Extending the Kubernetes API

• 1: Custom Resources
• 2: Kubernetes API Aggregation Layer

1 - Custom Resources

Custom resources are extensions of the Kubernetes API. This page discusses when to add a custom resource to your Kubernetes cluster and when to use a standalone service. It describes the two methods for adding custom resources and how to choose between them.

Custom resources

A resource is an endpoint in the Kubernetes API that stores a collection of API objects of a certain kind; for example, the built-in pods resource contains a collection of Pod objects.

A custom resource is an extension of the Kubernetes API that is not necessarily available in a default Kubernetes installation. It represents a customization of a particular Kubernetes installation. However, many core Kubernetes functions are now built using custom resources, making Kubernetes more modular.

Custom resources can appear and disappear in a running cluster through dynamic registration, and cluster admins can update custom resources independently of the cluster itself. Once a custom resource is installed, users can create and access its objects using kubectl, just as they do for built-in resources like Pods.

Custom controllers

On their own, custom resources let you store and retrieve structured data. When you combine a custom resource with a custom controller, custom resources provide a true declarative API.

The Kubernetes declarative API enforces a separation of responsibilities. You declare the desired state of your resource. The Kubernetes controller keeps the current state of Kubernetes objects in sync with your declared desired state. This is in contrast to an imperative API, where you instruct a server what to do.

You can deploy and update a custom controller on a running cluster, independently of the cluster's lifecycle. Custom controllers can work with any kind of resource, but they are especially effective when combined with custom resources. The Operator pattern combines custom resources and custom controllers. You can use custom controllers to encode domain knowledge for specific applications into an extension of the Kubernetes API.

Should I add a custom resource to my Kubernetes cluster?

When creating a new API, consider whether to aggregate your API with the Kubernetes cluster APIs or let your API stand alone.

Declarative APIs

In a Declarative API, typically:

• Your API consists of a relatively small number of relatively small objects (resources).
• The objects define configuration of applications or infrastructure.
• The objects are updated relatively infrequently.
• Humans often need to read and write the objects.
• The main operations on the objects are CRUD-y (creating, reading, updating and deleting).
• Transactions across objects are not required: the API represents a desired state, not an exact state.

Imperative APIs are not declarative. Signs that your API might not be declarative include:

• The client says "do this", and then gets a synchronous response back when it is done.
• The client says "do this", and then gets an operation ID back, and has to check a separate Operation object to determine completion of the request.
• You talk about Remote Procedure Calls (RPCs).
• Directly storing large amounts of data; for example, > a few kB per object, or > 1000s of objects.
• High bandwidth access (10s of requests per second sustained) needed.
• Store end-user data (such as images, PII, etc.) or other large-scale data processed by applications.
• The natural operations on the objects are not CRUD-y.
• The API is not easily modeled as objects.
• You chose to represent pending operations with an operation ID or an operation object.

Should I use a ConfigMap or a custom resource?

Use a ConfigMap if any of the following apply:

• There is an existing, well-documented configuration file format, such as a mysql.cnf or pom.xml.
• You want to put the entire configuration into one key of a ConfigMap.
• The main use of the configuration file is for a program running in a Pod on your cluster to consume the file to configure itself.
• Consumers of the file prefer to consume via file in a Pod or environment variable in a pod, rather than the Kubernetes API.
• You want to perform rolling updates via Deployment, etc., when the file is updated.

Use a custom resource (CRD or Aggregated API) if most of the following apply:

• You want to use Kubernetes client libraries and CLIs to create and update the new resource.
• You want top-level support from kubectl; for example, kubectl get my-object object-name.
• You want to build new automation that watches for updates on the new object, and then CRUD other objects, or vice versa.
• You want to write automation that handles updates to the object.
• You want to use Kubernetes API conventions like .spec, .status, and .metadata.
• You want the object to be an abstraction over a collection of controlled resources, or a summarization of other resources.

Adding custom resources

Kubernetes provides two ways to add custom resources to your cluster:

• CRDs are simple and can be created without any programming.
• API Aggregation requires programming, but allows more control over API behaviors like how data is stored and conversion between API versions.

Kubernetes provides these two options to meet the needs of different users, so that neither ease of use nor flexibility is compromised.

Aggregated APIs are subordinate API servers that sit behind the primary API server, which acts as a proxy. This arrangement is called API Aggregation(AA). To users, the Kubernetes API appears extended.

CRDs allow users to create new types of resources without adding another API server. You do not need to understand API Aggregation to use CRDs.

Regardless of how they are installed, the new resources are referred to as Custom Resources to distinguish them from built-in Kubernetes resources (like pods).

CustomResourceDefinitions

The CustomResourceDefinition API resource allows you to define custom resources. Defining a CRD object creates a new custom resource with a name and schema that you specify. The Kubernetes API serves and handles the storage of your custom resource. The name of the CRD object itself must be a valid DNS subdomain name derived from the defined resource name and its API group; see how to create a CRD for more details. Further, the name of an object whose kind/resource is defined by a CRD must also be a valid DNS subdomain name.

This frees you from writing your own API server to handle the custom resource, but the generic nature of the implementation means you have less flexibility than with API server aggregation.

Refer to the custom controller example for an example of how to register a new custom resource, work with instances of your new resource type, and use a controller to handle events.

API server aggregation

Usually, each resource in the Kubernetes API requires code that handles REST requests and manages persistent storage of objects. The main Kubernetes API server handles built-in resources like pods and services, and can also generically handle custom resources through CRDs.

