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title: Concepts
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The Concepts section helps you learn about the parts of the Kubernetes system and the abstractions Kubernetes uses to represent your {{< glossary_tooltip text="cluster" term_id="cluster" length="all" >}}, and helps you obtain a deeper understanding of how Kubernetes works.
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## Overview
@ -60,12 +60,13 @@ The Kubernetes master is responsible for maintaining the desired state for your
The nodes in a cluster are the machines (VMs, physical servers, etc) that run your applications and cloud workflows. The Kubernetes master controls each node; you'll rarely interact with nodes directly.
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## {{% heading "whatsnext" %}}
If you would like to write a concept page, see
[Using Page Templates](/docs/home/contribute/page-templates/)
for information about the concept page type and the concept template.
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title: Cloud Controller Manager
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{{< feature-state state="beta" for_k8s_version="v1.11" >}}
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The cloud-controller-manager is structured using a plugin
mechanism that allows different cloud providers to integrate their platforms with Kubernetes.
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## Design
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- update
```
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[Cloud Controller Manager Administration](/docs/tasks/administer-cluster/running-cloud-controller/#cloud-controller-manager)
has instructions on running and managing the cloud controller manager.
@ -212,4 +213,3 @@ The cloud controller manager uses Go interfaces to allow implementations from an
The implementation of the shared controllers highlighted in this document (Node, Route, and Service), and some scaffolding along with the shared cloudprovider interface, is part of the Kubernetes core. Implementations specific to cloud providers are outside the core of Kubernetes and implement the `CloudProvider` interface.
For more information about developing plugins, see [Developing Cloud Controller Manager](/docs/tasks/administer-cluster/developing-cloud-controller-manager/).
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title: Control Plane-Node Communication
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This document catalogs the communication paths between the control plane (really the apiserver) and the Kubernetes cluster. The intent is to allow users to customize their installation to harden the network configuration such that the cluster can be run on an untrusted network (or on fully public IPs on a cloud provider).
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## Node to Control Plane
All communication paths from the nodes to the control plane terminate at the apiserver (none of the other master components are designed to expose remote services). In a typical deployment, the apiserver is configured to listen for remote connections on a secure HTTPS port (443) with one or more forms of client [authentication](/docs/reference/access-authn-authz/authentication/) enabled.

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In robotics and automation, a _control loop_ is
a non-terminating loop that regulates the state of a system.
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## Controller pattern
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or externally to Kubernetes. What fits best will depend on what that particular
controller does.
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## {{% heading "whatsnext" %}}
* Read about the [Kubernetes control plane](/docs/concepts/#kubernetes-control-plane)
* Discover some of the basic [Kubernetes objects](/docs/concepts/#kubernetes-objects)
* Learn more about the [Kubernetes API](/docs/concepts/overview/kubernetes-api/)
* If you want to write your own controller, see [Extension Patterns](/docs/concepts/extend-kubernetes/extend-cluster/#extension-patterns) in Extending Kubernetes.
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- dchen1107
title: Nodes
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Kubernetes runs your workload by placing containers into Pods to run on _Nodes_.
A node may be a virtual or physical machine, depending on the cluster. Each node
@ -23,9 +23,9 @@ The [components](/docs/concepts/overview/components/#node-components) on a node
{{< glossary_tooltip text="container runtime" term_id="container-runtime" >}}, and the
{{< glossary_tooltip text="kube-proxy" term_id="kube-proxy" >}}.
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## Management
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See [Control Topology Management Policies on a Node](/docs/tasks/administer-cluster/topology-manager/)
for more information.
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* Learn about the [components](/docs/concepts/overview/components/#node-components) that make up a node.
* Read the [API definition for Node](/docs/reference/generated/kubernetes-api/{{< param "version" >}}/#node-v1-core).
* Read the [Node](https://git.k8s.io/community/contributors/design-proposals/architecture/architecture.md#the-kubernetes-node)
section of the architecture design document.
* Read about [taints and tolerations](/docs/concepts/configuration/taint-and-toleration/).
* Read about [cluster autoscaling](/docs/tasks/administer-cluster/cluster-management/#cluster-autoscaling).
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Add-ons extend the functionality of Kubernetes.
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Add-ons in each section are sorted alphabetically - the ordering does not imply any preferential status.
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## Networking and Network Policy
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Well-maintained ones should be linked to here. PRs welcome!
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When using client certificate authentication, you can generate certificates
manually through `easyrsa`, `openssl` or `cfssl`.
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### easyrsa
@ -249,4 +249,4 @@ You can use the `certificates.k8s.io` API to provision
x509 certificates to use for authentication as documented
[here](/docs/tasks/tls/managing-tls-in-a-cluster).
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This page explains how to manage Kubernetes running on a specific
cloud provider.
