Operators are software extensions to Kubernetes that make use of custom resources to manage applications and their components. Operators follow Kubernetes principles, notably the control loop. Motivation The operator pattern aims to capture the key aim of a human operator who is managing a service or set of services. Human operators who look after specific applications and services have deep knowledge of how the system ought to behave, how to deploy it, and how to react if there are problems.

Note: This section links to third party projects that provide functionality required by Kubernetes. The Kubernetes project authors aren't responsible for these projects, which are listed alphabetically. To add a project to this list, read the content guide before submitting a change. More information. Add-ons extend the functionality of Kubernetes. This page lists some of the available add-ons and links to their respective installation instructions. The list does not try to be exhaustive.

This page shows how to specify extended resources for a Node. Extended resources allow cluster administrators to advertise node-level resources that would otherwise be unknown to Kubernetes. Before you begin You need to have a Kubernetes cluster, and the kubectl command-line tool must be configured to communicate with your cluster. It is recommended to run this tutorial on a cluster with at least two nodes that are not acting as control plane hosts.

Networking is a central part of Kubernetes, but it can be challenging to understand exactly how it is expected to work. There are 4 distinct networking problems to address: Highly-coupled container-to-container communications: this is solved by Pods and localhost communications. Pod-to-Pod communications: this is the primary focus of this document. Pod-to-Service communications: this is covered by Services. External-to-Service communications: this is also covered by Services. Kubernetes is all about sharing machines among applications.

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.

Production-Grade Container Orchestration

_Topology Aware Routing_ provides a mechanism to help keep network traffic within the zone where it originated. Preferring same-zone traffic between Pods in your cluster can help with reliability, performance (network latency and throughput), or cost.

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.

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.

The EndpointSlice API is the mechanism that Kubernetes uses to let your Service scale to handle large numbers of backends, and allows the cluster to update its list of healthy backends efficiently.