This guide outlines the packaging format for Operators supported by Operator Lifecycle Manager (OLM) in OpenShift Container Platform.

Bundle format

The bundle format for Operators is a packaging format introduced by the Operator Framework. To improve scalability and to better enable upstream users hosting their own catalogs, the bundle format specification simplifies the distribution of Operator metadata.

An Operator bundle represents a single version of an Operator. On-disk bundle manifests are containerized and shipped as a bundle image, which is a non-runnable container image that stores the Kubernetes manifests and Operator metadata. Storage and distribution of the bundle image is then managed using existing container tools like podman and docker and container registries such as Quay.

Operator metadata can include:

  • Information that identifies the Operator, for example its name and version.

  • Additional information that drives the UI, for example its icon and some example custom resources (CRs).

  • Required and provided APIs.

  • Related images.

When loading manifests into the Operator Registry database, the following requirements are validated:

  • The bundle must have at least one channel defined in the annotations.

  • Every bundle has exactly one cluster service version (CSV).

  • If a CSV owns a custom resource definition (CRD), that CRD must exist in the bundle.


Bundle manifests refer to a set of Kubernetes manifests that define the deployment and RBAC model of the Operator.

A bundle includes one CSV per directory and typically the CRDs that define the owned APIs of the CSV in its /manifests directory.

Example bundle format layout
├── manifests
│   ├── etcdcluster.crd.yaml
│   └── etcdoperator.clusterserviceversion.yaml
│   └── secret.yaml
│   └── configmap.yaml
└── metadata
    └── annotations.yaml
    └── dependencies.yaml

Additionally supported objects

The following object types can also be optionally included in the /manifests directory of a bundle:

Supported optional object types
  • ClusterRole

  • ClusterRoleBinding

  • ConfigMap

  • ConsoleCLIDownload

  • ConsoleLink

  • ConsoleQuickStart

  • ConsoleYamlSample

  • PodDisruptionBudget

  • PriorityClass

  • PrometheusRule

  • Role

  • RoleBinding

  • Secret

  • Service

  • ServiceAccount

  • ServiceMonitor

  • VerticalPodAutoscaler

When these optional objects are included in a bundle, Operator Lifecycle Manager (OLM) can create them from the bundle and manage their lifecycle along with the CSV:

Lifecycle for optional objects
  • When the CSV is deleted, OLM deletes the optional object.

  • When the CSV is upgraded:

    • If the name of the optional object is the same, OLM updates it in place.

    • If the name of the optional object has changed between versions, OLM deletes and recreates it.


A bundle also includes an annotations.yaml file in its /metadata directory. This file defines higher level aggregate data that helps describe the format and package information about how the bundle should be added into an index of bundles:

Example annotations.yaml
  operators.operatorframework.io.bundle.mediatype.v1: "registry+v1" (1)
  operators.operatorframework.io.bundle.manifests.v1: "manifests/" (2)
  operators.operatorframework.io.bundle.metadata.v1: "metadata/" (3)
  operators.operatorframework.io.bundle.package.v1: "test-operator" (4)
  operators.operatorframework.io.bundle.channels.v1: "beta,stable" (5)
  operators.operatorframework.io.bundle.channel.default.v1: "stable" (6)
1 The media type or format of the Operator bundle. The registry+v1 format means it contains a CSV and its associated Kubernetes objects.
2 The path in the image to the directory that contains the Operator manifests. This label is reserved for future use and currently defaults to manifests/. The value manifests.v1 implies that the bundle contains Operator manifests.
3 The path in the image to the directory that contains metadata files about the bundle. This label is reserved for future use and currently defaults to metadata/. The value metadata.v1 implies that this bundle has Operator metadata.
4 The package name of the bundle.
5 The list of channels the bundle is subscribing to when added into an Operator Registry.
6 The default channel an Operator should be subscribed to when installed from a registry.

In case of a mismatch, the annotations.yaml file is authoritative because the on-cluster Operator Registry that relies on these annotations only has access to this file.


The dependencies of an Operator are listed in a dependencies.yaml file in the metadata/ folder of a bundle. This file is optional and currently only used to specify explicit Operator-version dependencies.