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### kubeadm
[kubeadm](/docs/reference/setup-tools/kubeadm/kubeadm/) is a popular option for creating kubernetes clusters.
kubeadm has configuration options to specify configuration information for cloud providers. For example a typical
@ -363,7 +363,7 @@ Kubernetes network plugin and should appear in the `[Route]` section of the
[kubenet]: /docs/concepts/cluster-administration/network-plugins/#kubenet
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## OVirt

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- lavalamp
title: Cluster Administration Overview
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The cluster administration overview is for anyone creating or administering a Kubernetes cluster.
It assumes some familiarity with core Kubernetes [concepts](/docs/concepts/).
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## Planning a cluster
See the guides in [Setup](/docs/setup/) for examples of how to plan, set up, and configure Kubernetes clusters. The solutions listed in this article are called *distros*.
@ -68,6 +68,6 @@ Note: Not all distros are actively maintained. Choose distros which have been te
* [Logging and Monitoring Cluster Activity](/docs/concepts/cluster-administration/logging/) explains how logging in Kubernetes works and how to implement it.
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Fairness feature enabled.
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## Enabling API Priority and Fairness
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request and the PriorityLevel to which it was assigned.
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For background information on design details for API priority and fairness, see
the [enhancement proposal](https://github.com/kubernetes/enhancements/blob/master/keps/sig-api-machinery/20190228-priority-and-fairness.md).
You can make suggestions and feature requests via [SIG API
Machinery](https://github.com/kubernetes/community/tree/master/sig-api-machinery).
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Garbage collection is a helpful function of kubelet that will clean up unused images and unused containers. Kubelet will perform garbage collection for containers every minute and garbage collection for images every five minutes.
External garbage collection tools are not recommended as these tools can potentially break the behavior of kubelet by removing containers expected to exist.
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## Image Collection
@ -77,10 +77,11 @@ Including:
| `--low-diskspace-threshold-mb` | `--eviction-hard` or `eviction-soft` | eviction generalizes disk thresholds to other resources |
| `--outofdisk-transition-frequency` | `--eviction-pressure-transition-period` | eviction generalizes disk pressure transition to other resources |
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See [Configuring Out Of Resource Handling](/docs/tasks/administer-cluster/out-of-resource/) for more details.
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title: Logging Architecture
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Application and systems logs can help you understand what is happening inside your cluster. The logs are particularly useful for debugging problems and monitoring cluster activity. Most modern applications have some kind of logging mechanism; as such, most container engines are likewise designed to support some kind of logging. The easiest and most embraced logging method for containerized applications is to write to the standard output and standard error streams.
However, the native functionality provided by a container engine or runtime is usually not enough for a complete logging solution. For example, if a container crashes, a pod is evicted, or a node dies, you'll usually still want to access your application's logs. As such, logs should have a separate storage and lifecycle independent of nodes, pods, or containers. This concept is called _cluster-level-logging_. Cluster-level logging requires a separate backend to store, analyze, and query logs. Kubernetes provides no native storage solution for log data, but you can integrate many existing logging solutions into your Kubernetes cluster.
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Cluster-level logging architectures are described in assumption that
a logging backend is present inside or outside of your cluster. If you're
@ -267,4 +267,4 @@ You can implement cluster-level logging by exposing or pushing logs directly fro
every application; however, the implementation for such a logging mechanism
is outside the scope of Kubernetes.
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title: Managing Resources
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You've deployed your application and exposed it via a service. Now what? Kubernetes provides a number of tools to help you manage your application deployment, including scaling and updating. Among the features that we will discuss in more depth are [configuration files](/docs/concepts/configuration/overview/) and [labels](/docs/concepts/overview/working-with-objects/labels/).
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## Organizing resource configurations
@ -449,11 +449,12 @@ kubectl edit deployment/my-nginx
That's it! The Deployment will declaratively update the deployed nginx application progressively behind the scene. It ensures that only a certain number of old replicas may be down while they are being updated, and only a certain number of new replicas may be created above the desired number of pods. To learn more details about it, visit [Deployment page](/docs/concepts/workloads/controllers/deployment/).
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- Learn about [how to use `kubectl` for application introspection and debugging](/docs/tasks/debug-application-cluster/debug-application-introspection/).
- See [Configuration Best Practices and Tips](/docs/concepts/configuration/overview/).
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- RainbowMango
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System component metrics can give a better look into what is happening inside them. Metrics are particularly useful for building dashboards and alerts.
Metrics in Kubernetes control plane are emitted in [prometheus format](https://prometheus.io/docs/instrumenting/exposition_formats/) and are human readable.
