helm-monitor VS argo-rollouts

Example2: performance is bad or errors rate is up. Need auto rollback 1. Need to be rolledback because 500 erorrs are coming. 2. Solutions may varied from a cronjob that polls the monitoring system to compare and detect 500 errors after it reaches a threshold then apply a command like kubectl deployment undo (check https://github.com/ContainerSolutions/helm-monitor) an fully functional AB rolling release system like argocd or weaveworks flagger ....

And support is on it's way for Argo Rollouts 🎉 https://github.com/argoproj/argo-rollouts/pull/2004

curl -LO https://github.com/argoproj/argo-rollouts/releases/latest/download/kubectl-argo-rollouts-linux-amd64 chmod +x ./kubectl-argo-rollouts-linux-amd64 sudo mv ./kubectl-argo-rollouts-linux-amd64 /usr/local/bin/kubectl-argo-rollouts kubectl argo rollouts version

kubectl create namespace argo-rollouts kubectl apply -n argo-rollouts -f https://github.com/argoproj/argo-rollouts/releases/latest/download/install.yaml

You can see in why argo section here what are the limitations of rolling updates and how rollouts solves it: https://github.com/argoproj/argo-rollouts

Argo Rollouts

Check the public users list https://github.com/argoproj/argo-rollouts/blob/master/USERS.md

Supplementary GitOps operators can also be used for deployment strategies, such as canary releases, A/B tests, and blue/green deployments, which have now been grouped under the term “progressive delivery”. The resources of most GitOps operators are not sufficient for this. One solution is Flagger. The tool that was launched by Weaveworks is now being developed as part of the Flux project. The Argo project also has an operator for this use case: Argo Rollouts. Both offer CRs for implementing progressive delivery strategies in interaction with various ingress controllers and service meshes.