Helm uses a packaging format called charts. A chart is a collection of files that describe a related set of Kubernetes resources. A single chart might be used to deploy something simple, like a memcached pod, or something complex, like a full web app stack with HTTP servers, databases, caches, and so on.
Charts are created as files laid out in a particular directory tree, then they can be packaged into versioned archives to be deployed.
This document explains the chart format, and provides basic guidance for building charts with Helm.
A chart is organized as a collection of files inside of a directory. The
directory name is the name of the chart (without versioning information). Thus,
a chart describing Wordpress would be stored in the wordpress/
directory.
Inside of this directory, Helm will expect a structure that matches this:
wordpress/
Chart.yaml # A YAML file containing information about the chart
LICENSE # OPTIONAL: A plain text file containing the license for the chart
README.md # OPTIONAL: A human-readable README file
values.yaml # The default configuration values for this chart
charts/ # OPTIONAL: A directory containing any charts upon which this chart depends.
templates/ # OPTIONAL: A directory of templates that, when combined with values,
# will generate valid Kubernetes manifest files.
templates/NOTES.txt # OPTIONAL: A plain text file containing short usage notes
Helm will silently strip out any other files.
The Chart.yaml
file is required for a chart. It contains the following fields:
name: The name of the chart (required)
version: A SemVer 2 version (required)
description: A single-sentence description of this project (optional)
keywords:
- A list of keywords about this project (optional)
home: The URL of this project's home page (optional)
sources:
- A list of URLs to source code for this project (optional)
maintainers: # (optional)
- name: The maintainer's name (required for each maintainer)
email: The maintainer's email (optional for each maintainer)
engine: gotpl # The name of the template engine (optional, defaults to gotpl)
If you are familiar with the Chart.yaml
file format for Helm Classic, you will
notice that fields specifying dependencies have been removed. That is because
the new Chart format expresses dependencies using the charts/
directory.
Other fields will be silently ignored.
Every chart must have a version number. A version must follow the SemVer 2 standard. Unlike Helm Classic, Kubernetes Helm uses version numbers as release markers. Packages in repositories are identified by name plus version.
For example, an nginx
chart whose version field is set to version: 1.2.3
will be named:
nginx-1.2.3.tgz
More complex SemVer 2 names are also supported, such as
version: 1.2.3-alpha.1+ef365
. But non-SemVer names are explicitly
disallowed by the system.
NOTE: Whereas Helm Classic and Deployment Manager were both very GitHub oriented when it came to charts, Kubernetes Helm does not rely upon or require GitHub or even Git. Consequently, it does not use Git SHAs for versioning at all.
The version
field inside of the Chart.yaml
is used by many of the
Helm tools, including the CLI and the Tiller server. When generating a
package, the helm package
command will use the version that it finds
in the Chart.yaml
as a token in the package name. The system assumes
that the version number in the chart package name matches the version number in
the Chart.yaml
. Failure to meet this assumption will cause an error.
Charts can also contain files that describe the installation, configuration, usage and license of a chart. A README for a chart should be formatted in Markdown (README.md), and should generally contain:
- A description of the application or service the chart provides
- Any prerequisites or requirements to run the chart
- Descriptions of options in
values.yaml
and default values - Any other information that may be relevant to the installation or configuration of the chart
The chart can also contain a short plain text templates/NOTES.txt
file that will be printed out
after installation, and when viewing the status of a release. This file is evaluated as a
template, and can be used to display usage notes, next steps, or any other
information relevant to a release of the chart. For example, instructions could be provided for
connecting to a database, or accessing a web UI. Since this file is printed to STDOUT when running
helm install
or helm status
, it is recommended to keep the content brief and point to the README
for greater detail.
In Helm, one chart may depend on any number of other charts. These
dependencies are expressed explicitly by copying the dependency charts
into the charts/
directory.
Note: The dependencies:
section of the Chart.yaml
from Helm
Classic has been completely removed.