The aggregation layer allows you to provide specialized implementations for your custom resources by writing and deploying your own API server. The main API server delegates requests to your API server for the custom resources that you handle, making them available to all of its clients.

Choosing a method for adding custom resources

CRDs are easier to use. Aggregated APIs are more flexible. Choose the method that best meets your needs.

Typically, CRDs are a good fit if:

• You have a handful of fields
• You are using the resource within your company, or as part of a small open-source project (as opposed to a commercial product)

Comparing ease of use

CRDs are easier to create than Aggregated APIs.

Advanced features and flexibility

Aggregated APIs offer more advanced API features and customization of other features; for example, the storage layer.

Common Features

When you create a custom resource, either via a CRD or an AA, you get many features for your API, compared to implementing it outside the Kubernetes platform:

Preparing to install a custom resource

There are several points to be aware of before adding a custom resource to your cluster.

Third party code and new points of failure

While creating a CRD does not automatically add any new points of failure (for example, by causing third party code to run on your API server), packages (for example, Charts) or other installation bundles often include CRDs as well as a Deployment of third-party code that implements the business logic for a new custom resource.

Installing an Aggregated API server always involves running a new Deployment.

Storage

Custom resources consume storage space in the same way that ConfigMaps do. Creating too many custom resources may overload your API server's storage space.

Aggregated API servers may use the same storage as the main API server, in which case the same warning applies.

Authentication, authorization, and auditing

CRDs always use the same authentication, authorization, and audit logging as the built-in resources of your API server.

If you use RBAC for authorization, most RBAC roles will not grant access to the new resources (except the cluster-admin role or any role created with wildcard rules). You'll need to explicitly grant access to the new resources. CRDs and Aggregated APIs often come bundled with new role definitions for the types they add.

Aggregated API servers may or may not use the same authentication, authorization, and auditing as the primary API server.

Accessing a custom resource

Kubernetes client libraries can be used to access custom resources. Not all client libraries support custom resources. The Go and Python client libraries do.

When you add a custom resource, you can access it using:

• kubectl
• The Kubernetes dynamic client.
• A REST client that you write.
• A client generated using Kubernetes client generation tools (generating one is an advanced undertaking, but some projects may provide a client along with the CRD or AA).

Custom resource field selectors

Field Selectors let clients select custom resources based on the value of one or more resource fields.

All custom resources support the metadata.name and metadata.namespace field selectors.

Fields declared in a CustomResourceDefinition may also be used with field selectors when included in the spec.versions[*].selectableFields field of the CustomResourceDefinition.

Selectable fields for custom resources

The spec.versions[*].selectableFields field of a CustomResourceDefinition may be used to declare which other fields in a custom resource may be used in field selectors with the feature of CustomResourceFieldSelectors feature gate (This feature gate is enabled by default since Kubernetes v1.31). The following example adds the .spec.color and .spec.size fields as selectable fields.

customresourcedefinition/shirt-resource-definition.yaml

apiVersion: apiextensions.k8s.io/v1
kind: CustomResourceDefinition
metadata:
  name: shirts.stable.example.com
spec:
  group: stable.example.com
  scope: Namespaced
  names:
    plural: shirts
    singular: shirt
    kind: Shirt
  versions:
  - name: v1
    served: true
    storage: true
    schema:
      openAPIV3Schema:
        type: object
        properties:
          spec:
            type: object
            properties:
              color:
                type: string
              size:
                type: string
    selectableFields:
    - jsonPath: .spec.color
    - jsonPath: .spec.size
    additionalPrinterColumns:
    - jsonPath: .spec.color
      name: Color
      type: string
    - jsonPath: .spec.size
      name: Size
      type: string

Field selectors can then be used to get only resources with a color of blue:

kubectl get shirts.stable.example.com --field-selector spec.color=blue

The output should be:

NAME       COLOR  SIZE
example1   blue   S
example2   blue   M

What's next

• Learn how to Extend the Kubernetes API with the aggregation layer.
• Learn how to Extend the Kubernetes API with CustomResourceDefinition.

2 - Kubernetes API Aggregation Layer

The aggregation layer allows Kubernetes to be extended with additional APIs, beyond what is offered by the core Kubernetes APIs. The additional APIs can either be ready-made solutions such as a metrics server, or APIs that you develop yourself.

The aggregation layer is different from Custom Resource Definitions, which are a way to make the kube-apiserver recognise new kinds of object.

Aggregation layer

The aggregation layer runs in-process with the kube-apiserver. Until an extension resource is registered, the aggregation layer will do nothing. To register an API, you add an APIService object, which "claims" the URL path in the Kubernetes API. At that point, the aggregation layer will proxy anything sent to that API path (e.g. /apis/myextension.mycompany.io/v1/…) to the registered APIService.

The most common way to implement the APIService is to run an extension API server in Pod(s) that run in your cluster. If you're using the extension API server to manage resources in your cluster, the extension API server (also written as "extension-apiserver") is typically paired with one or more controllers. The apiserver-builder library provides a skeleton for both extension API servers and the associated controller(s).

Response latency

Extension API servers should have low latency networking to and from the kube-apiserver. Discovery requests are required to round-trip from the kube-apiserver in five seconds or less.

If your extension API server cannot achieve that latency requirement, consider making changes that let you meet it.

What's next

• To get the aggregator working in your environment, configure the aggregation layer.
• Then, setup an extension api-server to work with the aggregation layer.
• Read about APIService in the API reference

Alternatively: learn how to extend the Kubernetes API using Custom Resource Definitions.