The dependency list contains a type field for each item to specify what kind of dependency this is. The following types of Operator dependencies are supported:


This type indicates a dependency for a specific Operator version. The dependency information must include the package name and the version of the package in semver format. For example, you can specify an exact version such as 0.5.2 or a range of versions such as >0.5.1.


With this type, the author can specify a dependency with group/version/kind (GVK) information, similar to existing CRD and API-based usage in a CSV. This is a path to enable Operator authors to consolidate all dependencies, API or explicit versions, to be in the same place.


This type declares generic constraints on arbitrary Operator properties.

In the following example, dependencies are specified for a Prometheus Operator and etcd CRDs:

Example dependencies.yaml file
  - type: olm.package
      packageName: prometheus
      version: ">0.27.0"
  - type: olm.gvk
      group: etcd.database.coreos.com
      kind: EtcdCluster
      version: v1beta2

About the opm CLI

The opm CLI tool is provided by the Operator Framework for use with the Operator bundle format. This tool allows you to create and maintain catalogs of Operators from a list of Operator bundles that are similar to software repositories. The result is a container image which can be stored in a container registry and then installed on a cluster.

A catalog contains a database of pointers to Operator manifest content that can be queried through an included API that is served when the container image is run. On OpenShift Container Platform, Operator Lifecycle Manager (OLM) can reference the image in a catalog source, defined by a CatalogSource object, which polls the image at regular intervals to enable frequent updates to installed Operators on the cluster.

  • See CLI tools for steps on installing the opm CLI.

File-based catalogs

File-based catalogs are the latest iteration of the catalog format in Operator Lifecycle Manager (OLM). It is a plain text-based (JSON or YAML) and declarative config evolution of the earlier SQLite database format, and it is fully backwards compatible. The goal of this format is to enable Operator catalog editing, composability, and extensibility.


With file-based catalogs, users interacting with the contents of a catalog are able to make direct changes to the format and verify that their changes are valid. Because this format is plain text JSON or YAML, catalog maintainers can easily manipulate catalog metadata by hand or with widely known and supported JSON or YAML tooling, such as the jq CLI.

This editability enables the following features and user-defined extensions:

  • Promoting an existing bundle to a new channel

  • Changing the default channel of a package

  • Custom algorithms for adding, updating, and removing upgrade edges


File-based catalogs are stored in an arbitrary directory hierarchy, which enables catalog composition. For example, consider two separate file-based catalog directories: catalogA and catalogB. A catalog maintainer can create a new combined catalog by making a new directory catalogC and copying catalogA and catalogB into it.

This composability enables decentralized catalogs. The format permits Operator authors to maintain Operator-specific catalogs, and it permits maintainers to trivially build a catalog composed of individual Operator catalogs. File-based catalogs can be composed by combining multiple other catalogs, by extracting subsets of one catalog, or a combination of both of these.

Duplicate packages and duplicate bundles within a package are not permitted. The opm validate command returns an error if any duplicates are found.

Because Operator authors are most familiar with their Operator, its dependencies, and its upgrade compatibility, they are able to maintain their own Operator-specific catalog and have direct control over its contents. With file-based catalogs, Operator authors own the task of building and maintaining their packages in a catalog. Composite catalog maintainers, however, only own the task of curating the packages in their catalog and publishing the catalog to users.


The file-based catalog specification is a low-level representation of a catalog. While it can be maintained directly in its low-level form, catalog maintainers can build interesting extensions on top that can be used by their own custom tooling to make any number of mutations.

For example, a tool could translate a high-level API, such as (mode=semver), down to the low-level, file-based catalog format for upgrade edges. Or a catalog maintainer might need to customize all of the bundle metadata by adding a new property to bundles that meet a certain criteria.

While this extensibility allows for additional official tooling to be developed on top of the low-level APIs for future OpenShift Container Platform releases, the major benefit is that catalog maintainers have this capability as well.

As of OpenShift Container Platform 4.11, the default Red Hat-provided Operator catalog releases in the file-based catalog format. The default Red Hat-provided Operator catalogs for OpenShift Container Platform 4.6 through 4.10 released in the deprecated SQLite database format.

The opm subcommands, flags, and functionality related to the SQLite database format are also deprecated and will be removed in a future release. The features are still supported and must be used for catalogs that use the deprecated SQLite database format.

