Agent-Skills.md

Agent Skills: Kubernetes Operator

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[kubernetesoperator-patterncrdcontroller-runtimekubebuilderplatform-engineeringsre]
engineeringID: borghei/claude-skills/kubernetes-operator

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borghei/claude-skills
borgheiLicense: NOASSERTION
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engineering/kubernetes-operator/SKILL.md

Skill Metadata

Name
kubernetes-operator
Description
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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

| Situation | Skill applies | |-----------|---------------| | Building a new operator for an internal platform primitive | Yes — start with the operator pattern decision | | Auditing an existing operator for production-readiness | Yes — use anti-patterns + scripts/reconciliation_audit.py | | Designing CRDs for a custom resource | Yes — use CRD design + scripts/crd_validator.py | | Deciding "operator vs Helm chart vs plain manifests" | Yes — use the decision matrix | | Scaffolding a new operator project | Yes — 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

| Tool | Purpose | Command | |------|---------|---------| | crd_validator.py | Validate 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.py | Generate a production-ready operator project skeleton with stricter RBAC, observability, and finalizer scaffolding | python3 scripts/operator_scaffold.py --name db-operator --group example.com --kind Database | | reconciliation_audit.py | Audit 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

| Skill | Integration | |-------|------------| | engineering/chaos-engineering | Chaos-test operators (kill the controller, partition from API server) | | engineering/observability-designer | Wire metrics + logging for operators | | engineering/incident-commander | Operators amplify blast radius; incident response matters more | | engineering/feature-flags-architect | Operators with spec.feature.<x>.enabled fields effectively become flag systems; consider the trade-off |