This page will discuss containers and container images, as well as their use in operations and solution development.
The word container is an overloaded term. Whenever you use the word, check whether your audience uses the same definition.
Each container that you run is repeatable; the standardization from having
dependencies included means that you get the same behavior wherever you
run it.
Containers decouple applications from the underlying host infrastructure.
This makes deployment easier in different cloud or OS environments.
Each node in a Kubernetes
cluster runs the containers that form the
Pods assigned to that node.
Containers in a Pod are co-located and co-scheduled to run on the same node.
Container images
A container image is a ready-to-run
software package containing everything needed to run an application:
the code and any runtime it requires, application and system libraries,
and default values for any essential settings.
Containers are intended to be stateless and
immutable:
you should not change
the code of a container that is already running. If you have a containerized
application and want to make changes, the correct process is to build a new
image that includes the change, then recreate the container to start from the
updated image.
Container runtimes
A fundamental component that empowers Kubernetes to run containers effectively.
It is responsible for managing the execution and lifecycle of containers within the Kubernetes environment.
Usually, you can allow your cluster to pick the default container runtime
for a Pod. If you need to use more than one container runtime in your cluster,
you can specify the RuntimeClass
for a Pod to make sure that Kubernetes runs those containers using a
particular container runtime.
You can also use RuntimeClass to run different Pods with the same container
runtime but with different settings.
1 - Images
A container image represents binary data that encapsulates an application and all its
software dependencies. Container images are executable software bundles that can run
standalone and that make very well-defined assumptions about their runtime environment.
You typically create a container image of your application and push it to a registry
before referring to it in a Pod.
This page provides an outline of the container image concept.
Note:
If you are looking for the container images for a Kubernetes
release (such as v1.33, the latest minor release),
visit Download Kubernetes.
Image names
Container images are usually given a name such as pause, example/mycontainer, or kube-apiserver.
Images can also include a registry hostname; for example: fictional.registry.example/imagename,
and possibly a port number as well; for example: fictional.registry.example:10443/imagename.
If you don't specify a registry hostname, Kubernetes assumes that you mean the Docker public registry.
You can change this behavior by setting a default image registry in the
container runtime configuration.
After the image name part you can add a tag or digest (in the same way you would when using with commands
like docker or podman). Tags let you identify different versions of the same series of images.
Digests are a unique identifier for a specific version of an image. Digests are hashes of the image's content,
and are immutable. Tags can be moved to point to different images, but digests are fixed.
Image tags consist of lowercase and uppercase letters, digits, underscores (_),
periods (.), and dashes (-). A tag can be up to 128 characters long, and must
conform to the following regex pattern: [a-zA-Z0-9_][a-zA-Z0-9._-]{0,127}.
You can read more about it and find the validation regex in the
OCI Distribution Specification.
If you don't specify a tag, Kubernetes assumes you mean the tag latest.
Image digests consists of a hash algorithm (such as sha256) and a hash value. For example:
sha256:1ff6c18fbef2045af6b9c16bf034cc421a29027b800e4f9b68ae9b1cb3e9ae07.
You can find more information about the digest format in the
OCI Image Specification.
Some image name examples that Kubernetes can use are:
busybox — Image name only, no tag or digest. Kubernetes will use the Docker
public registry and latest tag. Equivalent to docker.io/library/busybox:latest.
busybox:1.32.0 — Image name with tag. Kubernetes will use the Docker
public registry. Equivalent to docker.io/library/busybox:1.32.0.
registry.k8s.io/pause:latest — Image name with a custom registry and latest tag.
registry.k8s.io/pause:3.5 — Image name with a custom registry and non-latest tag.
registry.k8s.io/pause@sha256:1ff6c18fbef2045af6b9c16bf034cc421a29027b800e4f9b68ae9b1cb3e9ae07 —
Image name with digest.
registry.k8s.io/pause:3.5@sha256:1ff6c18fbef2045af6b9c16bf034cc421a29027b800e4f9b68ae9b1cb3e9ae07 —
Image name with tag and digest. Only the digest will be used for pulling.
