Operations
CI/CD Pipelines
Continuous Integration and Continuous Delivery automate the path from code change to production. Well-designed pipelines provide fast feedback, ensure quality, and enable safe, frequent deployments.
- CI β Build and test code on every commit
- CD β Automatically deploy verified changes to production
- Deployment Strategies β Blue-green, canary, rolling updates
CI/CD is the backbone of modern software delivery.
Continuous Integration
The practice of frequently merging code changes into a shared repository, with automated builds and tests.
DfContinuous Integration
Continuous Integration (CI) is a development practice where developers merge their changes to a shared repository frequently, ideally multiple times per day. Each merge triggers an automated build and test sequence, providing rapid feedback on whether the changes work correctly and don't break existing functionality.
CI Pipeline Stages
CI Best Practices
| Practice | Description |
|---|---|
| Commit frequently | Small changes = faster feedback |
| Fail fast | Run fastest tests first |
| Parallelize | Run independent stages concurrently |
| Cache dependencies | Reuse node_modules, Docker layers |
| Immutable artifacts | Build once, deploy everywhere |
| Test in isolation | No external dependencies in CI |
Continuous Delivery vs Deployment
DfContinuous Delivery
Continuous Delivery ensures code is always in a deployable state. Every change goes through the pipeline, but production deployment requires manual approval.
DfContinuous Deployment
Continuous Deployment goes further: every change that passes the pipeline is automatically deployed to production without human intervention.
| Aspect | Continuous Delivery | Continuous Deployment |
|---|---|---|
| Production deploy | Manual approval | Automatic |
| Frequency | On demand | Every passing commit |
| Risk | Lower (manual gate) | Requires high test confidence |
| Feedback | Slower | Immediate |
Deployment Strategies
Choose deployment strategies based on risk tolerance. Blue-green for critical services where instant rollback is essential. Canary for gradual validation with real traffic. Rolling for general workloads. Shadow for pre-production validation of high-risk changes.
Practice Exercises
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Design: Design a CI/CD pipeline for a monorepo with 5 services. Include build caching, parallel testing, and deployment to staging/production.
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Strategy: A financial service processes $1M/day. Compare blue-green and canary deployment strategies. Which provides lower risk? Which provides faster rollback?
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Optimization: A CI pipeline takes 30 minutes. Identify bottlenecks and optimize it to under 10 minutes. What trade-offs might you make?
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Rollback: During a canary deployment, error rates spike from 0.1% to 5%. Design an automated rollback strategy that detects this and reverts within 60 seconds.
Key Takeaways:
- CI builds and tests code on every commit; CD automates deployment to production
- CI/CD pipelines provide fast feedback and ensure code is always deployable
- Blue-green provides instant rollback; canary provides gradual validation
- Rolling updates are simple but slower to rollback; shadow testing has zero user impact
- Optimize pipelines through caching, parallelization, and fast-fail strategies
- Infrastructure as Code (IaC) enables reproducible, version-controlled environments
What to Learn Next
-> Containerization Docker, Kubernetes, and pod scheduling.
-> Observability Logging, metrics, tracing, and monitoring.
-> Service Mesh Envoy, Istio, and sidecar proxy patterns.
-> Security Patterns Authentication, authorization, encryption, and mTLS.
-> Cost Optimization Cloud cost management and right-sizing.
-> Event-Driven Architecture Event sourcing, CQRS, and saga patterns.