Blue Green Deployment Orchestrator

Blue-Green Deployment Orchestrator

Expert in progressive delivery strategies — blue-green, canary, and rolling deployments with automated traffic shifting and rollback.

Activation Triggers

Activate on: "blue-green deployment", "canary release", "rolling deployment", "traffic shifting", "rollback automation", "progressive delivery", "Argo Rollouts", "Flagger", "deployment strategy"

NOT for: K8s manifests → kubernetes-manifest-generator | CI/CD pipelines → github-actions-pipeline-builder | Monitoring → monitoring-stack-deployer

Quick Start

1. Choose strategy — blue-green for instant cutover, canary for gradual rollout, rolling for simple updates
2. Deploy progressive delivery controller — Argo Rollouts or Flagger
3. Define analysis metrics — error rate, latency p99, custom business metrics
4. Configure traffic shifting — weighted routing via Istio, Linkerd, or Gateway API
5. Set automated rollback — if analysis fails, automatically revert to stable version

Core Capabilities

Architecture Patterns

Argo Rollouts Canary Strategy

apiVersion: argoproj.io/v1alpha1
kind: Rollout
metadata:
  name: api-server
spec:
  replicas: 5
  strategy:
    canary:
      canaryService: api-canary-svc
      stableService: api-stable-svc
      trafficRouting:
        istio:
          virtualService:
            name: api-vsvc
      steps:
        - setWeight: 5        # 5% traffic to canary
        - pause: { duration: 5m }
        - analysis:
            templates:
              - templateName: error-rate-check
        - setWeight: 25       # 25% if analysis passes
        - pause: { duration: 10m }
        - analysis:
            templates:
              - templateName: latency-check
        - setWeight: 50       # 50%
        - pause: { duration: 10m }
        - setWeight: 100      # Full promotion
      rollbackWindow:
        revisions: 2

Blue-Green with Instant Cutover

                    ┌──────────────┐
                    │   Router     │
                    │  (Ingress/   │
                    │   Gateway)   │
                    └──────┬───────┘
                           │
              ┌────────────┼────────────┐
              ▼                         ▼
     ┌────────────────┐      ┌────────────────┐
     │  BLUE (active)  │      │  GREEN (preview)│
     │  v1.2.0         │      │  v1.3.0         │
     │  3 replicas     │      │  3 replicas     │
     └────────────────┘      └────────────────┘

Workflow:
  1. Deploy v1.3.0 to GREEN (preview, no traffic)
  2. Run smoke tests against GREEN preview URL
  3. Switch router: 100% traffic BLUE → GREEN
  4. Monitor for 15 minutes
  5. If healthy: scale down BLUE (now standby)
  6. If unhealthy: instant rollback — switch back to BLUE

Canary Analysis Template

apiVersion: argoproj.io/v1alpha1
kind: AnalysisTemplate
metadata:
  name: error-rate-check
spec:
  metrics:
    - name: error-rate
      interval: 1m
      count: 5
      successCondition: result[0] < 0.01  # < 1% error rate
      failureLimit: 2
      provider:
        prometheus:
          address: http://prometheus:9090
          query: |
            sum(rate(http_requests_total{status=~"5..",
              app="{{args.service}}",
              rollout_hash="{{args.canary-hash}}"}[2m]))
            /
            sum(rate(http_requests_total{
              app="{{args.service}}",
              rollout_hash="{{args.canary-hash}}"}[2m]))

Anti-Patterns

1. Canary without analysis — shifting traffic to canary but not measuring success. Always define automated analysis with clear success/failure criteria.
2. No rollback automation — manual rollback during incidents adds delay. Configure automatic rollback when analysis metrics fail.
3. Testing only happy paths in canary — synthetic smoke tests pass but real user traffic reveals issues. Include error rate and latency metrics from real traffic.
4. Blue-green without enough capacity — running both blue and green requires 2x resources. Budget for double capacity during deployment windows.
5. Skipping progressive steps — going from 5% to 100% in one jump. Use gradual steps (5% → 25% → 50% → 100%) with analysis at each stage.

Quality Checklist

[ ] Deployment strategy documented (blue-green, canary, or rolling)
[ ] Progressive delivery controller deployed (Argo Rollouts or Flagger)
[ ] Traffic splitting configured via service mesh or Gateway API
[ ] Canary analysis templates defined with Prometheus queries
[ ] Automated rollback triggers on error rate or latency degradation
[ ] Preview/canary service accessible for pre-promotion testing
[ ] Rollback tested independently (not just on failure)
[ ] Deployment takes less than 15 minutes end-to-end
[ ] Resource budget accounts for blue-green double capacity
[ ] Deployment status visible in Grafana or ArgoCD dashboard
[ ] Notification sent on promotion and rollback events
[ ] Runbook documents manual override procedures