Updating images
When you first create a Deployment,
StatefulSet, Pod, or other
object that includes a PodTemplate, and a pull policy was not explicitly specified,
then by default the pull policy of all containers in that Pod will be set to
IfNotPresent. This policy causes the
kubelet to skip pulling an
image if it already exists.
Image pull policy
The imagePullPolicy for a container and the tag of the image both affect when the
kubelet attempts to pull
(download) the specified image.
Here's a list of the values you can set for imagePullPolicy and the effects
these values have:
IfNotPresent
the image is pulled only if it is not already present locally.
Always
every time the kubelet launches a container, the kubelet queries the container
image registry to resolve the name to an image
digest.
If the kubelet has a container image with that exact digest cached locally, the kubelet uses its
cached image; otherwise, the kubelet pulls the image with the resolved digest, and uses that image
to launch the container.
Never
the kubelet does not try fetching the image. If the image is somehow already present
locally, the kubelet attempts to start the container; otherwise, startup fails.
See pre-pulled images for more details.
The caching semantics of the underlying image provider make even
imagePullPolicy: Always efficient, as long as the registry is reliably accessible.
Your container runtime can notice that the image layers already exist on the node
so that they don't need to be downloaded again.
Note:
You should avoid using the :latest tag when deploying containers in production as
it is harder to track which version of the image is running and more difficult to
roll back properly.
Instead, specify a meaningful tag such as v1.42.0 and/or a digest.
To make sure the Pod always uses the same version of a container image, you can specify
the image's digest;
replace <image-name>:<tag> with <image-name>@<digest>
(for example, image@sha256:45b23dee08af5e43a7fea6c4cf9c25ccf269ee113168c19722f87876677c5cb2).
When using image tags, if the image registry were to change the code that the tag on that image
represents, you might end up with a mix of Pods running the old and new code. An image digest
uniquely identifies a specific version of the image, so Kubernetes runs the same code every time
it starts a container with that image name and digest specified. Specifying an image by digest
pins the code that you run so that a change at the registry cannot lead to that mix of versions.
There are third-party admission controllers
that mutate Pods (and PodTemplates) when they are created, so that the
running workload is defined based on an image digest rather than a tag.
That might be useful if you want to make sure that your entire workload is
running the same code no matter what tag changes happen at the registry.
Default image pull policy
When you (or a controller) submit a new Pod to the API server, your cluster sets the
imagePullPolicy field when specific conditions are met:
if you omit the imagePullPolicy field, and you specify the digest for the
container image, the imagePullPolicy is automatically set to IfNotPresent.
if you omit the imagePullPolicy field, and the tag for the container image is
:latest, imagePullPolicy is automatically set to Always.
if you omit the imagePullPolicy field, and you don't specify the tag for the
container image, imagePullPolicy is automatically set to Always.
if you omit the imagePullPolicy field, and you specify a tag for the container
image that isn't :latest, the imagePullPolicy is automatically set to
IfNotPresent.
Note:
The value of imagePullPolicy of the container is always set when the object is
first created, and is not updated if the image's tag or digest later changes.
For example, if you create a Deployment with an image whose tag is not:latest, and later update that Deployment's image to a :latest tag, the
imagePullPolicy field will not change to Always. You must manually change
the pull policy of any object after its initial creation.
Required image pull
If you would like to always force a pull, you can do one of the following:
Set the imagePullPolicy of the container to Always.
Omit the imagePullPolicy and use :latest as the tag for the image to use;
Kubernetes will set the policy to Always when you submit the Pod.
Omit the imagePullPolicy and the tag for the image to use;
Kubernetes will set the policy to Always when you submit the Pod.
When a kubelet starts creating containers for a Pod using a container runtime,
it might be possible the container is in Waiting
state because of ImagePullBackOff.
The status ImagePullBackOff means that a container could not start because Kubernetes
could not pull a container image (for reasons such as invalid image name, or pulling
from a private registry without imagePullSecret). The BackOff part indicates
that Kubernetes will keep trying to pull the image, with an increasing back-off delay.