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## Metrics in Kubernetes
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cloudprovider_gce_api_request_duration_seconds { request = "list_disk"}
```
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* Read about the [Prometheus text format](https://github.com/prometheus/docs/blob/master/content/docs/instrumenting/exposition_formats.md#text-based-format) for metrics
* See the list of [stable Kubernetes metrics](https://github.com/kubernetes/kubernetes/blob/master/test/instrumentation/testdata/stable-metrics-list.yaml)
* Read about the [Kubernetes deprecation policy](https://kubernetes.io/docs/reference/using-api/deprecation-policy/#deprecating-a-feature-or-behavior )
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title: Cluster Networking
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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:
@ -17,10 +17,10 @@ problems to address:
3. Pod-to-Service communications: this is covered by [services](/docs/concepts/services-networking/service/).
4. External-to-Service communications: this is covered by [services](/docs/concepts/services-networking/service/).
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Kubernetes is all about sharing machines between applications. Typically,
sharing machines requires ensuring that two applications do not try to use the
@ -312,12 +312,13 @@ Weave Net runs as a [CNI plug-in](https://www.weave.works/docs/net/latest/cni-pl
or stand-alone. In either version, it doesn't require any configuration or extra code
to run, and in both cases, the network provides one IP address per pod - as is standard for Kubernetes.
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The early design of the networking model and its rationale, and some future
plans are described in more detail in the [networking design
document](https://git.k8s.io/community/contributors/design-proposals/network/networking.md).
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## Proxies
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Proxies have replaced redirect capabilities. Redirects have been deprecated.
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{{< glossary_definition term_id="configmap" prepend="A ConfigMap is" length="all" >}}
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or use additional (third party) tools to keep your data private.
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## Motivation
Use a ConfigMap for setting configuration data separately from application code.
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these pods.
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* Read about [Secrets](/docs/concepts/configuration/secret/).
* Read [Configure a Pod to Use a ConfigMap](/docs/tasks/configure-pod-container/configure-pod-configmap/).
* Read [The Twelve-Factor App](https://12factor.net/) to understand the motivation for
separating code from configuration.
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Automatically places containers based on their resource requirements and other constraints, while not sacrificing availability. Mix critical and best-effort workloads in order to drive up utilization and save even more resources.
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When you specify a {{< glossary_tooltip term_id="pod" >}}, you can optionally specify how
much of each resource a {{< glossary_tooltip text="Container" term_id="container" >}} needs.
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at least the _request_ amount of that system resource specifically for that container
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## Requests and limits
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* Get hands-on experience [assigning Memory resources to Containers and Pods](/docs/tasks/configure-pod-container/assign-memory-resource/).
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* Read about [project quotas](http://xfs.org/docs/xfsdocs-xml-dev/XFS_User_Guide/tmp/en-US/html/xfs-quotas.html) in XFS
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Use kubeconfig files to organize information about clusters, users, namespaces, and
authentication mechanisms. The `kubectl` command-line tool uses kubeconfig files to
@ -25,10 +25,10 @@ variable or by setting the
For step-by-step instructions on creating and specifying kubeconfig files, see
[Configure Access to Multiple Clusters](/docs/tasks/access-application-cluster/configure-access-multiple-clusters).
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## Supporting multiple clusters, users, and authentication mechanisms
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In `$HOME/.kube/config`, relative paths are stored relatively, and absolute paths
are stored absolutely.
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* [Configure Access to Multiple Clusters](/docs/tasks/access-application-cluster/configure-access-multiple-clusters/)
* [`kubectl config`](/docs/reference/generated/kubectl/kubectl-commands#config)
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title: Configuration Best Practices
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This document highlights and consolidates configuration best practices that are introduced throughout the user guide, Getting Started documentation, and examples.
This is a living document. If you think of something that is not on this list but might be useful to others, please don't hesitate to file an issue or submit a PR.
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## General Configuration Tips
- When defining configurations, specify the latest stable API version.
@ -105,5 +105,5 @@ The caching semantics of the underlying image provider make even `imagePullPolic
- Use `kubectl run` and `kubectl expose` to quickly create single-container Deployments and Services. See [Use a Service to Access an Application in a Cluster](/docs/tasks/access-application-cluster/service-access-application-cluster/) for an example.
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title: Pod Overhead
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on top of the container requests & limits.
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In Kubernetes, the Pod's overhead is set at
[admission](/docs/reference/access-authn-authz/extensible-admission-controllers/#what-are-admission-webhooks)
@ -188,11 +188,12 @@ running with a defined Overhead. This functionality is not available in the 1.9
kube-state-metrics, but is expected in a following release. Users will need to build kube-state-metrics
from source in the meantime.
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* [RuntimeClass](/docs/concepts/containers/runtime-class/)
* [PodOverhead Design](https://github.com/kubernetes/enhancements/blob/master/keps/sig-node/20190226-pod-overhead.md)
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scheduler tries to preempt (evict) lower priority Pods to make scheduling of the
pending Pod possible.
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{{< warning >}}
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exceeding its requests, it won't be evicted. Another Pod with higher priority
that exceeds its requests may be evicted.
