Devops ‐ EKS - pcont/wiki GitHub Wiki
| Area | DevOps Team Responsibilities |
|---|---|
| 1. Container Build and Management | - Build Docker images using CI pipelines (e.g., Jenkins, GitLab CI/CD) from application code. |
| - Store and manage images in Amazon ECR, including image versioning and tagging. | |
| - Implement automated vulnerability scanning on images before deployment. | |
| - Define Kubernetes configurations (e.g., Deployments, Services, ConfigMaps) for applications. | |
| 2. CI/CD Pipeline Management | - Develop and maintain CI/CD pipelines to automate container builds, tests, and deployments to EKS. |
| - Implement deployment strategies (e.g., rolling updates, blue-green, canary) within pipelines to ensure smooth rollouts. | |
| - Manage rollback mechanisms in the CI/CD pipeline to revert to previous stable versions when needed. | |
| 3. Deployment and Release Management | - Oversee deployments in different environments (e.g., dev, staging, prod) using separate namespaces in EKS. |
| - Ensure resources are correctly allocated using Kubernetes resource requests and limits to prevent resource contention. | |
| 4. Application Monitoring and Logging | - Set up application monitoring (e.g., Prometheus, Grafana) for performance, availability, and error tracking. |
| - Configure logging (e.g., CloudWatch Logs, ELK Stack) for applications to capture relevant logs for troubleshooting. | |
| - Integrate alerts with incident management tools (e.g., PagerDuty, Slack) for real-time notification and response. | |
| 5. Incident Response and Troubleshooting | - Establish incident response workflows and document procedures for issue resolution. |
| - Perform root cause analysis (RCA) on incidents and implement corrective actions to prevent recurrence. | |
| - Coordinate with infrastructure teams when infrastructure-related issues affect application availability or performance. | |
| 6. Cost Management and Optimization | - Track and analyze costs related to EKS applications, including pod resource usage and cluster costs. |
| - Set and monitor Kubernetes resource requests/limits to optimize resource allocation and minimize cost. | |
| - Use Spot Instances for non-critical workloads if applicable, and manage application-level autoscaling. | |
| 7. Security and Compliance | - Apply IAM roles for service accounts (IRSA) to provide pods with least privilege access to AWS resources. |
| - Implement Role-Based Access Control (RBAC) in Kubernetes to restrict access based on user roles. | |
| - Conduct regular security assessments on container images, ensuring they are compliant with security best practices. | |
| 8. Performance Tuning and Scaling | - Configure Horizontal Pod Autoscaler (HPA) to automatically scale applications based on resource usage and traffic. |
| - Conduct load testing to optimize application performance, ensuring efficient scaling under peak loads. | |
| - Tune pod configurations, such as resource requests/limits, for performance and cost-efficiency. | |
| 9. Continuous Improvement and Automation | - Automate deployment tasks, including scaling, health checks, and application-level backups as needed. |
| - Continuously update and refine CI/CD pipeline processes to improve deployment speed and reduce errors. | |
| - Document DevOps processes, best practices, and maintain up-to-date configurations for team knowledge sharing. |
Description of Each Area
- Container Build and Management: Focuses on building, securing, and managing application images in a registry.
- CI/CD Pipeline Management: Involves automating the build, test, and deployment processes to streamline application updates.
- Deployment and Release Management: Covers managing deployments across environments, ensuring proper resource allocation, and using Kubernetes best practices.
- Application Monitoring and Logging: Focuses on application-level observability, logging, and alerting for troubleshooting.
- Incident Response and Troubleshooting: Establishes protocols for rapid incident response and problem resolution.
- Cost Management and Optimization: Involves resource monitoring and optimizations to control application-related costs in EKS.
- Security and Compliance: Implements security measures specific to application deployment and access control within EKS.
- Performance Tuning and Scaling: Optimizes applications for high performance and scalable response to traffic.
- Continuous Improvement and Automation: Encourages ongoing improvements to deployment processes, automation, and team documentation.
This table highlights DevOps-only tasks, focusing on the application lifecycle in EKS. It avoids infrastructure provisioning and cluster/node management, which would be handled by the infra team. Let me know if you need any further adjustments!