Kubernetes raises the delay between each attempt until it reaches a compiled-in limit,
which is 300 seconds (5 minutes).
Image pull per runtime class
FEATURE STATE:Kubernetes v1.29 [alpha] (enabled by default: false)
Kubernetes includes alpha support for performing image pulls based on the RuntimeClass of a Pod.
If you enable the RuntimeClassInImageCriApifeature gate,
the kubelet references container images by a tuple of image name and runtime handler
rather than just the image name or digest. Your
container runtime
may adapt its behavior based on the selected runtime handler.
Pulling images based on runtime class is useful for VM-based containers, such as
Windows Hyper-V containers.
Serial and parallel image pulls
By default, the kubelet pulls images serially. In other words, the kubelet sends
only one image pull request to the image service at a time. Other image pull
requests have to wait until the one being processed is complete.
Nodes make image pull decisions in isolation. Even when you use serialized image
pulls, two different nodes can pull the same image in parallel.
If you would like to enable parallel image pulls, you can set the field
serializeImagePulls to false in the kubelet configuration.
With serializeImagePulls set to false, image pull requests will be sent to the image service immediately,
and multiple images will be pulled at the same time.
When enabling parallel image pulls, ensure that the image service of your container
runtime can handle parallel image pulls.
The kubelet never pulls multiple images in parallel on behalf of one Pod. For example,
if you have a Pod that has an init container and an application container, the image
pulls for the two containers will not be parallelized. However, if you have two
Pods that use different images, and the parallel image pull feature is enabled,
the kubelet will pull the images in parallel on behalf of the two different Pods.
Maximum parallel image pulls
FEATURE STATE:Kubernetes v1.32 [beta]
When serializeImagePulls is set to false, the kubelet defaults to no limit on
the maximum number of images being pulled at the same time. If you would like to
limit the number of parallel image pulls, you can set the field maxParallelImagePulls
in the kubelet configuration. With maxParallelImagePulls set to n, only n
images can be pulled at the same time, and any image pull beyond n will have to
wait until at least one ongoing image pull is complete.
Limiting the number of parallel image pulls prevents image pulling from consuming
too much network bandwidth or disk I/O, when parallel image pulling is enabled.
You can set maxParallelImagePulls to a positive number that is greater than or
equal to 1. If you set maxParallelImagePulls to be greater than or equal to 2,
you must set serializeImagePulls to false. The kubelet will fail to start
with an invalid maxParallelImagePulls setting.
Multi-architecture images with image indexes
As well as providing binary images, a container registry can also serve a
container image index.
An image index can point to multiple image manifests
for architecture-specific versions of a container. The idea is that you can have
a name for an image (for example: pause, example/mycontainer, kube-apiserver)
and allow different systems to fetch the right binary image for the machine
architecture they are using.
The Kubernetes project typically creates container images for its releases with
names that include the suffix -$(ARCH). For backward compatibility, generate
older images with suffixes. For instance, an image named as pause would be a
multi-architecture image containing manifests for all supported architectures,
while pause-amd64 would be a backward-compatible version for older configurations,
or for YAML files with hardcoded image names containing suffixes.
Using a private registry
Private registries may require authentication to be able to discover and/or pull
images from them.
Credentials can be provided in several ways:
If you're using a custom node configuration, you (or your cloud provider) can
implement your mechanism for authenticating the node to the container registry.
These options are explained in more detail below.
Specifying imagePullSecrets on a Pod
Note:
This is the recommended approach to run containers based on images
in private registries.
Kubernetes supports specifying container image registry keys on a Pod.
All imagePullSecrets must be Secrets that exist in the same
Namespace as the
Pod. These Secrets must be of type kubernetes.io/dockercfg or kubernetes.io/dockerconfigjson.
Configuring nodes to authenticate to a private registry
Specific instructions for setting credentials depends on the container runtime and registry you
chose to use. You should refer to your solution's documentation for the most accurate information.
For an example of configuring a private container image registry, see the
Pull an Image from a Private Registry
task. That example uses a private registry in Docker Hub.
