Progressive Delivery makes it easier to adopt Continuous Delivery, by deploying new versions to a subset of users and evaluating their correctness and performance before rolling them to the totality of the users, and rolled back if not matching some key metrics. Feature flags and Canary deployments are some of the techniques in Progressive Delivery, used to roll out new versions gradually.

For containerized workloads running on Kubernetes it is very easy to adopt Progressive Delivery using Argo Rollouts. At Adobe Experience Manager we are deploying over 10k non Adobe customer services to Kubernetes. New deployments can occur multiple times per day from internal changes or from customer code, which can be very different from one customer to another. A new feature or piece of code can work fine for 99% of customers but still affect the other 1%, and being able to detect this from just tests is a very costly process.

We will show how to implement a Progressive Delivery pipeline with Argo Rollouts to improve the reliability of the service and prevent regressions. It allows the protection of the service and automation of roll backs to a previous version if needed. This allows for faster delivery with more confidence so regressions are less likely to affect a customer.