Certainly! Here’s a typical set of steps for a CI/CD pipeline in an Amazon EKS environment, focusing on building, testing, and deploying containerized applications. The pipeline includes both Continuous Integration (CI) and Continuous Deployment (CD) stages, covering everything from code changes to deployment in EKS.
| Step | Description |
|---|---|
| 1. Code Commit and Version Control | Developers push code changes to the version control system (e.g., GitHub, GitLab, Bitbucket). This triggers the CI/CD pipeline. The repository should follow versioning conventions, branching strategies, and PR (pull request) workflows for collaboration. |
| 2. Code Quality and Security Scanning | Perform code quality checks (e.g., SonarQube) to enforce coding standards and run static application security testing (SAST) for early vulnerability detection. Ensure that code passes linting, unit tests, and security checks before proceeding. |
| 3. Build Docker Image | Use CI tools (e.g., Jenkins, GitLab CI/CD, AWS CodeBuild) to build a Docker image from the application code. The Dockerfile defines the build process, which includes dependencies, configurations, and environment setup. |
| 4. Run Unit and Integration Tests | Execute automated tests within the CI pipeline to validate that the application code works as expected. Unit tests check individual functions, while integration tests validate the interaction between components in the Docker environment. |
| 5. Push Image to Amazon ECR | After successful tests, tag the Docker image with a version or unique commit hash, then push it to Amazon ECR (Elastic Container Registry). This centralized registry stores images for different environments (e.g., dev, staging, prod). |
| 6. Image Security Scanning | Run container image vulnerability scans (e.g., AWS ECR scanning, Trivy) on the Docker image in ECR to detect potential security risks. Set up policies to fail the pipeline if critical vulnerabilities are detected in the image. |
| 7. Deploy to Development (Dev) Environment | Use a CD tool (e.g., ArgoCD, Spinnaker, or Helm) to deploy the image to the EKS dev environment. This is typically an automated step that applies the Kubernetes manifests or Helm charts configured to run in the dev namespace. |
| 8. Functional and Integration Testing in Dev | Run functional, integration, and smoke tests on the application in the dev environment. These tests verify the core features of the application and check for any issues introduced during deployment. |
| 9. Deploy to Staging Environment | If the dev deployment passes tests, the image and configurations are promoted to the staging environment. This is a close replica of production where additional testing (e.g., load testing, user acceptance testing) is performed. |
| 10. Performance and Load Testing | Run performance and load tests in the staging environment to ensure the application can handle expected production workloads. Results may require fine-tuning resource requests, limits, and autoscaling configurations in Kubernetes. |
| 11. Approval for Production Deployment | Require manual approval for production deployment. This can involve review and sign-off from stakeholders or automatic gating based on test results. Approval may be managed through CI/CD tools or integrated approval workflows. |
| 12. Deploy to Production Environment | Deploy the tested and approved image to the production environment in EKS. Use rolling updates or canary releases to gradually release the changes while monitoring the application’s health and performance during the deployment. |
| 13. Monitor and Verify Deployment | Post-deployment, monitor the application using tools like Prometheus, Grafana, or CloudWatch to ensure stability. Set up automated alerts for errors, latency, or unusual behavior, and verify that the application is functioning as expected. |
| 14. Rollback Mechanism | Configure rollback procedures in case of issues in production. Use the CI/CD tool or Kubernetes to revert to the previous stable version if errors are detected. Rollbacks can be automated or triggered manually based on alerts. |
| 15. Continuous Improvement and Feedback | Collect feedback from monitoring and logs, and integrate learnings into future development cycles. Analyze deployment metrics (e.g., lead time, deployment frequency, mean time to recovery) to improve pipeline performance. |
CI/CD Pipeline Summary
- Continuous Integration (CI): Includes code quality checks, image builds, automated testing, and security scans to ensure quality and security.
- Continuous Deployment (CD): Manages the progression from dev to staging to production environments, including deployment strategies, performance testing, and monitoring.
This pipeline covers a comprehensive CI/CD process tailored for containerized applications in Amazon EKS, ensuring smooth, reliable, and secure deployments across environments. Let me know if you’d like more detail on any specific step!