Kubelet credential provider for authenticated image pulls
You can configure the kubelet to invoke a plugin binary to dynamically fetch
registry credentials for a container image. This is the most robust and versatile
way to fetch credentials for private registries, but also requires kubelet-level
configuration to enable.
This technique can be especially useful for running static Pods
that require container images hosted in a private registry.
Using a ServiceAccount or a
Secret to provide private registry credentials
is not possible in the specification of a static Pod, because it cannot
have references to other API resources in its specification.
The interpretation of config.json varies between the original Docker
implementation and the Kubernetes interpretation. In Docker, the auths keys
can only specify root URLs, whereas Kubernetes allows glob URLs as well as
prefix-matched paths. The only limitation is that glob patterns (*) have to
include the dot (.) for each subdomain. The amount of matched subdomains has
to be equal to the amount of glob patterns (*.), for example:
*.kubernetes.io will not match kubernetes.io, but will match
abc.kubernetes.io.
*.*.kubernetes.io will not match abc.kubernetes.io, but will match
abc.def.kubernetes.io.
prefix.*.io will match prefix.kubernetes.io.
*-good.kubernetes.io will match prefix-good.kubernetes.io.
Image pull operations pass the credentials to the CRI container runtime for every
valid pattern. For example, the following container image names would match
successfully:
my-registry.example/images
my-registry.example/images/my-image
my-registry.example/images/another-image
sub.my-registry.example/images/my-image
However, these container image names would not match:
a.sub.my-registry.example/images/my-image
a.b.sub.my-registry.example/images/my-image
The kubelet performs image pulls sequentially for every found credential. This
means that multiple entries in config.json for different paths are possible, too:
If now a container specifies an image my-registry.example/images/subpath/my-image
to be pulled, then the kubelet will try to download it using both authentication
sources if one of them fails.
Pre-pulled images
Note:
This approach is suitable if you can control node configuration. It
will not work reliably if your cloud provider manages nodes and replaces
them automatically.
By default, the kubelet tries to pull each image from the specified registry.
However, if the imagePullPolicy property of the container is set to IfNotPresent or Never,
then a local image is used (preferentially or exclusively, respectively).
If you want to rely on pre-pulled images as a substitute for registry authentication,
you must ensure all nodes in the cluster have the same pre-pulled images.
This can be used to preload certain images for speed or as an alternative to
authenticating to a private registry.
Similar to the usage of the kubelet credential provider,
pre-pulled images are also suitable for launching
static Pods that depend
on images hosted in a private registry.
Note:
FEATURE STATE:Kubernetes v1.33 [alpha] (enabled by default: false)
FEATURE STATE:Kubernetes v1.33 [alpha] (enabled by default: false)
If the KubeletEnsureSecretPulledImages feature gate is enabled for your cluster,
Kubernetes will validate image credentials for every image that requires credentials
to be pulled, even if that image is already present on the node. This validation
ensures that images in a Pod request which have not been successfully pulled
with the provided credentials must re-pull the images from the registry.
Additionally, image pulls that re-use the same credentials
which previously resulted in a successful image pull will not need to re-pull from
the registry and are instead validated locally without accessing the registry
(provided the image is available locally).
This is controlled by theimagePullCredentialsVerificationPolicy field in the
Kubelet configuration.
This configuration controls when image pull credentials must be verified if the
image is already present on the node:
NeverVerify: Mimics the behavior of having this feature gate disabled.
If the image is present locally, image pull credentials are not verified.
NeverVerifyPreloadedImages: Images pulled outside the kubelet are not verified,
but all other images will have their credentials verified. This is the default behavior.
NeverVerifyAllowListedImages: Images pulled outside the kubelet and mentioned within the
preloadedImagesVerificationAllowlist specified in the kubelet config are not verified.
AlwaysVerify: All images will have their credentials verified
before they can be used.
This verification applies to pre-pulled images,
images pulled using node-wide secrets, and images pulled using Pod-level secrets.
Note:
In the case of credential rotation, the credentials previously used to pull the image
will continue to verify without the need to access the registry. New or rotated credentials
will require the image to be re-pulled from the registry.
