flagger VS autoscaler

Flagger

Where appropriate, canary releases are an excellent option, as the percentage of traffic exposed to the canary is highly controlled. The trade-off is that the system must have good monitoring in place to be able to quickly identify an issue and roll back if necessary (which can be automated). This guide shows you how to use Apache APISIX and Flagger to quickly implement a canary release solution.

What is Flagger? Flagger is a Progressive Delivery tool that automates the release process for applications running on Kubernetes. Under the hood, both tools are built on top of a modular GitOps toolkit. It is the main reason why Flagger compliments Flux.

flagger: Automated canary using istio/linkerd

I would suggest trying a-b deployment in this case using flagger. It will spin up a new instance and gradually rotate out old ones. Maybe that can be helpful in this weird situation :)

ArgoRollouts offers Canary and BlueGreen deployment strategies for Kubernetes Pods. It's a drop-in replacement for the v1.Deployment object. Flagger is similar what it offers, extending Kubernetes to support Canary and BlueGreen deployment strategies.

Check https://argoproj.github.io/argo-rollouts/ and https://flagger.app/

We use Cluster Autoscaler to automatically adjust the number of nodes (cluster size) based on your actual usage to ensure efficiency. Additionally, we deploy Vertical and Horizontal Pod Autoscalers to scale your applications' resources as their needs change automatically.

> * Hetzner: cheap, good service, the finest pets in the world, no cattle

You can absolutely do cattle with Hetzner. They support imaging and immutable infrastructure. They don't have a native auto scaling equivalent, but if you're using Kubernetes, they have a cluster autoscaler: https://github.com/kubernetes/autoscaler/blob/master/cluster...

Here we take the VPA as a starting point to analyze the design and implementation principles of the VPA in Autoscaler. The source code for this article is based on Autoscaler HEAD fbe25e1.

Autoscaling over EKS can be accomplished using either the cluster-autoscaler project or Karpenter. If you want to use Spot instances, consider using Karpenter, as it has better integrations with AWS for optimizing spot pricing and availability, minimizing interruptions, and falling back to on-demand nodes if no spot instances are available.

Autoscaling is already provided on OVH, but we don't use it for now. Autoscaler has to be manually installed on the AWS/EKS cluster.

do you mean this: https://github.com/kubernetes/autoscaler/blob/master/vertical-pod-autoscaler/pkg/recommender/README.md

Read more about this scaler in detail here!

We have a default node group of Linux hosts, but there's a secondary nodegroup of Windows hosts that is typically scaled down to 0. When a team's build runs, a pod is scheduled based on their definition. Cluster-autoscaler will check the nodeSelector and automatically spin up a node from that nodegroup if necessary.

I am running a Kubernetes cluster(AWS EKS one) with Autoscaler pod So that Cluster will autoscale according to the resource request within the cluster.