Canary Release Explained

Traffic control in a canary release:

In a canary release, traffic is split based on the application version that it is being directed to. At first, the new application version is deployed with 0% of the traffic directed to it while the old version handles 100% of the traffic. Then a small percentage of traffic is directed to the new version and monitoring of its performance starts. If there is an issue, that traffic is redirected back to the old version and the deployment process is stopped. If there is no issue, more traffic is gradually directed to the new version until the old version’s traffic gets to 0%.

Traffic Routing:

Traffic routing is a key feature of a canary release and it plays a big role in making it an effective deployment strategy.  With this strategy, you can select the traffic that you want to direct to the new version randomly or subjectively using set criteria. This level of traffic control allows the developer to collect meaningful data from the users’ interactions with the new version. Istio and Ambassador edge stack are traffic control tools that are commonly used in canary releases on Kubernetes.

Istio: This is an agile traffic controller that accepts programmable adjustment of traffic passing through its service mesh. Its ability to enforce policies right after receiving the instructions makes a canary release flexible because roll-out and roll-backs can be implemented fast.

Ambassador edge stack: It implements traffic routing between different services using the weighted round-robin scheme. This is a load balancing strategy that allows for unequal traffic distribution. Important metrics are collected for all the traffic the tool handles and this makes it easy to monitor the progress of a canary release.

Testing in a canary release:

When undertaking a canary release, we perform canary testing to evaluate the performance of the application in real-world usage. One of the ways to perform canary testing is by using feature flags. This works by allowing the developers to separate feature enablement and code release so as to create more testing dimensions. For instance, it can turn some features on or off remotely for a specific group of users or for all the application users. This allows it to measure feature prominence, performance, and importance to the users who are targeted by the changes. All this data provides meaningful insight related to the users’ interaction with the new application or features.

Caution: Even though a canary release will allow for application testing, it should not be a replacement for other types of tests such as unit testing, capacity testing, and A/B testing. Canary testing should be used to test applications that have passed all other tests. In short, tests performed in a canary release should only show the performance of the new feature, code, or configuration in a production environment. In other words, the tests performed are aimed at increasing the developers’ confidence in the application.

A practical use case: How YouTube used canary release

Google is one of the big tech companies that is known to use the canary release strategy while deploying new code and configurations. A while back, YouTube tested a new feature that would display a video preview and not just a static caption, when the pointer was put on a video. This was meant to give a user more information about a video beyond the views, caption, title, and description. They deployed this new application in some of their servers and directed a small subset of user traffic towards it. From this, they were able to measure two things: whether more users clicked on the videos after the preview and, if it helped users get the video they wanted to watch faster. The test was a success and they eventually rolled out the new application fully.

Limitations:

It is not easy to fully understand the capabilities of the canary version because it only handles a small subset of the traffic. Because of this, you can’t be sure of its performance relative to the existing version which is handling significantly more traffic. Therefore, the decision to move ahead with the deployment is made based on an analysis that isn’t very comprehensive. For instance, a canary version with a small subset of users can be fast but have significant latency when handling all users.

Summary

Canary release is very efficient in a situation where there are frequent deployments of new application versions. This is because it is easy to set up when rolling out light updates within a short period of time. While selecting a subset of users to be directed to the new version, one has the option of doing it randomly or based on set criteria. While canary testing can be very insightful, it should not be used as a replacement for other types of tests.

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