliation_audit.py)
  • Resource identity — for scaffolding: the operator name, API group, and kind (sets --name/--group/--kind); for validation/audit: the CRD YAML or controller path (the input the scripts read)
  • Framework — controller-runtime/Kubebuilder/operator-SDK (Go), or KOPF/JOSDK/kube-rs (drives the scaffold patterns)

Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.

Tools

ToolPurposeCommand
crd_validator.pyValidate CRD YAML against design best practices (preserve-unknown, missing descriptions/enums/printer-columns, status subresource, cluster-scope)python3 scripts/crd_validator.py --schema my-crd.yaml --format markdown
operator_scaffold.pyGenerate a production-ready operator project skeleton with stricter RBAC, observability, and finalizer scaffoldingpython3 scripts/operator_scaffold.py --name db-operator --group example.com --kind Database
reconciliation_audit.pyAudit Go controller source + CRDs for static-detectable anti-patterns (missing finalizers, no leader election, tight loops, no ownerRef, wide RBAC)python3 scripts/reconciliation_audit.py --controller-path ./internal/controllers --crd ./config/crd/bases/*.yaml

All scripts: stdlib only, argparse CLI, JSON or markdown output.

References

Load the reference that matches the task — keep this file lean and pull detail on demand:

  • references/operator-pattern-and-crds.md — pattern fundamentals, full CRD schema design (validation, CEL, status patterns), versioning, conversion webhooks, status/scale subresources, printer columns, RBAC, and a production-CRD checklist. Read when designing or reviewing a CRD.
  • references/controller-runtime-patterns.md — Go controller-runtime examples: skeleton reconciler, idempotent apply, owner refs, status updates, finalizers, leader election, watches/predicates/indexers, error handling, RBAC markers, envtest, plus the reconciliation-loop overview and operational concerns. Read when implementing or debugging a controller.
  • references/operator-anti-patterns.md — the full 24-entry anti-pattern catalog with severity, symptoms, consequences, fixes, a static-detection summary, and symptom-based triage. Read during design review, code review, or pre-production audit.
  • references/operator-decisions-and-workflows.md — when NOT to write an operator, operator-vs-alternatives decision matrix, framework selection, the four end-to-end workflows (scaffold / audit / design CRD / upgrade versions), and tooling outputs. Read when deciding the approach or running a workflow.

Scope & Limitations

Covers: operator pattern decisions; CRD design (schema/validation/versioning/conversion/subresources); idempotent reconciliation loops; Go controller-runtime / Kubebuilder / operator-SDK patterns; finalizers, leader election, RBAC scoping, observability; anti-pattern auditing. Primary target is Go operators, with notes on KOPF (Python), JOSDK (Java), kube-rs (Rust).

Does NOT cover: operating third-party community operators beyond understanding/monitoring them; cloud-provider-specific resource provisioning (see Crossplane); general Kubernetes cluster administration.

Integration Points

SkillIntegration
engineering/chaos-engineeringChaos-test operators (kill the controller, partition from API server)
engineering/observability-designerWire metrics + logging for operators
engineering/incident-commanderOperators amplify blast radius; incident response matters more
engineering/feature-flags-architectOperators with spec.feature.<x>.enabled fields effectively become flag systems; consider the trade-off

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

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