Pluggable components let you bring your own logging and monitoring, networking, and service mesh. There is a distinction between cluster operators(Platform Team) and developers (Application Team). The Open Application Model (OAM) was created to overcome this problem. This is true continuous deployment. Below, I discuss two of them briefly. Idiomatic developer experience, supporting common patterns such as GitOps, DockerOps, ManualOps. When a rollback happens, it is automated and the desired state stored in Git will not change. And for some of those fields it's impossible to not include them in the original manifest stored in git (e.g. Change). It allows you to transparently add capabilities like observability, traffic management, and security, without adding them to your own code. The goal is to progressively route traffic to the new version of an application, wait for metrics to be collected, analyze them and match them against pre define rules. However, the actual state is not converged into the desired one. For test environments you can use other solutions. Afterward, they want to scale down the new version and look at some metrics to determine if the new version is performant compared to the old version. Changing the actual state without defining it as the desired state first and storing the changes in Git is a big no-no. It is very easy to use. We've launched a new daily email newsletter! Both offer CRs for implementing progressive delivery strategies in interaction with various ingress controllers and service meshes. KubeVela is a Cloud Native Computing Foundation sandbox project and although it is still in its infancy, it can change the way we use Kubernetes in the near future allowing developers to focus on applications without being Kubernetes experts. For traffic splitting and metrics analysis, Argo Rollouts does not support Linkerd. If we move to the more significant problem of rollbacks, the issue becomes as complicated with Argo Rollouts as with Flagger. It has to be monitored by Promethues, hence the podAnnotations: Install Flagger and set it with nginx provider. However, that drift is temporary. Argo Rollouts is a Kubernetes controller and set of CRDs which provide advanced deployment capabilities such as blue-green, canary, canary analysis, experimentation, and progressive delivery features to Kubernetes. As with Deployments, Rollouts does not follow the strategy parameters on the initial deploy. Kaniko doesnt depend on a Docker daemon and executes each command within a Dockerfile completely in userspace. flagger vs argo rollouts - madphotobooths.co.uk One of the solutions out there is Argo Rollouts. flagger vs argo rollouts GitHub - argoproj/rollouts-demo Lets take a look at another two popular examples: Flagger and Argo Rollouts. A BlueGreen Rollout keeps the old ReplicaSet up and running for 30 seconds or the value of the scaleDownDelaySeconds. Argo Rollouts - Kubernetes Progressive Delivery Controller You just specify the desired state and SchemaHero manages the rest. Crossplane There is still a lot of work to be done. Can we run the Argo Rollouts controller in HA mode? from the official docs). This is how our Kubernetes test namespace looks like: Flagger created the service resources and another ingress podinfo-canary. Lately, Ive been checking on progressive delivery tools. automatically rollback a frontend if backend deployment fails) you need to write your own solution Next we enable Canary for our deployment: In short, during a rollout of a new version, we do acceptance-test and load-test.