Many of the opm subcommands and flags for working with the SQLite database format, such as opm index prune, do not work with the file-based catalog format. For more information about working with file-based catalogs, see Managing custom catalogs and Mirroring images for a disconnected installation using the oc-mirror plugin.

Directory structure

File-based catalogs can be stored and loaded from directory-based file systems. The opm CLI loads the catalog by walking the root directory and recursing into subdirectories. The CLI attempts to load every file it finds and fails if any errors occur.

Non-catalog files can be ignored using .indexignore files, which have the same rules for patterns and precedence as .gitignore files.

Example .indexignore file
# Ignore everything except non-object .json and .yaml files

Catalog maintainers have the flexibility to choose their desired layout, but it is recommended to store each package’s file-based catalog blobs in separate subdirectories. Each individual file can be either JSON or YAML; it is not necessary for every file in a catalog to use the same format.

Basic recommended structure
├── packageA
│   └── index.yaml
├── packageB
│   ├── .indexignore
│   ├── index.yaml
│   └── objects
│       └── packageB.v0.1.0.clusterserviceversion.yaml
└── packageC
    └── index.json
    └── deprecations.yaml

This recommended structure has the property that each subdirectory in the directory hierarchy is a self-contained catalog, which makes catalog composition, discovery, and navigation trivial file system operations. The catalog can also be included in a parent catalog by copying it into the parent catalog’s root directory.


File-based catalogs use a format, based on the CUE language specification, that can be extended with arbitrary schemas. The following _Meta CUE schema defines the format that all file-based catalog blobs must adhere to:

_Meta schema
_Meta: {
  // schema is required and must be a non-empty string
  schema: string & !=""

  // package is optional, but if it's defined, it must be a non-empty string
  package?: string & !=""

  // properties is optional, but if it's defined, it must be a list of 0 or more properties
  properties?: [... #Property]

#Property: {
  // type is required
  type: string & !=""

  // value is required, and it must not be null
  value: !=null

No CUE schemas listed in this specification should be considered exhaustive. The opm validate command has additional validations that are difficult or impossible to express concisely in CUE.

An Operator Lifecycle Manager (OLM) catalog currently uses three schemas (olm.package, olm.channel, and olm.bundle), which correspond to OLM’s existing package and bundle concepts.

Each Operator package in a catalog requires exactly one olm.package blob, at least one olm.channel blob, and one or more olm.bundle blobs.

All olm.* schemas are reserved for OLM-defined schemas. Custom schemas must use a unique prefix, such as a domain that you own.

olm.package schema

The olm.package schema defines package-level metadata for an Operator. This includes its name, description, default channel, and icon.

olm.package schema
#Package: {
  schema: "olm.package"

  // Package name
  name: string & !=""

  // A description of the package
  description?: string

  // The package's default channel
  defaultChannel: string & !=""

  // An optional icon
  icon?: {
    base64data: string
    mediatype:  string

olm.channel schema

The olm.channel schema defines a channel within a package, the bundle entries that are members of the channel, and the upgrade edges for those bundles.

If a bundle entry represents an edge in multiple olm.channel blobs, it can only appear once per channel.

It is valid for an entry’s replaces value to reference another bundle name that cannot be found in this catalog or another catalog. However, all other channel invariants must hold true, such as a channel not having multiple heads.

olm.channel schema
#Channel: {
  schema: "olm.channel"
  package: string & !=""
  name: string & !=""
  entries: [...#ChannelEntry]

#ChannelEntry: {
  // name is required. It is the name of an `olm.bundle` that
  // is present in the channel.
  name: string & !=""

  // replaces is optional. It is the name of bundle that is replaced
  // by this entry. It does not have to be present in the entry list.
  replaces?: string & !=""

  // skips is optional. It is a list of bundle names that are skipped by
  // this entry. The skipped bundles do not have to be present in the
  // entry list.
  skips?: [...string & !=""]

  // skipRange is optional. It is the semver range of bundle versions
  // that are skipped by this entry.
  skipRange?: string & !=""

When using the skipRange field, the skipped Operator versions are pruned from the update graph and are longer installable by users with the spec.startingCSV property of Subscription objects.

