This page explains two different approaches to setting up a highly available Kubernetes cluster using kubeadm: With stacked control plane nodes. This approach requires less infrastructure. The etcd members and control plane nodes are co-located. With an external etcd cluster. This approach requires more infrastructure. The control plane nodes and etcd members are separated. Before proceeding, you should carefully consider which approach best meets the needs of your applications and environment.

Production-Grade Container Orchestration

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.

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.

Define a range of valid CPU resource limits for a namespace, so that every new Pod in that namespace falls within the range you configure.

Production-Grade Container Orchestration

The aggregation layer allows Kubernetes to be extended with additional APIs, beyond what is offered by the core Kubernetes APIs. The additional APIs can either be ready-made solutions such as a metrics server, or APIs that you develop yourself. The aggregation layer is different from Custom Resource Definitions, which are a way to make the kube-apiserver recognise new kinds of object. Aggregation layer The aggregation layer runs in-process with the kube-apiserver.

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.

Windows applications constitute a large portion of the services and applications that run in many organizations. Windows containers provide a way to encapsulate processes and package dependencies, making it easier to use DevOps practices and follow cloud native patterns for Windows applications. Organizations with investments in Windows-based applications and Linux-based applications don't have to look for separate orchestrators to manage their workloads, leading to increased operational efficiencies across their deployments, regardless of operating system.