AGENT SKILL

canary

Canary deployment patterns

License 许可
MIT
所属仓库
NeuralBlitz/Mito
最近更新
2026-04-21
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Forks
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01 前言 Front Matter

name
canary
license
MIT
metadata
{ "audience": "devops-engineer, platform-engineer", "category": "devops" }
description
Canary deployment patterns
compatibility
opencode

03 SKILL.md 正文

What I do

  • Implement gradual traffic shifting strategies
  • Create automated canary deployments with metric analysis
  • Design rollback automation based on health checks
  • Build observability dashboards for canary analysis
  • Integrate canary releases with CI/CD pipelines
  • Configure intelligent traffic routing based on user segments

When to use me

  • When introducing new features to production
  • When validating infrastructure changes
  • When testing performance under real load
  • When deploying to multiple regions progressively
  • When working with A/B testing alongside deployments
  • When reducing blast radius of potential issues

Key Concepts

Flagger Canary CRD

apiVersion: flagger.app/v1alpha3
kind: Canary
metadata:
  name: myapp
spec:
  targetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: myapp
  service:
    port: 80
  canaryAnalysis:
    interval: 1m
    threshold: 10
    maxWeight: 50
    stepWeight: 10
    metrics:
      - name: request-success-rate
        threshold: 99
        interval: 1m
      - name: request-duration
        threshold: 500
        interval: 1m

Deployment Strategy

  • Start with small percentage (1-5%)
  • Increase gradually if metrics stay healthy
  • Stop and rollback if errors spike
  • Analyze at each stage before proceeding
  • Full rollout typically takes 30-60 minutes

Analysis Criteria

  • Error rate within acceptable threshold
  • Response time not degraded
  • No memory leaks or resource exhaustion
  • Business metrics not negatively impacted
  • No adverse effects on dependent services

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