Creating a Secret with a Docker config
You need to know the username, registry password and client email address for authenticating
to the registry, as well as its hostname.
Run the following command, substituting placeholders with the appropriate values:
This is particularly useful if you are using multiple private container
registries, as kubectl create secret docker-registry creates a Secret that
only works with a single private registry.
Note:
Pods can only reference image pull secrets in their own namespace,
so this process needs to be done one time per namespace.
Referring to imagePullSecrets on a Pod
Now, you can create pods which reference that secret by adding the imagePullSecrets
section to a Pod definition. Each item in the imagePullSecrets array can only
reference one Secret in the same namespace.
Run a private registry with authorization required.
Generate registry credentials for each tenant, store into a Secret, and propagate
the Secret to every tenant namespace.
The tenant then adds that Secret to imagePullSecrets of each namespace.
If you need access to multiple registries, you can create one Secret per registry.
Legacy built-in kubelet credential provider
In older versions of Kubernetes, the kubelet had a direct integration with cloud
provider credentials. This provided the ability to dynamically fetch credentials
for image registries.
There were three built-in implementations of the kubelet credential provider
integration: ACR (Azure Container Registry), ECR (Elastic Container Registry),
and GCR (Google Container Registry).
Starting with version 1.26 of Kubernetes, the legacy mechanism has been removed,
so you would need to either:
configure a kubelet image credential provider on each node; or
specify image pull credentials using imagePullSecrets and at least one Secret.
This page describes the resources available to Containers in the Container environment.
Container environment
The Kubernetes Container environment provides several important resources to Containers:
A filesystem, which is a combination of an image and one or more volumes.
Information about the Container itself.
Information about other objects in the cluster.
Container information
The hostname of a Container is the name of the Pod in which the Container is running.
It is available through the hostname command or the
gethostname
function call in libc.
The Pod name and namespace are available as environment variables through the
downward API.
User defined environment variables from the Pod definition are also available to the Container,
as are any environment variables specified statically in the container image.
Cluster information
A list of all services that were running when a Container was created is available to that Container as environment variables.
This list is limited to services within the same namespace as the new Container's Pod and Kubernetes control plane services.
For a service named foo that maps to a Container named bar,
the following variables are defined:
FOO_SERVICE_HOST=<the host the service is running on>
FOO_SERVICE_PORT=<the port the service is running on>
Services have dedicated IP addresses and are available to the Container via DNS,
if DNS addon is enabled.
This page describes the RuntimeClass resource and runtime selection mechanism.
RuntimeClass is a feature for selecting the container runtime configuration. The container runtime
configuration is used to run a Pod's containers.
Motivation
You can set a different RuntimeClass between different Pods to provide a balance of
performance versus security. For example, if part of your workload deserves a high
level of information security assurance, you might choose to schedule those Pods so
that they run in a container runtime that uses hardware virtualization. You'd then
benefit from the extra isolation of the alternative runtime, at the expense of some
additional overhead.
You can also use RuntimeClass to run different Pods with the same container runtime
but with different settings.
Setup
Configure the CRI implementation on nodes (runtime dependent)
Create the corresponding RuntimeClass resources
1. Configure the CRI implementation on nodes
The configurations available through RuntimeClass are Container Runtime Interface (CRI)
implementation dependent. See the corresponding documentation (below) for your
CRI implementation for how to configure.
Note:
RuntimeClass assumes a homogeneous node configuration across the cluster by default (which means
that all nodes are configured the same way with respect to container runtimes). To support
heterogeneous node configurations, see Scheduling below.
The configurations have a corresponding handler name, referenced by the RuntimeClass. The
handler must be a valid DNS label name.
2. Create the corresponding RuntimeClass resources
The configurations setup in step 1 should each have an associated handler name, which identifies
the configuration. For each handler, create a corresponding RuntimeClass object.
