As a software engineer, embracing best practices that streamline software delivery while minimizing disruptions to the user experience is essential. Canary deployments have become increasingly popular in k8s environments to address these concerns. In this post, we will explore the principle of canary deployments and explain how to achieve them using Azure Build and Release Pipelines.
What are canary deployments?
Canary deployments are a gradual release strategy that involves deploying a new version of an application or service alongside the existing version. A small percentage of user traffic is directed to the new version to evaluate its performance and stability before fully rolling it out to all users. This approach reduces the risk of introducing new errors or issues into the production environment and allows for quick rollback if any problems arise.
Why are canary deployments important?
Canary deployments provide several key benefits to development teams, including:
- Reduced risk: By exposing only a fraction of users to the new version, the impact of any issues is minimized. This allows teams to identify and resolve problems before they affect the entire user base.
- Faster feedback loop: Canary deployments enable developers to gather user feedback and performance metrics more quickly, leading to faster iterations and improvements.
- Improved confidence in releases: With canary deployments, teams can gain increased confidence in their releases, knowing that they have tested the new version with real users and observed its performance in the production environment.
How to achieve canary deployments in k8s?
To implement canary deployments using Azure Pipelines in Kubernetes, follow these steps:
- Create separate branches: Create separate branches in your version control system for the stable version and the canary version of your application.
- Set up Azure build pipelines: Configure Azure build pipelines to create separate artifacts for the stable and canary versions of your application. Ensure that each deployment has a unique label to distinguish them.
- Configure Azure release pipelines: Create an Azure release pipeline with separate stages for deploying the stable and canary versions. Use manifests to define deployment objects for each version and update the service object to select both the stable and canary deployments based on a common label.
- Control traffic distribution: Integrate a service mesh like Istio, dapr or a Kubernetes Ingress controller into your release pipeline to configure the percentage of traffic directed to the canary deployment. Start with a small percentage and gradually increase it as you gain confidence in the new version’s stability and performance.
- Monitor and analyze: Use Azure Monitor, Application Insights, or other monitoring tools to closely track the performance and error rates of the canary deployment. Consider integrating monitoring and analytics tools into your Release Pipeline to automate the collection of performance data and user feedback.
- Roll out or rollback: If the canary deployment performs well and meets your criteria for success, adjust the Release Pipeline to gradually increase the traffic percentage until it reaches 100%. If issues are detected, trigger a rollback in the pipeline to revert to the stable version and address the problems before attempting another canary deployment.
Canary deployments allow you to roll out new application versions gradually, directing a small percentage of user traffic to the new version before a full-scale rollout. This approach offers numerous benefits, including reduced risk, faster feedback loops, and improved confidence in releases. Unlike side-by-side or blue/green deployments, which require a full switch between versions, canary deployments provide greater flexibility and control over the rollout process, making them the go-to strategy for modern development teams. Dive into the world of canary deployments and learn how they can revolutionize your application release process, ensuring optimal performance and user satisfaction with every update.