본문으로 건너뛰기
cccskills
무료GitHub에 공개

ops-devops-platform

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

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

설치 방법 보기

포함된 파일(54)

  • SKILL.md13.2 KB
  • agents/openai.yaml353 B
  • assets/aws/template-aws-ops.md3.9 KB
  • assets/aws/template-aws-terraform.md2.7 KB
  • assets/aws/template-cost-optimization.md3.3 KB
  • assets/azure/template-azure-ops.md3.6 KB
  • assets/cicd-pipelines/template-ci-cd.md5.8 KB
  • assets/cicd-pipelines/template-github-actions.md1.7 KB
  • assets/cicd-pipelines/template-gitops.md4.1 KB
  • assets/cicd-pipelines/template-release-safety.md6.5 KB
  • assets/cost-governance/template-cost-governance.md10.4 KB
  • assets/docker/template-docker-ops.md6.6 KB
  • assets/gcp/template-gcp-ops.md3.8 KB
  • assets/gcp/template-gcp-terraform.md2.4 KB
  • assets/incident-response/template-incident-comm.md944 B
  • assets/incident-response/template-incident-response.md6.5 KB
  • assets/incident-response/template-postmortem.md2.5 KB
  • assets/incident-response/template-runbook-starter.md2.4 KB
  • assets/kafka/template-kafka-ops.md7.8 KB
  • assets/kubernetes/template-ha-dr.md6.5 KB
  • assets/kubernetes/template-k8s-deploy.yaml1.3 KB
  • assets/kubernetes/template-kubernetes-ops.md8.5 KB
  • assets/kubernetes/template-platform-api.md3.5 KB
  • assets/monitoring-observability/template-alert-rules.md1.0 KB
  • assets/monitoring-observability/template-loadtest-perf.md3.4 KB
  • assets/monitoring-observability/template-observability-slo.md6.0 KB
  • assets/monitoring-observability/template-slo.md1.3 KB
  • assets/security/template-security-hardening.md5.6 KB
  • assets/terraform-iac/template-env-promotion.md7.3 KB
  • assets/terraform-iac/template-iac-terraform.md7.9 KB
  • assets/terraform-iac/template-module.md2.1 KB
  • data/sources.json26.7 KB
  • learnings.consolidated.md595 B
  • learnings.md1.1 KB
  • references/aiops-patterns.md1.9 KB
  • references/control-theory-applied.md35.6 KB
  • references/cybernetics-vsm-applied.md18.2 KB
  • references/devops-best-practices.md12.2 KB
  • references/distributed-systems-applied.md31.4 KB
  • references/gitlab-ci-patterns.md7.1 KB
  • references/gitops-workflows.md20.3 KB
  • references/infrastructure-testing-strategy.md17.2 KB
  • references/operational-patterns.md2.8 KB
  • references/platform-engineering-patterns.md31.3 KB
  • references/queueing-theory-applied.md18.2 KB
  • references/reliability-theory-applied.md25.0 KB
  • references/sre-incident-management.md15.5 KB
  • references/stack-sizing-patterns.md11.5 KB
  • references/supply-chain-security.md6.0 KB
  • references/terraform-state-architecture.md13.9 KB
  • references/theory-of-constraints-applied.md49.3 KB
  • references/tool-landscape.md4.9 KB
  • scripts/test_validate_sources.py2.8 KB
  • scripts/validate_sources.py6.9 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

DevOps and Platform Engineering

Quick Reference

NeedStarting Direction
infrastructure provisioningTerraform, OpenTofu, Pulumi, or cloud-native IaC
cluster or app deploymentGitOps first for steady-state, direct tooling for local iteration
CI/CDprotected pipelines plus workload identity and supply-chain controls — see supply-chain-security
observabilityOpenTelemetry plus metrics, logs, traces, and SLO-based alerting
platform engineeringgolden paths, policy-as-code, and self-service interfaces
incident operationsrunbooks, 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