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* Read about using ResourceQuotas in connection with PriorityClasses: [limit Priority Class consumption by default](/docs/concepts/policy/resource-quotas/#limit-priority-class-consumption-by-default)
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The kube-scheduler can be configured to enable bin packing of resources along with extended resources using `RequestedToCapacityRatioResourceAllocation` priority function. Priority functions can be used to fine-tune the kube-scheduler as per custom needs.
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## Enabling Bin Packing using RequestedToCapacityRatioResourceAllocation
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- Read about the [Pod Overhead](/docs/concepts/configuration/pod-overhead/) concept
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The aggregation layer allows Kubernetes to be extended with additional APIs, beyond what is offered by the core Kubernetes APIs.
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The aggregation layer is different from [Custom Resources](/docs/concepts/extend-kubernetes/api-extension/custom-resources/), which are a way to make the {{< glossary_tooltip term_id="kube-apiserver" text="kube-apiserver" >}} recognise new kinds of object.
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* To get the aggregator working in your environment, [configure the aggregation layer](/docs/tasks/access-kubernetes-api/configure-aggregation-layer/).
* Then, [setup an extension api-server](/docs/tasks/access-kubernetes-api/setup-extension-api-server/) to work with the aggregation layer.
* Also, learn how to [extend the Kubernetes API using Custom Resource Definitions](/docs/tasks/access-kubernetes-api/extend-api-custom-resource-definitions/).
* Read the specification for [APIService](/docs/reference/generated/kubernetes-api/{{< param "version" >}}/#apiservice-v1-apiregistration-k8s-io)
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* Learn how to [Extend the Kubernetes API with the aggregation layer](/docs/concepts/extend-kubernetes/api-extension/apiserver-aggregation/).
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* The [Xilinx FPGA device plugins](https://github.com/Xilinx/FPGA_as_a_Service/tree/master/k8s-fpga-device-plugin/trunk) for Xilinx FPGA devices
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* Learn about [scheduling GPU resources](/docs/tasks/manage-gpus/scheduling-gpus/) using device plugins
* Learn about [advertising extended resources](/docs/tasks/administer-cluster/extended-resource-node/) on a node
* Read about using [hardware acceleration for TLS ingress](https://kubernetes.io/blog/2019/04/24/hardware-accelerated-ssl/tls-termination-in-ingress-controllers-using-kubernetes-device-plugins-and-runtimeclass/) with Kubernetes
* Learn about the [Topology Manager] (/docs/tasks/adminster-cluster/topology-manager/)
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* Read [CoreOS' original article](https://coreos.com/blog/introducing-operators.html) that introduced the Operator pattern
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* See [Poseidon-Firmament](https://github.com/kubernetes-sigs/poseidon#readme) on GitHub for more information.
* See the [design document](https://github.com/kubernetes-sigs/poseidon/blob/master/docs/design/README.md) for Poseidon.
* Read [Firmament: Fast, Centralized Cluster Scheduling at Scale](https://www.usenix.org/system/files/conference/osdi16/osdi16-gog.pdf), the academic paper on the Firmament scheduling design.
* If you'd like to contribute to Poseidon-Firmament, refer to the [developer setup instructions](https://github.com/kubernetes-sigs/poseidon/blob/master/docs/devel/README.md).
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* View [sample service brokers](https://github.com/openservicebrokerapi/servicebroker/blob/master/gettingStarted.md#sample-service-brokers).
* Explore the [kubernetes-incubator/service-catalog](https://github.com/kubernetes-incubator/service-catalog) project.
* View [svc-cat.io](https://svc-cat.io/docs/).
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Kubernetes is a portable, extensible, open-source platform for managing containerized workloads and services, that facilitates both declarative configuration and automation. It has a large, rapidly growing ecosystem. Kubernetes services, support, and tools are widely available.
The name Kubernetes originates from Greek, meaning helmsman or pilot. Google open-sourced the Kubernetes project in 2014. Kubernetes combines [over 15 years of Google's experience](/blog/2015/04/borg-predecessor-to-kubernetes/) running production workloads at scale with best-of-breed ideas and practices from the community.
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* Does not provide nor adopt any comprehensive machine configuration, maintenance, management, or self-healing systems.
* Additionally, Kubernetes is not a mere orchestration system. In fact, it eliminates the need for orchestration. The technical definition of orchestration is execution of a defined workflow: first do A, then B, then C. In contrast, Kubernetes comprises a set of independent, composable control processes that continuously drive the current state towards the provided desired state. It shouldn’t matter how you get from A to C. Centralized control is also not required. This results in a system that is easier to use and more powerful, robust, resilient, and extensible.
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You can visualize and manage Kubernetes objects with more tools than kubectl and
the dashboard. A common set of labels allows tools to work interoperably, describing
objects in a common manner that all tools can understand.