For example, if the Wordpress chart depends on the Apache chart, the
Apache chart (of the correct version) is supplied in the Wordpress
chart's charts/
directory:
wordpress:
Chart.yaml
# ...
charts/
apache/
Chart.yaml
# ...
mysql/
Chart.yaml
# ...
The example above shows how the Wordpress chart expresses its dependency
on Apache and MySQL by including those charts inside of its charts/
directory.
TIP: To drop a dependency into your charts/
directory, use the
helm fetch
command.
By default, Helm Chart templates are written in the Go template language, with the addition of 50 or so add-on template functions. (In the future, Helm may support other template languages, like Python Jinja.)
All template files are stored in a chart's templates/
folder. When
Helm renders the charts, it will pass every file in that directory
through the template engine.
Values for the templates are supplied two ways:
- Chart developers may supply a file called
values.yaml
inside of a chart. This file can contain default values. - Chart users may supply a YAML file that contains values. This can be
provided on the command line with
helm install
.
When a user supplies custom values, these values will override the
values in the chart's values.yaml
file.
Template files follow the standard conventions for writing Go templates (see the text/template Go package documentation for details). An example template file might look something like this:
apiVersion: v1
kind: ReplicationController
metadata:
name: deis-database
namespace: deis
labels:
heritage: deis
spec:
replicas: 1
selector:
app: deis-database
template:
metadata:
labels:
app: deis-database
spec:
serviceAccount: deis-database
containers:
- name: deis-database
image: {{.imageRegistry}}/postgres:{{.dockerTag}}
imagePullPolicy: {{.pullPolicy}}
ports:
- containerPort: 5432
env:
- name: DATABASE_STORAGE
value: {{default "minio" .storage}}
The above example, based loosely on https://github.com/deis/charts, is a template for a Kubernetes replication controller. It can use the following four template values:
imageRegistry
: The source registry for the Docker image.dockerTag
: The tag for the docker image.pullPolicy
: The Kubernetes pull policy.storage
: The storage backend, whose default is set to"minio"
All of these values are defined by the template author. Helm does not require or dictate parameters.
The following values are pre-defined, are available to every template, and cannot be overridden. As with all values, the names are case sensitive.
Release.Name
: The name of the release (not the chart)Release.Time
: The time the chart release was last updated. This will match theLast Released
time on a Release object.Release.Namespace
: The namespace the chart was released to.Release.Service
: The service that conducted the release. Usually this isTiller
.Chart
: The contents of theChart.yaml
. Thus, the chart version is obtainable asChart.Version
and the maintainers are inChart.Maintainers
.Files
: A map-like object containing all non-special files in the chart. This will not give you access to templates, but will give you access to additional files that are present. Files can be accessed using{{index .Files "file.name"}}
or using the{{.Files.Get name}}
or{{.Files.GetString name}}
functions. Note that file data is returned as a[]byte
unless{{.Files.GetString}}
is used.
NOTE: Any unknown Chart.yaml fields will be dropped. They will not
be accessible inside of the Chart
object. Thus, Chart.yaml cannot be
used to pass arbitrarily structured data into the template.
Considering the template in the previous section, a values.yaml
file
that supplies the necessary values would look like this:
imageRegistry: "quay.io/deis"
dockerTag: "latest"
pullPolicy: "alwaysPull"
storage: "s3"
A values file is formatted in YAML. A chart may include a default
values.yaml
file. The Helm install command allows a user to override
values by supplying additional YAML values:
$ helm install --values=myvals.yaml wordpress
When values are passed in this way, they will be merged into the default
values file. For example, consider a myvals.yaml
file that looks like
this:
storage: "gcs"
When this is merged with the values.yaml
in the chart, the resulting
generated content will be:
imageRegistry: "quay.io/deis"
dockerTag: "latest"
pullPolicy: "alwaysPull"
storage: "gcs"
Note that only the last field was overridden.
NOTE: The default values file included inside of a chart must be named
values.yaml
. But files specified on the command line can be named
anything.
Values files can declare values for the top-level chart, as well as for
any of the charts that are included in that chart's charts/
directory.
