Agent Skills: DevOps and Platform Engineering

DevOps and platform engineering patterns: Kubernetes, Terraform, GitOps, CI/CD, observability, incident response, and cloud-native ops.

UncategorizedID: vasilyu1983/AI-Agents-public/ops-devops-platform

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pnpm dlx add-skill https://github.com/vasilyu1983/AI-Agents-public/tree/HEAD/skills/universal/ops-devops-platform

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skills/universal/ops-devops-platform/SKILL.md

Skill Metadata

Name
ops-devops-platform
Description
"Designs DevOps and platform engineering systems. Use when planning Kubernetes, Terraform, GitOps, CI/CD, observability, incident response, or cloud-native operations."

DevOps and Platform Engineering

Quick Reference

| Need | Starting Direction | |------|--------------------| | infrastructure provisioning | Terraform, OpenTofu, Pulumi, or cloud-native IaC | | cluster or app deployment | GitOps first for steady-state, direct tooling for local iteration | | CI/CD | protected pipelines plus workload identity and supply-chain controls — see supply-chain-security | | observability | OpenTelemetry plus metrics, logs, traces, and SLO-based alerting | | platform engineering | golden paths, policy-as-code, and self-service interfaces | | incident operations | runbooks, severity model, escalation, and postmortems |

Workflow

  1. classify the dominant problem:
    • provisioning
    • deployment
    • CI/CD
    • observability
    • platform engineering
    • security hardening
    • incident operations
  2. choose the smallest viable toolchain that matches the runtime and team skill
  3. load the relevant reference and template set
  4. use source and release links to check the target runtime's supported APIs, tool compatibility, and deprecations; for provenance, load supply-chain-security and assess the actual builder against the selected SLSA track
  5. separate evidence stages: static lint/plan, target-environment reconciliation, runtime health plus a representative service path, and rollback or roll-forward readiness
  6. finish with concrete operational outputs: plan, controls, owners, artifact or commit identity, environment, observation window, and untested failure modes

Decision Rules

| Situation | Rule | |-----------|------| | infrastructure change | IaC by default; reconcile an emergency manual change back into code before the next promotion | | steady-state production reconciliation | GitOps (Argo CD / Flux) over push-based deploys | | CI credentials | workload identity (OIDC) over long-lived secrets | | alerting | page on actionable SLO burn rates or imminent capacity exhaustion; send diagnostic host metrics to dashboards | | new environments | platform template + policy guard; no snowflakes | | supply-chain integrity | SLSA build track + cosign keyless signing | | drift | detect via reconciler or terraform plan in CI; never discover by accident |

Related Routing


Guardrails

| Domain | Do | Anti-pattern to avoid | |--------|----|-----------------------| | Provisioning | all material changes in IaC; explicit promotion gates | clickops drift; untagged infrastructure | | Delivery | protected pipelines; artifact provenance; rollback + smoke checks | pipelines without identity boundaries | | Platform | golden paths before self-service; policy-as-code that reduces variation | tools shipped without adoption path or ownership | | Observability | define SLOs first; join logs/traces/metrics on shared trace ID | alert fatigue from raw host-metric thresholds | | Incidents | postmortems feed runbooks and platform changes | postmortems that stop at narrative | | Cost | tagging + budget alerts at resource creation; monthly right-sizing | unmanaged snowflake environments; unreviewed reservations |


Navigation

Reference routing

| Load when… | Reference | |------------|-----------| | supply-chain, SBOM, signing, SLSA | references/supply-chain-security.md | | DORA's five metrics and team archetypes (Elite/High/Medium/Low tiers are retired), AI-adoption instability tax, general DevOps best practices | references/devops-best-practices.md | | GitLab CI — parent/child pipelines, MR variable traps, env-export pattern | references/gitlab-ci-patterns.md | | choosing a tool (IaC, GitOps, CI, policy, observability) | references/tool-landscape.md | | golden paths, internal developer portal, platform maturity, when NOT to build an IDP, platform-vs-product boundary, measuring team cognitive load (Weis four-cluster model, Teamperature, leadership load), CI/IaC/GitOps adoption sequencing | references/platform-engineering-patterns.md | | GitOps multi-env promotion, Argo CD / Flux patterns, automation lag and why continuous apply beats apply-on-change | references/gitops-workflows.md | | Terraform state isolation, why terraform workspace is wrong for environments, stage/prod/mgmt/global layout, secrets-in-state and backend choice | references/terraform-state-architecture.md | | stack sizing (monolithic → application-group → service → micro), blast radius, "is my stack a monolith?" | references/stack-sizing-patterns.md | | IaC testing rungs and their blind spots, infrastructure test diamond vs pyramid, Swiss-cheese layering | references/infrastructure-testing-strategy.md | | on-call, severity model, escalation, postmortems | references/sre-incident-management.md | | day-2 operational runbooks, environment hygiene | references/operational-patterns.md | | AIOps alert correlation, automated triage | references/aiops-patterns.md | | Kalman canary, cost autoscaler, CI capacity stabiliser | references/control-theory-applied.md | | capacity planning, saturation SLO, pipeline bottleneck hunt | references/queueing-theory-applied.md | | CI/CD throughput recovery, constraint surfacing, spend reallocation | references/theory-of-constraints-applied.md | | platform-team charter, algedonic escalation, PRR audit | references/cybernetics-vsm-applied.md | | MTBF/MTTR, availability budgets, FMEA | references/reliability-theory-applied.md | | CAP/PACELC, consensus, idempotency, quorums | references/distributed-systems-applied.md | | source URLs and release trackers | data/sources.json |

When changing the source inventory, run python3 scripts/validate_sources.py --skip-network from this skill directory for schema and coverage only. Run the offline CLI regressions with python3 -m pytest scripts/test_validate_sources.py. URL reachability and source content require separate checks; a schema pass does not refresh evidence dates.

Templates

AWS / GCP / Azure

Kubernetes

Docker / Kafka

Terraform / IaC

CI/CD and GitOps

Monitoring / Observability

Incident response

Security / Cost

Shared utilities

Related Skills

Learnings Loop

When prior decisions or pitfalls are relevant, consult learnings.consolidated.md if present; use learnings.md only for needed history or as the available fallback. Otherwise skip both.

After applying it, if you encountered a pattern worth remembering, a mistake worth preventing, or a domain fact that surprised you, append one dated bullet to learnings.md via agents-skills-feedback-loop/scripts/append_learning.py. Do not modify SKILL.md itself.