callmedevops / cicd-gke

CI/CD with GitHub Actions: Deploying to GKE using Kustomize

Welcome to our repository! This project focuses on a robust CI/CD pipeline using GitHub Actions, deploying applications to Google Kubernetes Engine (GKE) with the aid of Kustomize for manifest customization.

Table of Contents

• Workflow Trigger
• Environment Setup
• CI/CD Pipeline
• Future Implementations and Enhancements
• Conclusion
• Contributing
• License

Workflow Trigger

Our workflow is initiated when a pull request is merged into specific branches: main, develop, and main. This ensures that the CI/CD process is initiated only when code changes are finalized and ready for deployment.

Environment Setup

Before diving into the CI/CD steps, we set up environment variables. These variables, some fetched from GitHub secrets, provide necessary context and credentials for the subsequent steps.

CI/CD Pipeline

1. Checkout Code: The workflow starts by checking out the latest code from the repository.
2. Authenticate with GCloud: To interact with Google Cloud services, the workflow authenticates using a service account key.
3. Configure Docker for GCloud: This step ensures Docker can push images to Google's Artifact Registry.
4. Build and Push Docker Image: The application is containerized and the resulting Docker image is pushed to the Artifact Registry.
5. Setup Kustomize: Kustomize is downloaded and set up. It will be used later for customizing Kubernetes manifests.
6. Get GKE Credentials: To deploy to GKE, the workflow fetches credentials for the Kubernetes cluster.
7. Clone k8s-infra and Deploy: The k8s-infra repository, which contains Kubernetes manifests, is cloned using a deploy key. Then, Kustomize customizes the manifests, and the application is deployed to GKE.

Future Implementations and Enhancements

• ArgoCD Integration: ArgoCD is a declarative, GitOps continuous delivery tool for Kubernetes.
• Enhanced Monitoring with Prometheus and Grafana: Get real-time metrics on application performance and set up alerts for any anomalies.
• Automated Testing with SonarQube: Continuous inspection of code quality.
• Infrastructure as Code with Terraform: Define and provide data center infrastructure using a declarative configuration language.

Conclusion

Our GitHub Actions workflow provides a robust foundation for CI/CD. By considering integrations like ArgoCD, Prometheus, Grafana, SonarQube, and Terraform, we can ensure a more efficient, scalable, and reliable deployment process.

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