In addition to supporting tooling, the recommended labels describe applications
in a way that can be queried.
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The metadata is organized around the concept of an _application_. Kubernetes is not
a platform as a service (PaaS) and doesn't have or enforce a formal notion of an application.
Instead, applications are informal and described with metadata. The definition of
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With the MySQL `StatefulSet` and `Service` you'll notice information about both MySQL and Wordpress, the broader application, are included.
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This page explains how Kubernetes objects are represented in the Kubernetes API, and how you can express them in `.yaml` format.
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## Understanding Kubernetes objects {#kubernetes-objects}
*Kubernetes objects* are persistent entities in the Kubernetes system. Kubernetes uses these entities to represent the state of your cluster. Specifically, they can describe:
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and the `spec` format for a Deployment can be found in
[DeploymentSpec v1 apps](/docs/reference/generated/kubernetes-api/{{< param "version" >}}/#deploymentspec-v1-apps).
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* [Kubernetes API overview](/docs/reference/using-api/api-overview/) explains some more API concepts
* Learn about the most important basic Kubernetes objects, such as [Pod](/docs/concepts/workloads/pods/pod-overview/).
* Learn about [controllers](/docs/concepts/architecture/controller/) in Kubernetes
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_Labels_ are key/value pairs that are attached to objects, such as pods.
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## Motivation
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One use case for selecting over labels is to constrain the set of nodes onto which a pod can schedule.
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Each object in your cluster has a [_Name_](#names) that is unique for that type of resource.
Every Kubernetes object also has a [_UID_](#uids) that is unique across your whole cluster.
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For non-unique user-provided attributes, Kubernetes provides [labels](/docs/concepts/overview/working-with-objects/labels/) and [annotations](/docs/concepts/overview/working-with-objects/annotations/).
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## Names
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Kubernetes UIDs are universally unique identifiers (also known as UUIDs).
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* Read about [labels](/docs/concepts/overview/working-with-objects/labels/) in Kubernetes.
* See the [Identifiers and Names in Kubernetes](https://git.k8s.io/community/contributors/design-proposals/architecture/identifiers.md) design document.
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Kubernetes supports multiple virtual clusters backed by the same physical cluster.
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## When to Use Multiple Namespaces
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kubectl api-resources --namespaced=false
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* Learn more about [creating a new namespace](/docs/tasks/administer-cluster/namespaces/#creating-a-new-namespace).
* Learn more about [deleting a namespace](/docs/tasks/administer-cluster/namespaces/#deleting-a-namespace).
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The `kubectl` command-line tool supports several different ways to create and manage
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approaches. Read the [Kubectl book](https://kubectl.docs.kubernetes.io) for
details of managing objects by Kubectl.
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## Management techniques
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- Declarative object configuration is harder to debug and understand results when they are unexpected.
- Partial updates using diffs create complex merge and patch operations.
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- [Managing Kubernetes Objects Using Imperative Commands](/docs/tasks/manage-kubernetes-objects/imperative-command/)
- [Managing Kubernetes Objects Using Object Configuration (Imperative)](/docs/tasks/manage-kubernetes-objects/imperative-config/)
@ -185,4 +186,4 @@ Disadvantages compared to imperative object configuration:
- [Kubectl Book](https://kubectl.docs.kubernetes.io)
- [Kubernetes API Reference](/docs/reference/generated/kubernetes-api/{{< param "version" >}}/)
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By default, containers run with unbounded [compute resources](/docs/user-guide/compute-resources) on a Kubernetes cluster.
With resource quotas, cluster administrators can restrict resource consumption and creation on a {{< glossary_tooltip text="namespace" term_id="namespace" >}} basis.
Within a namespace, a Pod or Container can consume as much CPU and memory as defined by the namespace's resource quota. There is a concern that one Pod or Container could monopolize all available resources. A LimitRange is a policy to constrain resource allocations (to Pods or Containers) in a namespace.
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A _LimitRange_ provides constraints that can:
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Refer to the [LimitRanger design document](https://git.k8s.io/community/contributors/design-proposals/resource-management/admission_control_limit_range.md) for more information.
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- a [detailed example on configuring quota per namespace](/docs/tasks/administer-cluster/quota-memory-cpu-namespace/).
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## What is a Pod Security Policy?
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See [Pod Security Standards](/docs/concepts/security/pod-security-standards/) for policy recommendations.
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When several users or teams share a cluster with a fixed number of nodes,
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A resource quota, defined by a `ResourceQuota` object, provides constraints that limit
aggregate resource consumption per namespace. It can limit the quantity of objects that can
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See a [detailed example for how to use resource quota](/docs/tasks/administer-cluster/quota-api-object/).
