Kubernetes Custom Resource Definition (CRD) Validation
Table of Contents
- Core Concepts of Kubernetes CRD Validation
- Typical Usage Example
- Common Practices
- Best Practices
- Conclusion
- References
Core Concepts of Kubernetes CRD Validation
What is a CRD?
A Custom Resource Definition (CRD) is an API extension in Kubernetes that allows you to define new custom resources. These resources can be used to represent any kind of object in your application’s domain, such as databases, messaging queues, or machine learning models. Once a CRD is created, you can create, read, update, and delete instances of the custom resource, just like you would with built - in Kubernetes resources like Pods or Services.
Why is Validation Necessary?
When working with custom resources, there is a risk of users providing incorrect or inconsistent data. For example, a user might specify an invalid configuration for a custom resource, which could lead to errors or unexpected behavior in the application. CRD validation helps prevent such issues by ensuring that the data submitted for a custom resource adheres to a set of predefined rules.
Types of Validation
- Schema Validation: This is the most common type of validation in Kubernetes CRDs. It uses JSON Schema to define the structure and data types of the custom resource. For example, you can specify that a particular field must be an integer, a string of a certain length, or an array of specific objects.
- Webhook Validation: Webhook validation allows you to implement custom validation logic outside of the Kubernetes API server. When a user creates, updates, or deletes a custom resource, the API server sends a request to the webhook, which can then perform more complex validation based on business rules, external data sources, or other factors.
Typical Usage Example
Let’s create a simple CRD for a “Book” resource and add validation to it.
Step 1: Define the CRD
apiVersion: apiextensions.k8s.io/v1
kind: CustomResourceDefinition
metadata:
name: books.example.com
spec:
group: example.com
versions:
- name: v1
served: true
storage: true
schema:
openAPIV3Schema:
type: object
properties:
spec:
type: object
properties:
title:
type: string
minLength: 1
author:
type: string
minLength: 1
year:
type: integer
minimum: 1000
maximum: 3000
scope: Namespaced
names:
plural: books
singular: book
kind: Book
In this CRD, we have defined a Book resource with three fields in the spec: title, author, and year. We have added schema validation rules to ensure that the title and author are non - empty strings, and the year is an integer between 1000 and 3000.
Step 2: Create a Custom Resource Instance
apiVersion: example.com/v1
kind: Book
metadata:
name: my - book
spec:
title: "The Great Gatsby"
author: "F. Scott Fitzgerald"
year: 1925
If we try to create a custom resource with an invalid year value, for example:
apiVersion: example.com/v1
kind: Book
metadata:
name: invalid - book
spec:
title: "Invalid Book"
author: "Unknown"
year: 500
The Kubernetes API server will reject the creation of this resource because the year value does not meet the validation criteria.
Common Practices
Start with Schema Validation
Schema validation is a simple and effective way to enforce basic rules on the structure and data types of your custom resources. It is built - in to the Kubernetes API server, so there is no need to set up additional infrastructure. Start by defining a JSON Schema for your custom resource and gradually add more rules as your application evolves.
Use Webhook Validation for Complex Logic
When your validation requirements go beyond what can be expressed in JSON Schema, use webhook validation. For example, if you need to check if a custom resource’s configuration is compatible with an external service or if it violates some business rules, a webhook can perform these checks.
Test Your Validation Rules
Before deploying your CRD to a production environment, thoroughly test your validation rules. Create custom resource instances with both valid and invalid data to ensure that the validation works as expected. You can use tools like kubectl to test the creation and update of custom resources.
Best Practices
Keep Validation Rules Simple and Clear
Complex validation rules can be difficult to understand and maintain. Try to keep your validation rules as simple as possible, and document them clearly. This will make it easier for other developers to work with your custom resources.
Provide Meaningful Error Messages
When a validation error occurs, the Kubernetes API server should return a meaningful error message. In the case of webhook validation, you can customize the error message to provide more detailed information about what went wrong. This will help users quickly identify and fix the issues.
Version Your Validation Rules
As your application evolves, your validation rules may change. It is important to version your CRDs and their validation rules to ensure compatibility with existing custom resources. When making changes to the validation rules, consider how they will affect the existing resources and provide a migration plan if necessary.
Conclusion
Kubernetes CRD validation is an essential part of managing custom resources in a Kubernetes cluster. By understanding the core concepts, using typical usage examples, following common practices, and adopting best practices, intermediate - to - advanced software engineers can ensure the integrity and reliability of their custom resources. Whether you are using schema validation or webhook validation, proper validation will help prevent errors and make your application more robust.
References
- Kubernetes Documentation: https://kubernetes.io/docs/concepts/extend-kubernetes/api-extension/custom-resources/
- JSON Schema Specification: https://json-schema.org/
- Kubernetes Webhook Validation: https://kubernetes.io/docs/reference/access-authn-authz/extensible-admission-controllers/