You can update an Operator incrementally while keeping previously installed versions available to users for future installation by using both the skipRange and replaces field. Ensure that the replaces field points to the immediate previous version of the Operator version in question.

olm.bundle schema

olm.bundle schema
#Bundle: {
  schema: "olm.bundle"
  package: string & !=""
  name: string & !=""
  image: string & !=""
  properties: [...#Property]
  relatedImages?: [...#RelatedImage]

#Property: {
  // type is required
  type: string & !=""

  // value is required, and it must not be null
  value: !=null

#RelatedImage: {
  // image is the image reference
  image: string & !=""

  // name is an optional descriptive name for an image that
  // helps identify its purpose in the context of the bundle
  name?: string & !=""

olm.deprecations schema

The optional olm.deprecations schema defines deprecation information for packages, bundles, and channels in a catalog. Operator authors can use this schema to provide relevant messages about their Operators, such as support status and recommended upgrade paths, to users running those Operators from a catalog.

An olm.deprecations schema entry contains one or more of the following reference types, which indicates the deprecation scope. After the Operator is installed, any specified messages can be viewed as status conditions on the related Subscription object.

Table 1. Deprecation reference types
Type Scope Status condition


Represents the entire package



Represents one channel



Represents one bundle version


Each reference type has their own requirements, as detailed in the following example.

Example olm.deprecations schema with each reference type
schema: olm.deprecations
package: my-operator (1)
  - reference:
      schema: olm.package (2)
    message: | (3)
    The 'my-operator' package is end of life. Please use the
    'my-operator-new' package for support.
  - reference:
      schema: olm.channel
      name: alpha (4)
    message: |
    The 'alpha' channel is no longer supported. Please switch to the
    'stable' channel.
  - reference:
      schema: olm.bundle
      name: my-operator.v1.68.0 (5)
    message: |
    my-operator.v1.68.0 is deprecated. Uninstall my-operator.v1.68.0 and
    install my-operator.v1.72.0 for support.
1 Each deprecation schema must have a package value, and that package reference must be unique across the catalog. There must not be an associated name field.
2 The olm.package schema must not include a name field, because it is determined by the package field defined earlier in the schema.
3 All message fields, for any reference type, must be a non-zero length and represented as an opaque text blob.
4 The name field for the olm.channel schema is required.
5 The name field for the olm.bundle schema is required.

The deprecation feature does not consider overlapping deprecation, for example package versus channel versus bundle.

Operator authors can save olm.deprecations schema entries as a deprecations.yaml file in the same directory as the package’s index.yaml file:

Example directory structure for a catalog with deprecations
└── my-operator
    ├── index.yaml
    └── deprecations.yaml


Properties are arbitrary pieces of metadata that can be attached to file-based catalog schemas. The type field is a string that effectively specifies the semantic and syntactic meaning of the value field. The value can be any arbitrary JSON or YAML.

OLM defines a handful of property types, again using the reserved olm.* prefix.

olm.package property

The olm.package property defines the package name and version. This is a required property on bundles, and there must be exactly one of these properties. The packageName field must match the bundle’s first-class package field, and the version field must be a valid semantic version.

olm.package property
#PropertyPackage: {
  type: "olm.package"
  value: {
    packageName: string & !=""
    version: string & !=""

olm.gvk property

The olm.gvk property defines the group/version/kind (GVK) of a Kubernetes API that is provided by this bundle. This property is used by OLM to resolve a bundle with this property as a dependency for other bundles that list the same GVK as a required API. The GVK must adhere to Kubernetes GVK validations.

olm.gvk property
#PropertyGVK: {
  type: "olm.gvk"
  value: {
    group: string & !=""
    version: string & !=""
    kind: string & !=""


The olm.package.required property defines the package name and version range of another package that this bundle requires. For every required package property a bundle lists, OLM ensures there is an Operator installed on the cluster for the listed package and in the required version range. The versionRange field must be a valid semantic version (semver) range.

olm.package.required property
#PropertyPackageRequired: {
  type: "olm.package.required"
  value: {
    packageName: string & !=""
    versionRange: string & !=""


The olm.gvk.required property defines the group/version/kind (GVK) of a Kubernetes API that this bundle requires. For every required GVK property a bundle lists, OLM ensures there is an Operator installed on the cluster that provides it. The GVK must adhere to Kubernetes GVK validations.

olm.gvk.required property
#PropertyGVKRequired: {
  type: "olm.gvk.required"
  value: {
    group: string & !=""
    version: string & !=""
    kind: string & !=""

Example catalog

With file-based catalogs, catalog maintainers can focus on Operator curation and compatibility. Because Operator authors have already produced Operator-specific catalogs for their Operators, catalog maintainers can build their catalog by rendering each Operator catalog into a subdirectory of the catalog’s root directory.