Or, to phrase it differently, a values file can supply values to the
chart as well as to any of its dependencies. For example, the
demonstration Wordpress chart above has both mysql
and apache
as
dependencies. The values file could supply values to all of these
components:
title: "My Wordpress Site" # Sent to the Wordpress template
mysql:
max_connections: 100 # Sent to MySQL
password: "secret"
apache:
port: 8080 # Passed to Apache
Charts at a higher level have access to all of the variables defined
beneath. So the wordpress chart can access .mysql.password
. But lower
level charts cannot access things in parent charts, so MySQL will not be
able to access the title
property. Nor, for that matter, can it access
.apache.port
.
Values are namespaced, but namespaces are pruned. So for the Wordpress
chart, it can access the MySQL password field as .mysql.password
. But
for the MySQL chart, the scope of the values has been reduced and the
namespace prefix removed, so it will see the password field simply as
.password
.
As of 2.0.0-Alpha.2, Helm supports special "global" value. Consider this modified version of the previous example:
title: "My Wordpress Site" # Sent to the Wordpress template
global:
app: MyWordpress
mysql:
max_connections: 100 # Sent to MySQL
password: "secret"
apache:
port: 8080 # Passed to Apache
The above adds a global
section with the value app: MyWordpress
.
This value is available to all charts as .Values.global.app
.
For example, the mysql
templates may access app
as {{.Values.global.app}}
, and
so can the apache
chart. Effectively, the values file above is
regenerated like this:
title: "My Wordpress Site" # Sent to the Wordpress template
global:
app: MyWordpress
mysql:
global:
app: MyWordpress
max_connections: 100 # Sent to MySQL
password: "secret"
apache:
global:
app: MyWordpress
port: 8080 # Passed to Apache
This provides a way of sharing one top-level variable with all
subcharts, which is useful for things like setting metadata
properties
like labels.
If a subchart declares a global variable, that global will be passed downward (to the subchart's subcharts), but not upward to the parent chart. There is no way for a subchart to influence the values of the parent chart.
Global sections are restricted to only simple key/value pairs. They do not support nesting.
For example, the following is illegal and will not work:
global:
foo: # It is illegal to nest an object inside of global.
bar: baz
When it comes to writing templates and values files, there are several standard references that will help you out.
Helm provides a hook mechanism to allow chart developers to intervene at certain points in a release's life cycle. For example, you can use hooks to:
- Load a ConfigMap or Secret during install before any other charts are loaded.
- Execute a Job to backup up a database before installing a new chart, and then execute a second job after the upgrade in order to restore data.
- Run a Job before deleting a release to gracefully take a service out of rotation before removing it.
Hooks work like regular templates, but they have special annotations that cause Helm to utilize them differently. In this section, we cover the basic usage pattern for hooks.
The following hooks are defined:
- pre-install: Executes after templates are rendered, but before any resources are created in Kubernetes.
- post-install: Executes after all resources are loaded into Kubernetes
- pre-delete: Executes on a deletion request before any resources are deleted from Kubernetes.
- post-delete: Executes on a deletion request after all of the release's resources have been deleted.
- pre-upgrade: Executes on an upgrade request after templates are rendered, but before any resources are loaded into Kubernetes (e.g. before a kuberntes apply operation).
- post-upgrade: Executes on an upgrade after all resources have been upgraded.
