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CI/CD Overview

Continuous Integration (CI) and Continuous Deployment (CD) automate the software delivery process, enabling teams to release code changes frequently and reliably.

CI/CD Pipeline Stages

Code → Build → Test → Deploy → Monitor

Stage Breakdown

StagePurposeTypical Tools
SourceVersion controlGit, GitHub, GitLab
BuildCompile & packageDocker, Maven, npm
TestValidate changesJest, PyTest, Selenium
DeployRelease to environmentKubernetes, Docker, AWS
MonitorTrack performancePrometheus, Grafana

CI/CD Patterns

Git-Based CI

Triggers on every push or pull request. Runs tests and builds automatically.

Best For: Open source, team collaboration, code review workflows

Branch-Based Deployment

Different branches deploy to different environments.

BranchEnvironmentPurpose
mainProductionStable releases
stagingStagingPre-production testing
developDevelopmentFeature integration
feature/*Feature environmentsIndividual feature testing

GitOps

Git is the single source of truth for infrastructure and deployments.

Principles:

  • Entire system described in Git
  • Desired state declared in Git
  • Approved changes automatically applied
  • Drift detection and correction

Best For: Kubernetes deployments, infrastructure as code

Tool Selection Guide

ToolTypeWhen to UseStrengthsWeaknesses
GitHub ActionsSaaS CI/CDGitHub-hosted projectsDeep GitHub integration, free for public reposLimited to GitHub
GitLab CIIntegrated CI/CDGitLab-based projectsAll-in-one, extensive featuresRequires GitLab
JenkinsSelf-hostedOn-premise, complex pipelinesHighly customizable, plugin ecosystemRequires maintenance
ArgoCDGitOpsKubernetes deploymentsDeclarative, K8s-nativeLimited to Kubernetes

Deployment Strategies

Rolling Deployment

Gradually replace instances with new version, keeping application available.

Pros: Zero downtime, gradual rollout Cons: Slower deployment, can have multiple versions running simultaneously

Blue-Green Deployment

Maintain two identical production environments. Switch traffic between them.

Pros: Instant rollback, clean testing Cons: Double infrastructure cost, complex state management

Canary Deployment

Roll out to small percentage of users before full deployment.

Pros: Safe testing with real users, gradual rollout Cons: Requires sophisticated traffic routing, longer deployment window

Feature Flags

Release features behind configuration flags without deploying new code.

Pros: Instant enable/disable, no rollback needed Cons: Technical debt accumulation, testing complexity

Common CI/CD Scenarios

Scenario: Simple Web Application

Tools: GitHub Actions, Docker Pipeline:

  1. Push to main branch triggers pipeline
  2. Build Docker image
  3. Run unit tests
  4. Deploy to server
  5. Run smoke tests

Scenario: Microservices Architecture

Tools: Jenkins, Kubernetes, ArgoCD Pipeline:

  1. Each service has its own pipeline
  2. Independent testing and deployment
  3. ArgoCD syncs manifests from Git
  4. Rollback with Git revert

Scenario: Enterprise Application

Tools: GitLab CI, multiple environments, feature flags Pipeline:

  1. Multi-stage pipeline (build, test, deploy)
  2. Promotions between environments
  3. Manual approvals for production
  4. Feature flags control feature rollout

Best Practices

Testing Pyramid

  • Unit Tests: Fast, many tests, isolated code
  • Integration Tests: Slower, fewer tests, component interaction
  • End-to-End Tests: Slowest, fewest tests, full user flows

Pipeline Optimization

  • Parallelize independent tests
  • Cache dependencies between builds
  • Use incremental builds
  • Separate fast feedback from slow verification

Security Integration

  • Scan dependencies for vulnerabilities (Snyk, Dependabot)
  • Static analysis (SonarQube, ESLint)
  • Container image scanning (Trivy, Clair)
  • Infrastructure security checks (Terraform sec)

Monitoring and Alerting

  • Track deployment frequency and lead time
  • Monitor failure rate and recovery time
  • Alert on pipeline failures
  • Collect deployment metrics

Getting Started Guides

Released under MIT License.