There are many possible ways to build a file-based catalog; the following steps outline a simple approach:

  1. Maintain a single configuration file for the catalog, containing image references for each Operator in the catalog:

    Example catalog configuration file
    name: community-operators
    repo: quay.io/community-operators/catalog
    tag: latest
    - name: etcd-operator
      image: quay.io/etcd-operator/index@sha256:5891b5b522d5df086d0ff0b110fbd9d21bb4fc7163af34d08286a2e846f6be03
    - name: prometheus-operator
      image: quay.io/prometheus-operator/index@sha256:e258d248fda94c63753607f7c4494ee0fcbe92f1a76bfdac795c9d84101eb317
  2. Run a script that parses the configuration file and creates a new catalog from its references:

    Example script
    name=$(yq eval '.name' catalog.yaml)
    mkdir "$name"
    yq eval '.name + "/" + .references[].name' catalog.yaml | xargs mkdir
    for l in $(yq e '.name as $catalog | .references[] | .image + "|" + $catalog + "/" + .name + "/index.yaml"' catalog.yaml); do
      image=$(echo $l | cut -d'|' -f1)
      file=$(echo $l | cut -d'|' -f2)
      opm render "$image" > "$file"
    opm generate dockerfile "$name"
    indexImage=$(yq eval '.repo + ":" + .tag' catalog.yaml)
    docker build -t "$indexImage" -f "$name.Dockerfile" .
    docker push "$indexImage"


Consider the following guidelines when maintaining file-based catalogs.

Immutable bundles

The general advice with Operator Lifecycle Manager (OLM) is that bundle images and their metadata should be treated as immutable.

If a broken bundle has been pushed to a catalog, you must assume that at least one of your users has upgraded to that bundle. Based on that assumption, you must release another bundle with an upgrade edge from the broken bundle to ensure users with the broken bundle installed receive an upgrade. OLM will not reinstall an installed bundle if the contents of that bundle are updated in the catalog.

However, there are some cases where a change in the catalog metadata is preferred:

  • Channel promotion: If you already released a bundle and later decide that you would like to add it to another channel, you can add an entry for your bundle in another olm.channel blob.

  • New upgrade edges: If you release a new 1.2.z bundle version, for example 1.2.4, but 1.3.0 is already released, you can update the catalog metadata for 1.3.0 to skip 1.2.4.

Source control

Catalog metadata should be stored in source control and treated as the source of truth. Updates to catalog images should include the following steps:

  1. Update the source-controlled catalog directory with a new commit.

  2. Build and push the catalog image. Use a consistent tagging taxonomy, such as :latest or :<target_cluster_version>, so that users can receive updates to a catalog as they become available.

CLI usage

For instructions about creating file-based catalogs by using the opm CLI, see Managing custom catalogs.

For reference documentation about the opm CLI commands related to managing file-based catalogs, see CLI tools.


Operator authors and catalog maintainers are encouraged to automate their catalog maintenance with CI/CD workflows. Catalog maintainers can further improve on this by building GitOps automation to accomplish the following tasks:

  • Check that pull request (PR) authors are permitted to make the requested changes, for example by updating their package’s image reference.

  • Check that the catalog updates pass the opm validate command.

  • Check that the updated bundle or catalog image references exist, the catalog images run successfully in a cluster, and Operators from that package can be successfully installed.

  • Automatically merge PRs that pass the previous checks.

  • Automatically rebuild and republish the catalog image.

RukPak (Technology Preview)

RukPak is a Technology Preview feature only. Technology Preview features are not supported with Red Hat production service level agreements (SLAs) and might not be functionally complete. Red Hat does not recommend using them in production. These features provide early access to upcoming product features, enabling customers to test functionality and provide feedback during the development process.

For more information about the support scope of Red Hat Technology Preview features, see Technology Preview Features Support Scope.