SituationRule
infrastructure changeIaC by default; reconcile an emergency manual change back into code before the next promotion
steady-state production reconciliationGitOps (Argo CD / Flux) over push-based deploys
CI credentialsworkload identity (OIDC) over long-lived secrets
alertingpage on actionable SLO burn rates or imminent capacity exhaustion; send diagnostic host metrics to dashboards
new environmentsplatform template + policy guard; no snowflakes
supply-chain integritySLSA build track + cosign keyless signing
driftdetect via reconciler or terraform plan in CI; never discover by accident

Related Routing


Guardrails

DomainDoAnti-pattern to avoid
Provisioningall material changes in IaC; explicit promotion gatesclickops drift; untagged infrastructure
Deliveryprotected pipelines; artifact provenance; rollback + smoke checkspipelines without identity boundaries
Platformgolden paths before self-service; policy-as-code that reduces variationtools shipped without adoption path or ownership
Observabilitydefine SLOs first; join logs/traces/metrics on shared trace IDalert fatigue from raw host-metric thresholds
Incidentspostmortems feed runbooks and platform changespostmortems that stop at narrative
Costtagging + budget alerts at resource creation; monthly right-sizingunmanaged snowflake environments; unreviewed reservations

Navigation

Reference routing

Load when…Reference
supply-chain, SBOM, signing, SLSAreferences/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 practicesreferences/devops-best-practices.md
GitLab CI — parent/child pipelines, MR variable traps, env-export patternreferences/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 sequencingreferences/platform-engineering-patterns.md
GitOps multi-env promotion, Argo CD / Flux patterns, automation lag and why continuous apply beats apply-on-changereferences/gitops-workflows.md
Terraform state isolation, why terraform workspace is wrong for environments, stage/prod/mgmt/global layout, secrets-in-state and backend choicereferences/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 layeringreferences/infrastructure-testing-strategy.md
on-call, severity model, escalation, postmortemsreferences/sre-incident-management.md
day-2 operational runbooks, environment hygienereferences/operational-patterns.md
AIOps alert correlation, automated triagereferences/aiops-patterns.md
Kalman canary, cost autoscaler, CI capacity stabiliserreferences/control-theory-applied.md
capacity planning, saturation SLO, pipeline bottleneck huntreferences/queueing-theory-applied.md
CI/CD throughput recovery, constraint surfacing, spend reallocationreferences/theory-of-constraints-applied.md
platform-team charter, algedonic escalation, PRR auditreferences/cybernetics-vsm-applied.md
MTBF/MTTR, availability budgets, FMEAreferences/reliability-theory-applied.md
CAP/PACELC, consensus, idempotency, quorumsreferences/distributed-systems-applied.md
source URLs and release trackersdata/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.

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

Configures Claude Code hooks and Codex hooks.json/notify. Use when adding PreToolUse guards, Stop hooks, managed hooks, format-on-save, preflight, audits, or worktree/budget hooks.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

vasilyu1983/AI-Agents-public1012026년 10월 16일 업데이트

Configures and hardens Claude Code and Codex MCP servers. Use when connecting databases, APIs, SaaS, building servers, or serving a clearance-filtered knowledge base.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

vasilyu1983/AI-Agents-public1012026년 10월 16일 업데이트

Owns instruction files: AGENTS.md, CLAUDE.md, personal and repo rules. Use when writing, pruning, auditing them, sharing rules across Claude and Codex, or fixing ignored rules.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

vasilyu1983/AI-Agents-public1012026년 10월 16일 업데이트

Creates and audits agent skills: SKILL.md, references, scripts, runtime metadata. Use when writing, validating, or security-reviewing a skill, or fixing truncated skill listings.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

vasilyu1983/AI-Agents-public1012026년 10월 16일 업데이트

Adds per-skill learnings loops for dated patterns, mistakes, and domain facts. Use when wiring skill memory, consolidation, or drift audits.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

vasilyu1983/AI-Agents-public1012026년 10월 16일 업데이트

Chooses subagent, team, workflow, or debate and launches it on Claude Code or Codex. Use when delegating, running agent review boards, or installing shared agents.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

vasilyu1983/AI-Agents-public1012026년 10월 16일 업데이트

vasilyu1983의 스킬 모두 보기

이 스킬의 문제 신고