Creating a comprehensive deployment rollback script requires careful consideration. Here's a high-level Python script outline tailored for your Kubernetes-based microservices environment: ```python # rollback.py import subprocess import time def rollback(): try: # Rollback Kubernetes deployment using Helm subprocess.run(["helm", "rollback", "release_name", "revision_number"]) # Wait for the deployment to stabilize time.sleep(60) # Adjust based on your application's stability requirements # Scale down the new deployment to zero replicas subprocess.run(["kubectl", "scale", "--replicas=0", "deployment", "deployment_name"]) # Delete new pods to trigger rolling back to the previous version subprocess.run(["kubectl", "delete", "pod", "--selector=app=your_app"]) # Scale up the previous deployment to the desired replicas subprocess.run(["kubectl", "scale", "--replicas=desired_replicas", "deployment", "previous_deployment_name"]) print("Rollback completed successfully.") except Exception as e: print(f"Error during rollback: {str(e)}") if __name__ == "__main__": rollback() ``` This script leverages Helm for rolling back deployments and adjusts replicas to minimize downtime. Integrate this script into your Jenkins pipeline as a post-deployment step. Ensure your Helm charts and Kubernetes manifests specify resource constraints and anti-affinity rules for optimal performance. Regularly review and update the script to accommodate changes in your evolving DevOps landscape. Test it in a controlled environment before applying to production to guarantee smooth execution. Note: Adapt the script according to your specific deployment configurations and Helm chart structure.