OpenShift Container Platform 4.12 introduces the platform Operator type as a Technology Preview feature. The platform Operator mechanism relies on the RukPak component, also introduced in OpenShift Container Platform 4.12, and its resources to manage content.

OpenShift Container Platform 4.14 introduces Operator Lifecycle Manager (OLM) 1.0 as a Technology Preview feature, which also relies on the RukPak component.

RukPak is a pluggable solution for packaging and distributing cloud-native content. It supports advanced strategies for installation, updates, and policy.

RukPak provides a content ecosystem for installing a variety of artifacts on a Kubernetes cluster. Artifact examples include Git repositories, Helm charts, and OLM bundles. RukPak can then manage, scale, and upgrade these artifacts in a safe way to enable powerful cluster extensions.

At its core, RukPak is a small set of APIs and controllers. The APIs are packaged as custom resource definitions (CRDs) that express what content to install on a cluster and how to create a running deployment of the content. The controllers watch for the APIs.

Common terminology

A collection of Kubernetes manifests that define content to be deployed to a cluster

Bundle image

A container image that contains a bundle within its filesystem

Bundle Git repository

A Git repository that contains a bundle within a directory


Controllers that install and manage content on a Kubernetes cluster

Bundle deployment

Generates deployed instances of a bundle


A RukPak Bundle object represents content to make available to other consumers in the cluster. Much like the contents of a container image must be pulled and unpacked in order for pod to start using them, Bundle objects are used to reference content that might need to be pulled and unpacked. In this sense, a bundle is a generalization of the image concept and can be used to represent any type of content.

Bundles cannot do anything on their own; they require a provisioner to unpack and make their content available in the cluster. They can be unpacked to any arbitrary storage medium, such as a tar.gz file in a directory mounted into the provisioner pods. Each Bundle object has an associated spec.provisionerClassName field that indicates the Provisioner object that watches and unpacks that particular bundle type.

Example Bundle object configured to work with the plain provisioner
apiVersion: core.rukpak.io/v1alpha1
kind: Bundle
  name: my-bundle
    type: image
      ref: my-bundle@sha256:xyz123
  provisionerClassName: core-rukpak-io-plain

Bundles are considered immutable after they are created.

Bundle immutability

After a Bundle object is accepted by the API server, the bundle is considered an immutable artifact by the rest of the RukPak system. This behavior enforces the notion that a bundle represents some unique, static piece of content to source onto the cluster. A user can have confidence that a particular bundle is pointing to a specific set of manifests and cannot be updated without creating a new bundle. This property is true for both standalone bundles and dynamic bundles created by an embedded BundleTemplate object.

Bundle immutability is enforced by the core RukPak webhook. This webhook watches Bundle object events and, for any update to a bundle, checks whether the spec field of the existing bundle is semantically equal to that in the proposed updated bundle. If they are not equal, the update is rejected by the webhook. Other Bundle object fields, such as metadata or status, are updated during the bundle’s lifecycle; it is only the spec field that is considered immutable.

Applying a Bundle object and then attempting to update its spec should fail. For example, the following example creates a bundle:

$ oc apply -f -<<EOF
apiVersion: core.rukpak.io/v1alpha1
kind: Bundle
  name: combo-tag-ref
    type: git
        tag: v0.0.2
      repository: https://github.com/operator-framework/combo
  provisionerClassName: core-rukpak-io-plain
Example output
bundle.core.rukpak.io/combo-tag-ref created

Then, patching the bundle to point to a newer tag returns an error:

$ oc patch bundle combo-tag-ref --type='merge' -p '{"spec":{"source":{"git":{"ref":{"tag":"v0.0.3"}}}}}'
Example output
Error from server (bundle.spec is immutable): admission webhook "vbundles.core.rukpak.io" denied the request: bundle.spec is immutable

The core RukPak admission webhook rejected the patch because the spec of the bundle is immutable. The recommended method to change the content of a bundle is by creating a new Bundle object instead of updating it in-place.

Further immutability considerations

While the spec field of the Bundle object is immutable, it is still possible for a BundleDeployment object to pivot to a newer version of bundle content without changing the underlying spec field. This unintentional pivoting could occur in the following scenario:

  1. A user sets an image tag, a Git branch, or a Git tag in the spec.source field of the Bundle object.

  2. The image tag moves to a new digest, a user pushes changes to a Git branch, or a user deletes and re-pushes a Git tag on a different commit.

