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CI/CD Workflow

1. CD/CD workflow diagram

CI/CD flow View full-size image

2. CI/CD Pipeline with GitHub Actions, SonarQube, and ArgoCD

2.1. Source Code Management & Trigger

  • Use GitHub as the single source of truth.

  • Commits or pull requests trigger the CI/CD pipeline automatically via GitHub Actions.

2.2. Continuous Integration (CI) with GitHub Actions

  • Automated build of the application and container image.

  • Run unit tests, integration tests, and linting.

  • Build artifacts (Docker images) are stored in a container registry.

2.3. Code Quality & Security with SonarQube

  • Integrate SonarQube in the CI workflow to perform static code analysis.

  • Detect bugs, code smells, security vulnerabilities, and maintain code quality standards.

  • Fail the build if quality gates are not met, ensuring only high-quality code progresses to deployment.

2.4. Continuous Deployment (CD) with ArgoCD

  • ArgoCD continuously monitors Git repositories for updated Kubernetes manifests or Helm charts.

  • Automatically deploys the new release to the target Kubernetes cluster once the CI pipeline completes successfully.

  • Supports declarative GitOps model, rollback on failure, and progressive rollout strategies.

2.5. Horizontal Scalability & Reliability

  • CI/CD flow ensures consistent and repeatable deployments.

  • Combined with Kubernetes features (autoscaling, node pools), new releases can scale horizontally without downtime.

2.6. Observability & Feedback Loop

  • Provide real-time feedback via GitHub Actions status checks.

  • Logs and metrics from ArgoCD help monitor deployment health and performance post-release.

3. Developer Experience Tooling for Consistent and High-Quality Codebase

3.1. Pre-commit Hooks with Husky + Lint-Staged

  • Automatically enforce code quality before commits.

  • Run linters, formatters, or tests only on staged files, preventing broken or inconsistent code from entering the repository.

  • Reduces human error and ensures team-wide adherence to standards.

3.2. Code Quality and Formatting: ESLint + Prettier

  • ESLint enforces consistent coding patterns and identifies potential bugs.

  • Prettier ensures a unified code style across the codebase.

  • Together, they reduce code review overhead and maintain readability.

3.3. Unit and Integration Testing with Jest

  • Provides a robust framework for writing and running automated tests.

  • Ensures that individual modules and their integrations behave as expected.

  • Critical for maintaining confidence during refactors or feature additions.

3.4. Environment-aware Testing with Testcontainers

  • Allows running ephemeral, isolated containerized dependencies (like databases) for tests.

  • Ensures test environments closely resemble production, reducing environment-related bugs.

3.5. Type Safety with TypeScript

  • Enforces static typing across the codebase.

  • Helps catch errors at compile time rather than runtime.

  • Enhances developer productivity and reduces bugs in large, complex applications.