How do I implement canary releases for Spinnaker?

Canary releases are an essential strategy for deploying applications with minimal risk. By deploying a new version of your application to a small subset of users before a full rollout, you can monitor its performance and catch any issues early. In Spinnaker, you can implement canary releases using various features like Traffic Splitting and Load Balancers. Below is a simple guide to configure canary releases in Spinnaker.

To implement canary releases:

  1. Create two different versions of your application: the canary and the stable releases.
  2. Set up a Load Balancer to manage the traffic between the two versions.
  3. Use Spinnaker's deployment strategy to define the percentage of traffic to be sent to the canary.
  4. Monitor the performance metrics and error rates of both versions.
  5. Decide whether to promote the canary to be the new stable version or roll back.

Here's an example of how to configure the canary deployment in a Spinnaker pipeline using YAML configuration:

pipeline: name: Canary Deployment type: CANARY stages: - name: Canary Analysis type: canary canaryConfig: name: canary-config trafficSplit: stable: percentage: 90 canary: percentage: 10 - name: Deploy Stable type: deploy ...

Canary Releases Spinnaker DevOps Continuous Delivery Application Deployment

Related Questions

How do I avoid rehashing overhead with std::set in multithreaded code?

How do I find elements with custom comparators with std::set for embedded targets?

How do I erase elements while iterating with std::set for embedded targets?

How do I provide stable iteration order with std::unordered_map for large datasets?

How do I reserve capacity ahead of time with std::unordered_map for large datasets?

How do I erase elements while iterating with std::unordered_map in multithreaded code?

How do I provide stable iteration order with std::map for embedded targets?

How do I provide stable iteration order with std::map in multithreaded code?

How do I avoid rehashing overhead with std::map in performance-sensitive code?

How do I merge two containers efficiently with std::map for embedded targets?