Hooks allow you, the chart developer, an opportunity to perform
operations at strategic points in a release lifecycle. For example,
consider the lifecycle for a helm install
. By default, the lifecycle
looks like this:
- User runs
helm install foo
- Chart is loaded into Tiller
- After some verification, Tiller renders the
foo
templates - Tiller loads the resulting resources into Kubernetes
- Tiller returns the release name (and other data) to the client
- The client exits
Helm defines two hooks for the install
lifecycle: pre-install
and
post-install
. If the developer of the foo
chart implements both
hooks, the lifecycle is altered like this:
- User runs
helm install foo
- Chart is loaded into Tiller
- After some verification, Tiller renders the
foo
templates - Tiller executes the
pre-install
hook (loading hook resources into Kubernetes) - Tiller waits until the hook is "Ready"
- Tiller loads the resulting resources into Kubernetes
- Tiller executes the
post-install
hook (loading hook resources) - Tiller waits until the hook is "Ready"
- Tiller returns the release name (and other data) to the client
- The client exits
What does it mean to wait until a hook is ready? This depends on the
resource declared in the hook. If the resources is a Job
kind, Tiller
will wait until the job successfully runs to completion. And if the job
fails, the release will fail. This is a blocking operation, so the
Helm client will pause while the Job is run.
For all other kinds, as soon as Kubernetes marks the resource as loaded (added or updated), the resource is considered "Ready". When many resources are declared in a hook, the resources are executed serially, but the order of their execution is not guaranteed.
The resources that a hook creates are not tracked or managed as part of the release. Once Tiller verifies that the hook has reached its ready state, it will leave the hook resource alone.
Practically speaking, this means that if you create resources in a hook, you
cannot rely upon helm delete
to remove the resources. To destroy such
resources, you need to write code to perform this operation in a pre-delete
or post-delete
hook.
Hooks are just Kubernetes manfiest files with special annotations in the
metadata
section. Because they are template files, you can use all of
the normal template features, including reading .Values
, .Release
,
and .Template
.
For example, this template, stored in templates/post-install-job.yaml
,
declares a job to be run on post-install
:
apiVersion: batch/v1
kind: Job
metadata:
name: "{{.Release.Name}}"
labels:
heritage: {{.Release.Service | quote }}
release: {{.Release.Name | quote }}
chart: "{{.Chart.Name}}-{{.Chart.Version}}"
annotations:
# This is what defines this resource as a hook. Without this line, the
# job is considered part of the release.
"helm.sh/hook": post-install
spec:
template:
metadata:
name: "{{.Release.Name}}"
labels:
heritage: {{.Release.Service | quote }}
release: {{.Release.Name | quote }}
chart: "{{.Chart.Name}}-{{.Chart.Version}}"
spec:
restartPolicy: Never
containers:
- name: post-install-job
image: "alpine:3.3"
command: ["/bin/sleep","{{default "10" .Values.sleepyTime}}"]
What makes this template a hook is the annotation:
annotations:
"helm.sh/hook": post-install
One resource can implement multiple hooks:
annotations:
"helm.sh/hook": post-install,post-upgrade
Similarly, there is no limit to the number of different resources that may implement a given hook. For example, one could declare both a secret as a config map as a pre-install hook. It is important to keep in mind, though, that there are no ordering guarantees about hooks.
When subcharts declare hooks, those are also evaluated. There is no way for a top-level chart to disable the hooks declared by subcharts. And again, there is no guaranteed ordering.
The helm
tool has several commands for working with charts.
It can create a new chart for you:
$ helm create mychart
Created mychart/
Once you have edited a chart, helm
can package it into a chart archive
for you:
$ helm package mychart
Archived mychart-0.1.-.tgz
You can also use helm
to help you find issues with your chart's
formatting or information:
$ helm lint mychart
No issues found
A chart repository is an HTTP server that houses one or more packaged
charts. While helm
can be used to manage local chart directories, when
it comes to sharing charts, the preferred mechanism is a chart
repository.
Any HTTP server that can serve YAML files and tar files and can answer GET requests can be used as a repository server.
Helm comes with built-in package server for developer testing (helm serve
). The Helm team has tested other servers, including Google Cloud
Storage with website mode enabled, and S3 with website mode enabled.
A repository is characterized primarily by the presence of a special
file called index.yaml
that has a list of all of the packages supplied
by the repository, together with metadata that allows retrieving and
verifying those packages.
On the client side, repositories are managed with the helm repo
commands. However, Helm does not provide tools for uploading charts to
remote repository servers. This is because doing so would add
substantial requirements to an implementing server, and thus raise the
barrier for setting up a repository.