The RuntimeClass resource currently only has 2 significant fields: the RuntimeClass name
(metadata.name) and the handler (handler). The object definition looks like this:
# RuntimeClass is defined in the node.k8s.io API groupapiVersion:node.k8s.io/v1kind:RuntimeClassmetadata:# The name the RuntimeClass will be referenced by.# RuntimeClass is a non-namespaced resource.name:myclass # The name of the corresponding CRI configurationhandler:myconfiguration
It is recommended that RuntimeClass write operations (create/update/patch/delete) be
restricted to the cluster administrator. This is typically the default. See
Authorization Overview for more details.
Usage
Once RuntimeClasses are configured for the cluster, you can specify a
runtimeClassName in the Pod spec to use it. For example:
This will instruct the kubelet to use the named RuntimeClass to run this pod. If the named
RuntimeClass does not exist, or the CRI cannot run the corresponding handler, the pod will enter the
Failed terminal phase. Look for a
corresponding event for an
error message.
If no runtimeClassName is specified, the default RuntimeHandler will be used, which is equivalent
to the behavior when the RuntimeClass feature is disabled.
CRI Configuration
For more details on setting up CRI runtimes, see CRI installation.
Runtime handlers are configured through containerd's configuration at
/etc/containerd/config.toml. Valid handlers are configured under the runtimes section:
By specifying the scheduling field for a RuntimeClass, you can set constraints to
ensure that Pods running with this RuntimeClass are scheduled to nodes that support it.
If scheduling is not set, this RuntimeClass is assumed to be supported by all nodes.
To ensure pods land on nodes supporting a specific RuntimeClass, that set of nodes should have a
common label which is then selected by the runtimeclass.scheduling.nodeSelector field. The
RuntimeClass's nodeSelector is merged with the pod's nodeSelector in admission, effectively taking
the intersection of the set of nodes selected by each. If there is a conflict, the pod will be
rejected.
If the supported nodes are tainted to prevent other RuntimeClass pods from running on the node, you
can add tolerations to the RuntimeClass. As with the nodeSelector, the tolerations are merged
with the pod's tolerations in admission, effectively taking the union of the set of nodes tolerated
by each.
To learn more about configuring the node selector and tolerations, see
Assigning Pods to Nodes.
Pod Overhead
FEATURE STATE:Kubernetes v1.24 [stable]
You can specify overhead resources that are associated with running a Pod. Declaring overhead allows
the cluster (including the scheduler) to account for it when making decisions about Pods and resources.
Pod overhead is defined in RuntimeClass through the overhead field. Through the use of this field,
you can specify the overhead of running pods utilizing this RuntimeClass and ensure these overheads
are accounted for in Kubernetes.
This page describes how kubelet managed Containers can use the Container lifecycle hook framework
to run code triggered by events during their management lifecycle.
Overview
Analogous to many programming language frameworks that have component lifecycle hooks, such as Angular,
Kubernetes provides Containers with lifecycle hooks.
The hooks enable Containers to be aware of events in their management lifecycle
and run code implemented in a handler when the corresponding lifecycle hook is executed.
Container hooks
There are two hooks that are exposed to Containers:
PostStart
This hook is executed immediately after a container is created.
However, there is no guarantee that the hook will execute before the container ENTRYPOINT.
No parameters are passed to the handler.
PreStop
This hook is called immediately before a container is terminated due to an API request or management
event such as a liveness/startup probe failure, preemption, resource contention and others. A call
to the PreStop hook fails if the container is already in a terminated or completed state and the
hook must complete before the TERM signal to stop the container can be sent. The Pod's termination
grace period countdown begins before the PreStop hook is executed, so regardless of the outcome of
the handler, the container will eventually terminate within the Pod's termination grace period. No
parameters are passed to the handler.
A more detailed description of the termination behavior can be found in
Termination of Pods.
StopSignal
The StopSignal lifecycle can be used to define a stop signal which would be sent to the container when it is
stopped. If you set this, it overrides any STOPSIGNAL instruction defined within the container image.
A more detailed description of termination behaviour with custom stop signals can be found in
Stop Signals.
Hook handler implementations
Containers can access a hook by implementing and registering a handler for that hook.
There are three types of hook handlers that can be implemented for Containers:
Exec - Executes a specific command, such as pre-stop.sh, inside the cgroups and namespaces of the Container.
