Concepts

Kubernetes v1.14 documentation is no longer actively maintained. The version you are currently viewing is a static snapshot. For up-to-date documentation, see the latest version.

Edit This Page

Pod Overview

This page provides an overview of Pod, the smallest deployable object in the Kubernetes object model.

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 ClusterA set of machines, called nodes, that run containerized applications managed by Kubernetes. .

A Pod encapsulates an application’s container (or, in some cases, multiple containers), storage resources, a unique network IP, and options that govern how the container(s) should run. A Pod represents a unit of deployment: a single instance of an application in Kubernetes, which might consist of either a single containerA lightweight and portable executable image that contains software and all of its dependencies. or a small number of containers that are tightly coupled and that share resources.

Docker is the most common container runtime used in a Kubernetes Pod, but Pods support other container runtimes as well.

Pods in a Kubernetes cluster can be used in two main ways:

Each Pod is meant to run a single instance of a given application. If you want to scale your application horizontally (e.g., run multiple instances), you should use multiple Pods, one for each instance. In Kubernetes, this is generally referred to as replication. Replicated Pods are usually created and managed as a group by an abstraction called a Controller. See Pods and Controllers for more information.

How Pods manage multiple Containers

Pods are designed to support multiple cooperating processes (as containers) that form a cohesive unit of service. The containers in a Pod are automatically co-located and co-scheduled on the same physical or virtual machine in the cluster. The containers can share resources and dependencies, communicate with one another, and coordinate when and how they are terminated.

Note that grouping multiple co-located and co-managed containers in a single Pod is a relatively advanced use case. You should use this pattern only in specific instances in which your containers are tightly coupled. For example, you might have a container that acts as a web server for files in a shared volume, and a separate “sidecar” container that updates those files from a remote source, as in the following diagram:

example pod diagram

Some Pods have init containersOne or more initialization containers that must run to completion before any app containers run. as well as app containersA container used to run part of a workload. Compare with init container. . Init containers run and complete before the app containers are started.

Pods provide two kinds of shared resources for their constituent containers: networking and storage.

Networking

Each Pod is assigned a unique IP address. Every container in a Pod shares the network namespace, including the IP address and network ports. Containers inside a Pod can communicate with one another using localhost. When containers in a Pod communicate with entities outside the Pod, they must coordinate how they use the shared network resources (such as ports).

Storage

A Pod can specify a set of shared storage VolumesA directory containing data, accessible to the containers in a pod. . All containers in the Pod can access the shared volumes, allowing those containers to share data. Volumes also allow persistent data in a Pod to survive in case one of the containers within needs to be restarted. See Volumes for more information on how Kubernetes implements shared storage in a Pod.

Working with Pods

You’ll rarely create individual Pods directly in Kubernetes–even singleton Pods. This is because Pods are designed as relatively ephemeral, disposable entities. When a Pod gets created (directly by you, or indirectly by a Controller), it is scheduled to run on a NodeA node is a worker machine in Kubernetes. in your cluster. The Pod remains on that Node until the process is terminated, the pod object is deleted, the Pod is evicted for lack of resources, or the Node fails.

Note: Restarting a container in a Pod should not be confused with restarting the Pod. The Pod itself does not run, but is an environment the containers run in and persists until it is deleted.

Pods do not, by themselves, self-heal. If a Pod is scheduled to a Node that fails, or if the scheduling operation itself fails, the Pod is deleted; likewise, a Pod won’t survive an eviction due to a lack of resources or Node maintenance. Kubernetes uses a higher-level abstraction, called a Controller, that handles the work of managing the relatively disposable Pod instances. Thus, while it is possible to use Pod directly, it’s far more common in Kubernetes to manage your pods using a Controller. See Pods and Controllers for more information on how Kubernetes uses Controllers to implement Pod scaling and healing.

Pods and Controllers

A Controller can create and manage multiple Pods for you, handling replication and rollout and providing self-healing capabilities at cluster scope. For example, if a Node fails, the Controller might automatically replace the Pod by scheduling an identical replacement on a different Node.

Some examples of Controllers that contain one or more pods include:

In general, Controllers use a Pod Template that you provide to create the Pods for which it is responsible.

Pod Templates

Pod templates are pod specifications which are included in other objects, such as Replication Controllers, Jobs, and DaemonSets. Controllers use Pod Templates to make actual pods. The sample below is a simple manifest for a Pod which contains a container that prints a message.

apiVersion: v1
kind: Pod
metadata:
  name: myapp-pod
  labels:
    app: myapp
spec:
  containers:
  - name: myapp-container
    image: busybox
    command: ['sh', '-c', 'echo Hello Kubernetes! && sleep 3600']

Rather than specifying the current desired state of all replicas, pod templates are like cookie cutters. Once a cookie has been cut, the cookie has no relationship to the cutter. There is no “quantum entanglement”. Subsequent changes to the template or even switching to a new template has no direct effect on the pods already created. Similarly, pods created by a replication controller may subsequently be updated directly. This is in deliberate contrast to pods, which do specify the current desired state of all containers belonging to the pod. This approach radically simplifies system semantics and increases the flexibility of the primitive.

What's next

Feedback