Stop Downtime with Kubernetes Resource Planning

Stop Downtime with Kubernetes Resource Planning

Stop Downtime with Kubernetes Resource Planning. With a little effort, these issues can be prevented with resource planning. By using Resource requests and limits, users can impose restrictions to a single pod or a group of pods in a namespace.

Why you need Resource Planning

Out of the box, Kubernetes does an excellent job of managing containers. Your Kubernetes cluster may just work perfectly fine right now. Things are humming along perfectly if you just started your container workflow. As your teams grow in size and your cluster hosts more nodes, stability issues will start to surface.

By default, container pods run with unbounded limits. A single pod in the system is capable of consuming as much CPU and memory as available on that node. If you deploy a large application on a node with limited resources, it is possible that the lack of memory or CPU resources will degrade the application and nearby apps within that node. Kubernetes may kill pods as the node reaches out of memory. Worse, it may start throttling critical vital applications to support lesser sensitive ones. An application with an inefficient codebase can easily spiral out of control. Poorly coded or rogue microservices can jeopardize the entire ecosystem through replication. Next, different teams may be spinning up more replicas than they are entitled to. In short, a wide variety of issues will crop up if you don’t properly manage the resources of your growing container platform.

kubernetes kubernetes resource

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