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You can constrain a {{< glossary_tooltip text="Pod" term_id="pod" >}} to only be able to run on particular
{{< glossary_tooltip text="Node(s)" term_id="node" >}}, or to prefer to run on particular nodes.
@ -21,9 +21,9 @@ but there are some circumstances where you may want more control on a node where
that a pod ends up on a machine with an SSD attached to it, or to co-locate pods from two different
services that communicate a lot into the same availability zone.
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## nodeSelector
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The above pod will run on the node kube-01.
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[Taints](/docs/concepts/scheduling-eviction/taint-and-toleration/) allow a Node to *repel* a set of Pods.
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The [topology manager](/docs/tasks/administer-cluster/topology-manager/) can take part in node-level
resource allocation decisions.
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## Scheduling overview {#scheduling}
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`QueueSort`, `Filter`, `Score`, `Bind`, `Reserve`, `Permit`, and others. You
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* Read about [scheduler performance tuning](/docs/concepts/scheduling-eviction/scheduler-perf-tuning/)
* Read about [Pod topology spread constraints](/docs/concepts/workloads/pods/pod-topology-spread-constraints/)
* Read the [reference documentation](/docs/reference/command-line-tools-reference/kube-scheduler/) for kube-scheduler
* Learn about [configuring multiple schedulers](/docs/tasks/administer-cluster/configure-multiple-schedulers/)
* Learn about [topology management policies](/docs/tasks/administer-cluster/topology-manager/)
* Learn about [Pod Overhead](/docs/concepts/configuration/pod-overhead/)
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This page explains performance tuning optimizations that are relevant for
large Kubernetes clusters.
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In large clusters, you can tune the scheduler's behaviour balancing
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After going over all the Nodes, it goes back to Node 1.
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[kep]: https://github.com/kubernetes/enhancements/blob/master/keps/sig-scheduling/20180409-scheduling-framework.md
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# Framework workflow
@ -239,4 +239,3 @@ If you are using Kubernetes v1.18 or later, you can configure a set of plugins a
a scheduler profile and then define multiple profiles to fit various kinds of workload.
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[_Node affinity_](/docs/concepts/scheduling-eviction/assign-pod-node/#affinity-and-anti-affinity),
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a set of {{< glossary_tooltip text="nodes" term_id="node" >}} (either as a preference or a
@ -22,9 +22,9 @@ Taints and tolerations work together to ensure that pods are not scheduled
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## Concepts
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Adding these tolerations ensures backward compatibility. You can also add
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* Read about [out of resource handling](/docs/tasks/administer-cluster/out-of-resource/) and how you can configure it
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Kubernetes Security (and security in general) is an immense topic that has many
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integrated into many of the systems that help web applications run,
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for some general concepts surrounding Cloud Native Security. The mental model is completely arbitrary
and you should only use it if it helps you think about where to secure your software
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## The 4C's of Cloud Native Security
Let's start with a diagram that may help you understand how you can think about security in layers.
@ -153,12 +153,13 @@ Most of the above mentioned suggestions can actually be automated in your code
delivery pipeline as part of a series of checks in security. To learn about a
more "Continuous Hacking" approach to software delivery, [this article](https://thenewstack.io/beyond-ci-cd-how-continuous-hacking-of-docker-containers-and-pipeline-driven-security-keeps-ygrene-secure/) provides more detail.
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* Read about [network policies for Pods](/docs/concepts/services-networking/network-policies/)
* Read about [securing your cluster](/docs/tasks/administer-cluster/securing-a-cluster/)
* Read about [API access control](/docs/reference/access-authn-authz/controlling-access/)
* Read about [data encryption in transit](/docs/tasks/tls/managing-tls-in-a-cluster/) for the control plane
* Read about [data encryption at rest](/docs/tasks/administer-cluster/encrypt-data/)
* Read about [Secrets in Kubernetes](/docs/concepts/configuration/secret/)
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Security settings for Pods are typically applied by using [security
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PodSecurityPolicy. The intent of this page is to detail recommended Pod security profiles, decoupled
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## Policy Types
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Additionally, the protection of sandboxed workloads is highly dependent on the method of
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## Default Hosts File Content
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## Exposing pods to the cluster
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...
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* Learn more about [Using a Service to Access an Application in a Cluster](/docs/tasks/access-application-cluster/service-access-application-cluster/)
* Learn more about [Connecting a Front End to a Back End Using a Service](/docs/tasks/access-application-cluster/connecting-frontend-backend/)
* Learn more about [Creating an External Load Balancer](/docs/tasks/access-application-cluster/create-external-load-balancer/)
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## Introduction
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| 1.10 | Beta (on by default)|
| 1.9 | Alpha |
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## Supported Features
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## Motivation
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repacking of EndpointSlices with all pods and their corresponding endpoints
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## Additional controllers
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* Learn more about [Ingress](/docs/concepts/services-networking/ingress/).
