Understanding Kubernetes Custom Resource Definitions (CRDs) Types
Table of Contents
- Core Concepts of Kubernetes CRD Types
- Typical Usage Example
- Common Practices
- Best Practices
- Conclusion
- References
Core Concepts of Kubernetes CRD Types
What are Custom Resource Definitions (CRDs)?
A Custom Resource Definition is a way to teach Kubernetes about a new kind of object. It is essentially a schema that defines the structure and behavior of a custom resource. Once a CRD is created in a Kubernetes cluster, users can create, read, update, and delete instances of the custom resource, just like they would with built - in Kubernetes resources such as Pods or Services.
Structure of a CRD
A CRD is defined using a YAML or JSON file. The main components of a CRD definition include:
- API Group: A namespace for the custom resource. It helps to avoid naming conflicts with other resources in the cluster. For example,
mycompany.comcould be an API group. - Version: The version of the API for the custom resource. This allows for evolution of the resource schema over time. For example,
v1. - Kind: The name of the custom resource kind. For example,
MyCustomResource. - Namespaced: A boolean value indicating whether the custom resource is namespaced or cluster - scoped. Namespaced resources are isolated within a specific namespace, while cluster - scoped resources are available across the entire cluster.
Custom Resources vs. Built - in Resources
Built - in resources like Pods, Services, and Deployments are part of the core Kubernetes API. Custom resources, on the other hand, are defined by the users to meet specific application requirements. While built - in resources are designed to handle general - purpose container orchestration tasks, custom resources can be used to model domain - specific concepts such as database migrations, machine learning jobs, or custom monitoring configurations.
Typical Usage Example
Scenario: Managing Database Migrations
Let’s assume we want to create a custom resource to manage database migrations in a Kubernetes cluster.
Step 1: Define the CRD
apiVersion: apiextensions.k8s.io/v1
kind: CustomResourceDefinition
metadata:
name: databasemigrations.mycompany.com
spec:
group: mycompany.com
versions:
- name: v1
served: true
storage: true
schema:
openAPIV3Schema:
type: object
properties:
spec:
type: object
properties:
migrationScript:
type: string
databaseName:
type: string
scope: Namespaced
names:
plural: databasemigrations
singular: databasemigration
kind: DatabaseMigration
Step 2: Create an Instance of the Custom Resource
apiVersion: mycompany.com/v1
kind: DatabaseMigration
metadata:
name: my - database - migration
spec:
migrationScript: "ALTER TABLE users ADD COLUMN new_column VARCHAR(255);"
databaseName: mydatabase
Step 3: Create a Controller to Handle the Custom Resource
A controller is a Kubernetes component that watches for changes to the custom resource and takes appropriate actions. In this case, the controller could connect to the database and execute the migration script.
package main
import (
"log"
"k8s.io/apimachinery/pkg/apis/meta/v1"
"k8s.io/client - go/kubernetes"
"k8s.io/client - go/rest"
"k8s.io/client - go/tools/clientcmd"
)
func main() {
config, err := clientcmd.BuildConfigFromFlags("", clientcmd.RecommendedHomeFile)
if err != nil {
log.Fatalf("Error building kubeconfig: %v", err)
}
clientset, err := kubernetes.NewForConfig(config)
if err != nil {
log.Fatalf("Error creating clientset: %v", err)
}
// Watch for changes to the custom resource
// and perform database migrations
// This is a simplified example, and a real - world controller would be more complex
//...
}
Common Practices
Versioning
When creating CRDs, it is important to version them properly. This allows for seamless updates to the resource schema without breaking existing applications. Use semantic versioning and ensure that you have a clear migration path between versions.
Validation
Validate the input data for custom resources using the openAPIV3Schema in the CRD definition. This helps to prevent invalid data from being stored in the cluster and ensures that the custom resources are in a consistent state.
Controller Design
Design controllers to be idempotent. This means that if the same operation is performed multiple times, it should have the same effect as if it was performed only once. Idempotency helps to handle errors and retries gracefully.
Best Practices
Documentation
Document the purpose, structure, and usage of your custom resources thoroughly. This makes it easier for other developers to understand and use the custom resources in the cluster.
Testing
Write unit tests and integration tests for your CRDs and controllers. Test different scenarios, including valid and invalid input, to ensure that the custom resources and controllers work as expected.
Security
Apply appropriate security measures to your custom resources. This includes proper authentication and authorization, as well as ensuring that the custom resources do not expose sensitive information.
Conclusion
Kubernetes Custom Resource Definitions (CRDs) are a powerful feature that allows users to extend the Kubernetes API and create custom resources tailored to their specific application needs. By understanding the core concepts, following typical usage examples, adopting common practices, and implementing best practices, software engineers can effectively use CRDs to build more flexible and scalable Kubernetes - based applications.
References
- Kubernetes Documentation: https://kubernetes.io/docs/concepts/extend - kubernetes/api - extensions/custom - resources/
- Kubernetes Custom Resource Definition API Reference: https://kubernetes.io/docs/reference/generated/kubernetes - api/v1.23/#customresourcedefinition - v1 - apiextensions - k8s - io
- Kubernetes Controller Patterns: https://kubernetes.io/docs/concepts/architecture/controller/