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.

This page shows how to use kubectl to list all of the Container images for Pods running in a cluster. 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. If you do not already have a cluster, you can create one by using minikube or you can use one of these Kubernetes playgrounds:

In this example, you will run a Kubernetes Job with multiple parallel worker processes. In this example, as each pod is created, it picks up one unit of work from a task queue, completes it, deletes it from the queue, and exits. Here is an overview of the steps in this example: Start a message queue service. In this example, you use RabbitMQ, but you could use another one. In practice you would set up a message queue service once and reuse it for many jobs.

This documentation is about investigating and diagnosing kubectl related issues. If you encounter issues accessing kubectl or connecting to your cluster, this document outlines various common scenarios and potential solutions to help identify and address the likely cause. Before you begin You need to have a Kubernetes cluster. You also need to have kubectl installed - see install tools Verify kubectl setup Make sure you have installed and configured kubectl correctly on your local machine.

This page shows how to write and read a Container termination message. Termination messages provide a way for containers to write information about fatal events to a location where it can be easily retrieved and surfaced by tools like dashboards and monitoring software. In most cases, information that you put in a termination message should also be written to the general Kubernetes logs. Before you begin You need to have a Kubernetes cluster, and the kubectl command-line tool must be configured to communicate with your cluster.

This page shows how to define dependent environment variables for a container in a Kubernetes Pod. 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. If you do not already have a cluster, you can create one by using minikube or you can use one of these Kubernetes playgrounds:

In this example, you will run a Job in Indexed completion mode configured such that the pods created by the Job can communicate with each other using pod hostnames rather than pod IP addresses. Pods within a Job might need to communicate among themselves. The user workload running in each pod could query the Kubernetes API server to learn the IPs of the other Pods, but it's much simpler to rely on Kubernetes' built-in DNS resolution.

This document details the deprecation policy for various facets of the system. Kubernetes is a large system with many components and many contributors. As with any such software, the feature set naturally evolves over time, and sometimes a feature may need to be removed. This could include an API, a flag, or even an entire feature. To avoid breaking existing users, Kubernetes follows a deprecation policy for aspects of the system that are slated to be removed.

FEATURE STATE: Kubernetes v1.22 [stable] Kubernetes supports multiple appliers collaborating to manage the fields of a single object. Server-Side Apply provides an optional mechanism for your cluster's control plane to track changes to an object's fields. At the level of a specific resource, Server-Side Apply records and tracks information about control over the fields of that object. Server-Side Apply helps users and controllers manage their resources through declarative configuration. Clients can create and modify objects declaratively by submitting their fully specified intent.