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## Terminology
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* Use [Service.Type=LoadBalancer](/docs/concepts/services-networking/service/#loadbalancer)
* Use [Service.Type=NodePort](/docs/concepts/services-networking/service/#nodeport)
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* Learn about [Ingress Controllers](/docs/concepts/services-networking/ingress-controllers/)
* [Set up Ingress on Minikube with the NGINX Controller](/docs/tasks/access-application-cluster/ingress-minikube)
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## Prerequisites
Network policies are implemented by the [network plugin](/docs/concepts/extend-kubernetes/compute-storage-net/network-plugins/). To use network policies, you must be using a networking solution which supports NetworkPolicy. Creating a NetworkPolicy resource without a controller that implements it will have no effect.
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- See the [Declare Network Policy](/docs/tasks/administer-cluster/declare-network-policy/)
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## Motivation
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* Read [Connecting Applications with Services](/docs/concepts/services-networking/connect-applications-service/)
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## Background
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## Introduction
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dynamic storage support (in which case the user should create a matching PV)
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* Learn more about [Creating a PersistentVolume](/docs/tasks/configure-pod-container/configure-persistent-volume-storage/#create-a-persistentvolume).
* Learn more about [Creating a PersistentVolumeClaim](/docs/tasks/configure-pod-container/configure-persistent-volume-storage/#create-a-persistentvolumeclaim).
@ -759,4 +760,3 @@ and need persistent storage, it is recommended that you use the following patter
* [PersistentVolumeSpec](/docs/reference/generated/kubernetes-api/{{< param "version" >}}/#persistentvolumespec-v1-core)
* [PersistentVolumeClaim](/docs/reference/generated/kubernetes-api/{{< param "version" >}}/#persistentvolumeclaim-v1-core)
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## Introduction
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This document describes the concept of `VolumeSnapshotClass` in Kubernetes. Familiarity
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## Introduction
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## CronJob
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[Cron expression format](https://pkg.go.dev/github.com/robfig/cron?tab=doc#hdr-CRON_Expression_Format)
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## Writing a DaemonSet Spec
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the Pod runs on. Use a DaemonSet when it is important that a copy of a Pod always run on
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A _Deployment_ provides declarative updates for [Pods](/docs/concepts/workloads/pods/pod/) and
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Do not manage ReplicaSets owned by a Deployment. Consider opening an issue in the main Kubernetes repository if your use case is not covered below.
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## Use Case
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## How a ReplicationController Works
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* Follow an example of [deploying a stateful application](/docs/tutorials/stateful-application/basic-stateful-set/).
* Follow an example of [deploying Cassandra with Stateful Sets](/docs/tutorials/stateful-application/cassandra/).
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forcing a restart, and the init container completion record has been lost due
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title: Pod Lifecycle
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{{< comment >}}Updated: 4/14/2015{{< /comment >}}
{{< comment >}}Edited and moved to Concepts section: 2/2/17{{< /comment >}}
This page describes the lifecycle of a Pod.
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## Pod phase
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* Node controller sets Pod `phase` to Failed.
* If running under a controller, Pod is recreated elsewhere.
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* Get hands-on experience
[attaching handlers to Container lifecycle events](/docs/tasks/configure-pod-container/attach-handler-lifecycle-event/).
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* Learn more about [Container lifecycle hooks](/docs/concepts/containers/container-lifecycle-hooks/).
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title: Pod Overview
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This page provides an overview of `Pod`, the smallest deployable object in the Kubernetes object model.
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## Understanding Pods
A *Pod* is the basic execution unit of a Kubernetes application--the smallest and simplest unit in the Kubernetes object model that you create or deploy. A Pod represents processes running on your {{< glossary_tooltip term_id="cluster" text="cluster" >}}.
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On Nodes, the {{< glossary_tooltip term_id="kubelet" text="kubelet" >}} does not directly observe or manage any of the details around pod templates and updates; those details are abstracted away. That abstraction and separation of concerns simplifies system semantics, and makes it feasible to extend the cluster's behavior without changing existing code.
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* Learn more about [Pods](/docs/concepts/workloads/pods/pod/)
* [The Distributed System Toolkit: Patterns for Composite Containers](https://kubernetes.io/blog/2015/06/the-distributed-system-toolkit-patterns) explains common layouts for Pods with more than one container
* Learn more about Pod behavior:
* [Pod Termination](/docs/concepts/workloads/pods/pod/#termination-of-pods)
* [Pod Lifecycle](/docs/concepts/workloads/pods/pod-lifecycle/)
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{{< feature-state for_k8s_version="v1.18" state="beta" >}}
You can use _topology spread constraints_ to control how {{< glossary_tooltip text="Pods" term_id="Pod" >}} are spread across your cluster among failure-domains such as regions, zones, nodes, and other user-defined topology domains. This can help to achieve high availability as well as efficient resource utilization.