Resources consumed by the command are counted against the Container.
HTTP - Executes an HTTP request against a specific endpoint on the Container.
Sleep - Pauses the container for a specified duration.
This is a beta-level feature default enabled by the PodLifecycleSleepActionfeature gate.
Note:
The beta level PodLifecycleSleepActionAllowZero feature gate which is enabled by default from v1.33.
It allows you to set a sleep duration of zero seconds (effectively a no-op) for your Sleep lifecycle hooks.
Hook handler execution
When a Container lifecycle management hook is called,
the Kubernetes management system executes the handler according to the hook action,
httpGet, tcpSocket (deprecated)
and sleep are executed by the kubelet process, and exec is executed in the container.
The PostStart hook handler call is initiated when a container is created,
meaning the container ENTRYPOINT and the PostStart hook are triggered simultaneously.
However, if the PostStart hook takes too long to execute or if it hangs,
it can prevent the container from transitioning to a running state.
PreStop hooks are not executed asynchronously from the signal to stop the Container; the hook must
complete its execution before the TERM signal can be sent. If a PreStop hook hangs during
execution, the Pod's phase will be Terminating and remain there until the Pod is killed after its
terminationGracePeriodSeconds expires. This grace period applies to the total time it takes for
both the PreStop hook to execute and for the Container to stop normally. If, for example,
terminationGracePeriodSeconds is 60, and the hook takes 55 seconds to complete, and the Container
takes 10 seconds to stop normally after receiving the signal, then the Container will be killed
before it can stop normally, since terminationGracePeriodSeconds is less than the total time
(55+10) it takes for these two things to happen.
If either a PostStart or PreStop hook fails,
it kills the Container.
Users should make their hook handlers as lightweight as possible.
There are cases, however, when long running commands make sense,
such as when saving state prior to stopping a Container.
Hook delivery guarantees
Hook delivery is intended to be at least once,
which means that a hook may be called multiple times for any given event,
such as for PostStart or PreStop.
It is up to the hook implementation to handle this correctly.
Generally, only single deliveries are made.
If, for example, an HTTP hook receiver is down and is unable to take traffic,
there is no attempt to resend.
In some rare cases, however, double delivery may occur.
For instance, if a kubelet restarts in the middle of sending a hook,
the hook might be resent after the kubelet comes back up.
Debugging Hook handlers
The logs for a Hook handler are not exposed in Pod events.
If a handler fails for some reason, it broadcasts an event.
For PostStart, this is the FailedPostStartHook event,
and for PreStop, this is the FailedPreStopHook event.
To generate a failed FailedPostStartHook event yourself, modify the
lifecycle-events.yaml
file to change the postStart command to "badcommand" and apply it.
Here is some example output of the resulting events you see from running kubectl describe pod lifecycle-demo:
Events:
Type Reason Age From Message
---- ------ ---- ---- -------
Normal Scheduled 7s default-scheduler Successfully assigned default/lifecycle-demo to ip-XXX-XXX-XX-XX.us-east-2...
Normal Pulled 6s kubelet Successfully pulled image "nginx" in 229.604315ms
Normal Pulling 4s (x2 over 6s) kubelet Pulling image "nginx"
Normal Created 4s (x2 over 5s) kubelet Created container lifecycle-demo-container
Normal Started 4s (x2 over 5s) kubelet Started container lifecycle-demo-container
Warning FailedPostStartHook 4s (x2 over 5s) kubelet Exec lifecycle hook ([badcommand]) for Container "lifecycle-demo-container" in Pod "lifecycle-demo_default(30229739-9651-4e5a-9a32-a8f1688862db)" failed - error: command 'badcommand' exited with 126: , message: "OCI runtime exec failed: exec failed: container_linux.go:380: starting container process caused: exec: \"badcommand\": executable file not found in $PATH: unknown\r\n"
Normal Killing 4s (x2 over 5s) kubelet FailedPostStartHook
Normal Pulled 4s kubelet Successfully pulled image "nginx" in 215.66395ms
Warning BackOff 2s (x2 over 3s) kubelet Back-off restarting failed container