cicd

CI/CD Pipeline Patterns and Deployment Strategies

Continuous Integration, Continuous Delivery, and Continuous Deployment are a spectrum of automation practices. Each builds on the previous one and removes more manual work between a code change and its availability to users.

CI vs CD vs CD

Practice	What it automates	Gate to next stage
Continuous Integration	Merging, building, and testing code on every commit	Automated tests must pass before merge
Continuous Delivery	Packaging and promoting artifacts through environments	Manual approval before production deployment
Continuous Deployment	Full path from commit to production without manual steps	Automated quality gates replace human approval

Continuous Integration is the foundation. Without reliable, fast integration, neither delivery nor deployment is sustainable. Start there.

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Pipeline design principles

A good pipeline gives developers fast, trustworthy feedback and keeps broken code away from users.

Principle	Meaning
Fast feedback	Run the cheapest, fastest checks first - lint and unit tests before integration tests and builds
Fail early	Stop the pipeline at the first failure - do not waste time on downstream stages when upstream checks fail
Reproducibility	Every pipeline run with the same inputs must produce the same outputs - pin dependencies, use immutable base images
Idempotency	Re-running a pipeline stage should be safe and produce the same result
Isolation	Each pipeline run operates in a clean environment - no shared state between runs
Security by default	Secrets are injected at runtime, never stored in source - scan for vulnerabilities early

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Deployment strategies overview

Strategy	Downtime	Rollback speed	Infrastructure cost	Complexity	Best for
Blue-Green	Zero	Instant (traffic switch)	2x production	Low	Major releases, risk-averse teams
Canary	Zero	Fast (route traffic back)	1x + small canary slice	Medium	Data-driven teams, high-traffic services
Rolling	Zero (if surge configured)	Slow (reverse rollout)	1x (reuses existing)	Low	Stateless services, frequent small changes
Recreate	Yes (brief)	Slow (full redeploy)	1x	Minimal	Dev/staging environments, stateful apps that cannot run two versions
Feature Flags	Zero	Instant (toggle off)	1x	Medium	Progressive rollout, A/B testing, trunk-based development

No single strategy fits every situation. Many teams combine them, for example canary releases with feature flags to control who sees new functionality.

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Environment management overview

A typical promotion path moves artifacts through increasingly production-like environments:

dev -> staging -> production

Principles:

• Artifact immutability - Build once, deploy the same artifact everywhere. Never rebuild for each environment.
• Configuration separation - Environment-specific values (database URLs, API keys, feature toggles) live outside the artifact.
• Parity - Staging should mirror production as closely as possible in infrastructure, data shape, and scale.
• Ephemeral environments - Spin up isolated environments per pull request for testing and review, then tear them down when the PR closes.

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Quick reference: pipeline anti-patterns

Anti-pattern	Problem	Fix
Rebuilding artifacts per environment	Different binary in staging vs production	Build once, promote the same artifact
Long-running monolithic pipeline	Slow feedback, developers context-switch	Parallelize stages, split into focused pipelines
Secrets in source control	Credential leaks, compliance violations	Use a secrets manager, inject at runtime
Manual environment setup	Configuration drift, "works on my machine"	Infrastructure as code, containerized builds
No rollback plan	Extended outages when deployments fail	Automate rollback, test it regularly
Skipping staging	Production-only bugs discovered too late	Always promote through at least one pre-production environment

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Reference Files

Reference	Contents
Pipeline Design	Pipeline stages, parallelization, caching, monorepo patterns, secrets management with multi-format examples
Deployment Strategies	Blue-green, canary, rolling deployments, feature flags, zero-downtime migrations, rollback strategies
Environment Management	Environment promotion, infrastructure as code, ephemeral environments, artifact versioning, health checks

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Integration with Other Skills

Situation	Recommended Skill
Monitoring and observability for deployments	microservices
Security scanning in pipelines	security
Testing strategy for CI pipelines	testing
API versioning during deployments	api-design