This guide is for application owners who want to build highly available applications, and thus need to understand what types of disruptions can happen to Pods. It is also for cluster administrators who want to perform automated cluster actions, like upgrading and autoscaling clusters. Voluntary and involuntary disruptions Pods do not disappear until someone (a person or a controller) destroys them, or there is an unavoidable hardware or system software error.

In order for an [Ingress](/docs/concepts/services-networking/ingress/) to work in your cluster, there must be an _ingress controller_ running. You need to select at least one ingress controller and make sure it is set up in your cluster. This page lists common ingress controllers that you can deploy.

If two Pods in your cluster want to communicate, and both Pods are actually running on the same node, use _Service Internal Traffic Policy_ to keep network traffic within that node. Avoiding a round trip via the cluster network can help with reliability, performance (network latency and throughput), or cost.

You can constrain a Pod so that it is restricted to run on particular node(s), or to prefer to run on particular nodes. There are several ways to do this and the recommended approaches all use label selectors to facilitate the selection. Often, you do not need to set any such constraints; the scheduler will automatically do a reasonable placement (for example, spreading your Pods across nodes so as not place Pods on a node with insufficient free resources).

Information about how to make the Kubernetes scheduler more secure.

This page outlines the differences in how resources are managed between Linux and Windows. On Linux nodes, cgroups are used as a pod boundary for resource control. Containers are created within that boundary for network, process and file system isolation. The Linux cgroup APIs can be used to gather CPU, I/O, and memory use statistics. In contrast, Windows uses a job object per container with a system namespace filter to contain all processes in a container and provide logical isolation from the host.

Lower-level detail relevant to creating or administering a Kubernetes cluster.

System component metrics can give a better look into what is happening inside them. Metrics are particularly useful for building dashboards and alerts. Kubernetes components emit metrics in Prometheus format. This format is structured plain text, designed so that people and machines can both read it. Metrics in Kubernetes In most cases metrics are available on /metrics endpoint of the HTTP server. For components that don't expose endpoint by default, it can be enabled using --bind-address flag.

FEATURE STATE: Kubernetes v1.19 [stable] The scheduling framework is a pluggable architecture for the Kubernetes scheduler. It consists of a set of "plugin" APIs that are compiled directly into the scheduler. These APIs allow most scheduling features to be implemented as plugins, while keeping the scheduling "core" lightweight and maintainable. Refer to the design proposal of the scheduling framework for more technical information on the design of the framework.

Overview of Linux kernel security modules and constraints that you can use to harden your Pods and containers.