  3. A user does something to cause the bundle unpack pod to be re-created, such as deleting the unpack pod.

If this scenario occurs, the new content from step 2 is unpacked as a result of step 3. The bundle deployment detects the changes and pivots to the newer version of the content.

This is similar to pod behavior, where one of the pod’s container images uses a tag, the tag is moved to a different digest, and then at some point in the future the existing pod is rescheduled on a different node. At that point, the node pulls the new image at the new digest and runs something different without the user explicitly asking for it.

To be confident that the underlying Bundle spec content does not change, use a digest-based image or a Git commit reference when creating the bundle.

Plain bundle spec

A plain bundle in RukPak is a collection of static, arbitrary, Kubernetes YAML manifests in a given directory.

The currently implemented plain bundle format is the plain+v0 format. The name of the bundle format, plain+v0, combines the type of bundle (plain) with the current schema version (v0).

The plain+v0 bundle format is at schema version v0, which means it is an experimental format that is subject to change.

For example, the following shows the file tree in a plain+v0 bundle. It must have a manifests/ directory containing the Kubernetes resources required to deploy an application.

Example plain+v0 bundle file tree
$ tree manifests

├── namespace.yaml
├── service_account.yaml
├── cluster_role.yaml
├── cluster_role_binding.yaml
└── deployment.yaml

The static manifests must be located in the manifests/ directory with at least one resource in it for the bundle to be a valid plain+v0 bundle that the provisioner can unpack. The manifests/ directory must also be flat; all manifests must be at the top-level with no subdirectories.

Do not include any content in the manifests/ directory of a plain bundle that are not static manifests. Otherwise, a failure will occur when creating content on-cluster from that bundle. Any file that would not successfully apply with the oc apply command will result in an error. Multi-object YAML or JSON files are valid, as well.

Registry bundle spec

A registry bundle, or registry+v1 bundle, contains a set of static Kubernetes YAML manifests organized in the legacy Operator Lifecycle Manager (OLM) bundle format.

Additional resources


A BundleDeployment object changes the state of a Kubernetes cluster by installing and removing objects. It is important to verify and trust the content that is being installed and limit access, by using RBAC, to the BundleDeployment API to only those who require those permissions.

The RukPak BundleDeployment API points to a Bundle object and indicates that it should be active. This includes pivoting from older versions of an active bundle. A BundleDeployment object might also include an embedded spec for a desired bundle.

Much like pods generate instances of container images, a bundle deployment generates a deployed version of a bundle. A bundle deployment can be seen as a generalization of the pod concept.

The specifics of how a bundle deployment makes changes to a cluster based on a referenced bundle is defined by the provisioner that is configured to watch that bundle deployment.

Example BundleDeployment object configured to work with the plain provisioner
apiVersion: core.rukpak.io/v1alpha1
kind: BundleDeployment
  name: my-bundle-deployment
  provisionerClassName: core-rukpak-io-plain
        app: my-bundle
        type: image
          ref: my-bundle@sha256:xyz123
      provisionerClassName: core-rukpak-io-plain

About provisioners

RukPak consists of a series of controllers, known as provisioners, that install and manage content on a Kubernetes cluster. RukPak also provides two primary APIs: Bundle and BundleDeployment. These components work together to bring content onto the cluster and install it, generating resources within the cluster.

Two provisioners are currently implemented and bundled with RukPak: the plain provisioner that sources and unpacks plain+v0 bundles, and the registry provisioner that sources and unpacks Operator Lifecycle Manager (OLM) registry+v1 bundles.

Each provisioner is assigned a unique ID and is responsible for reconciling Bundle and BundleDeployment objects with a spec.provisionerClassName field that matches that particular ID. For example, the plain provisioner is able to unpack a given plain+v0 bundle onto a cluster and then instantiate it, making the content of the bundle available in the cluster.

A provisioner places a watch on both Bundle and BundleDeployment resources that refer to the provisioner explicitly. For a given bundle, the provisioner unpacks the contents of the Bundle resource onto the cluster. Then, given a BundleDeployment resource referring to that bundle, the provisioner installs the bundle contents and is responsible for managing the lifecycle of those resources.