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## Prerequisites
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- Scaling down a Deployment may result in imbalanced Pods distribution.
- Pods matched on tainted nodes are respected. See [Issue 80921](https://github.com/kubernetes/kubernetes/issues/80921)
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_Pods_ are the smallest deployable units of computing that can be created and
managed in Kubernetes.
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## What is a Pod?
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When creating the manifest for a Pod object, make sure the name specified is a valid
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{{< feature-state for_k8s_version="v1.6" state="alpha" >}}
This page provides an overview of PodPresets, which are objects for injecting
certain information into pods at creation time. The information can include
secrets, volumes, volume mounts, and environment variables.
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## Understanding Pod presets
A PodPreset is an API resource for injecting additional runtime requirements
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See [Injecting data into a Pod using PodPreset](/docs/tasks/inject-data-application/podpreset/)
For more information about the background, see the [design proposal for PodPreset](https://git.k8s.io/community/contributors/design-proposals/service-catalog/pod-preset.md).
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This website is maintained by [Kubernetes SIG Docs](/docs/contribute/#get-involved-with-sig-docs).
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Kubernetes documentation welcomes improvements from all contributors, new and experienced!
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## Getting started
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- Read the [contributor cheatsheet](https://github.com/kubernetes/community/tree/master/contributors/guide/contributor-cheatsheet) to get involved with Kubernetes feature development.
- Submit a [blog post or case study](/docs/contribute/new-content/blogs-case-studies/).
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This page assumes that you understand how to
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to learn about more ways to contribute. You need to use the Git command line
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## Be the PR Wrangler for a week
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This page shows how to contribute to the upstream `kubernetes/kubernetes` project.
You can fix bugs found in the Kubernetes API documentation or the content of
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- [Generating Reference Documentation for the Kubernetes API](/docs/contribute/generate-ref-docs/kubernetes-api/)
- [Generating Reference Documentation for the Kubernetes Components and Tools](/docs/contribute/generate-ref-docs/kubernetes-components/)
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- You need to have these tools installed:
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For more information, see [Creating a Pull Request](https://help.github.com/articles/creating-a-pull-request/)
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## The big picture
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You are now ready to follow the [Generating Reference Documentation for the Kubernetes API](/docs/contribute/generate-ref-docs/kubernetes-api/) guide to generate the
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* [Generating Reference Documentation for the Kubernetes API](/docs/contribute/generate-ref-docs/kubernetes-api/)
* [Generating Reference Docs for Kubernetes Components and Tools](/docs/contribute/generate-ref-docs/kubernetes-components/)
* [Generating Reference Documentation for kubectl Commands](/docs/contribute/generate-ref-docs/kubectl/)
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This page shows how to generate the `kubectl` command reference.
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* [Generating Reference Documentation Quickstart](/docs/contribute/generate-ref-docs/quickstart/)
* [Generating Reference Documentation for Kubernetes Components and Tools](/docs/contribute/generate-ref-docs/kubernetes-components/)
* [Generating Reference Documentation for the Kubernetes API](/docs/contribute/generate-ref-docs/kubernetes-api/)
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This page shows how to update the Kubernetes API reference documentation.
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If you need only to regenerate the reference documentation from the [OpenAPI](https://github.com/OAI/OpenAPI-Specification)
spec, continue reading this page.
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## Setting up the local repositories
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Monitor your pull request, and respond to reviewer comments as needed. Continue
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* [Generating Reference Documentation Quickstart](/docs/contribute/generate-ref-docs/quickstart/)
* [Generating Reference Docs for Kubernetes Components and Tools](/docs/contribute/generate-ref-docs/kubernetes-components/)
* [Generating Reference Documentation for kubectl Commands](/docs/contribute/generate-ref-docs/kubectl/)
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Start with the [Prerequisites section](/docs/contribute/generate-ref-docs/quickstart/#before-you-begin)
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* [Generating Reference Documentation Quickstart](/docs/contribute/generate-ref-docs/quickstart/)
* [Generating Reference Documentation for kubectl Commands](/docs/contribute/generate-ref-docs/kubectl/)
* [Generating Reference Documentation for the Kubernetes API](/docs/contribute/generate-ref-docs/kubernetes-api/)
* [Contributing to the Upstream Kubernetes Project for Documentation](/docs/contribute/generate-ref-docs/contribute-upstream/)
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This page shows how to use the `update-imported-docs` script to generate
the Kubernetes reference documentation. The script automates
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To generate the individual reference documentation by manually setting up the required build repositories and
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* [Generating Reference Documentation for kubectl Commands](/docs/contribute/generate-ref-docs/kubectl/)
* [Generating Reference Documentation for the Kubernetes API](/docs/contribute/generate-ref-docs/kubernetes-api/)
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