How can you implement a rolling deployment strategy in your CI pipeline?

1 Benefits of rolling deployment

Rolling deployment offers several advantages over other deployment methods, such as blue-green or canary. First, it reduces the risk of downtime and errors, as you can test and monitor each update on a small portion of your users or servers before rolling it out to the rest. Second, it allows you to control the pace and scope of your deployment, as you can adjust the number and size of your batches according to your needs and feedback. Third, it saves resources and costs, as you do not need to provision extra infrastructure or duplicate your environment for each deployment.

2 Tools for rolling deployment

To implement a rolling deployment strategy in your CI pipeline, you need some tools that can automate and orchestrate the process. Depending on your cloud provider and platform, you may have different options to choose from. For example, if you use AWS and Kubernetes, you can use AWS CodeDeploy and Kubernetes Deployment objects to manage your rolling updates. If you use Azure and Docker, you can use Azure DevOps and Docker Swarm to achieve the same goal. Alternatively, you can use some cross-platform tools, such as Jenkins or Spinnaker, to integrate with your cloud services and perform rolling deployments.

3 Steps for rolling deployment

Rolling deployment generally involves building and testing your code in a CI pipeline with tools like Git, Maven, or JUnit, then packaging and uploading your code to a repository or registry with tools such as Docker, Helm, or AWS ECR. You should define and configure the deployment parameters, such as batch size, health check, and rollback policy with tools like AWS CodeDeploy, Kubernetes Deployment, or Spinnaker. Once you have triggered the deployment with tools like AWS CodePipeline, Azure DevOps, or Jenkins, you can validate and verify the deployment with tools such as Prometheus, Grafana, or New Relic.

4 Best practices for rolling deployment

To ensure a successful and smooth rolling deployment, you should use version control and branching strategies to manage your code changes and releases, automated tests and code quality checks to ensure your code is ready for deployment, immutable and stateless containers or microservices to avoid configuration drift and dependency issues, load balancers and service discovery to distribute and route your traffic among your servers or pods, metrics and logs to monitor your deployment progress and performance, as well as feedback loops and alerts to detect and resolve any issues or anomalies.

5 Challenges of rolling deployment

Rolling deployment can present several challenges, such as compatibility and dependency issues, testing and debugging difficulties, and user experience and satisfaction issues. To combat these issues, you should use backward and forward compatibility techniques, end-to-end and integration tests, canary or A/B tests, user feedback and analytics, feature toggles or gradual rollouts. This will help ensure your services or components can communicate with each other, your code works as expected, and your users are happy with your updates.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?