Deployment Advising
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Included in this chapter:
- The three deployment tracks an architect advises
- The application pipeline: Cloud Build then Cloud Deploy
- Choosing a deployment strategy
- Apigee for the API surface and Gemini Cloud Assist
- Exam-pattern recognition
Deployment strategies: blast radius versus cost and speed
| Strategy | How traffic moves to the new version | Downtime | Rollback speed | Cost / complexity | Native support |
|---|---|---|---|---|---|
| Recreate | Stop all old, start all new | Yes, during the swap | Redeploy the old version | Lowest; one environment | Plain Deployment (Recreate) |
| Rolling update | Replace instances incrementally, old and new coexist | No | Roll the update backward | Low; one environment | GKE / Kubernetes default |
| Blue-green | Cut all traffic over in one switch to a parallel environment | No | Fastest; flip back to blue | High; two full environments | Cloud Run traffic split; manual on GKE |
| Canary | Small percentage first, verify, then widen progressively | No | Shift the percentage back | Highest; needs traffic split and verification | Cloud Deploy canary; Cloud Run percentages |
Decision tree
Cheat sheet
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Also tested in
References
- Infrastructure Manager overview
- Cloud Build overview
- Cloud Deploy overview
- What is Apigee?
- Artifact Registry overview
- Using Skaffold with Cloud Deploy
- Cloud Deploy deployment strategies
- Cloud Deploy canary deployment strategy
- Cloud Run: rollouts, rollbacks, and traffic migration
- Cloud Load Balancing overview
- Gemini Cloud Assist overview
- Binary Authorization overview