The Operator pattern aims to capture the key aim of a human operator who is managing a service or set of services. Human operators who look after specific applications and services have deep knowledge of how the system ought to behave, how to deploy it, and how to react if there are problems.
People who run workloads on Kubernetes often like to use automation to take care of repeatable tasks. The Operator pattern captures how you can write code to automate a task beyond what Kubernetes itself provides.
Operators in Kubernetes
Kubernetes is designed for automation. Out of the box, you get lots of built-in automation from the core of Kubernetes. You can use Kubernetes to automate deploying and running workloads, and you can automate how Kubernetes does that.
Kubernetes' operator pattern concept lets you extend the cluster's behaviour without modifying the code of Kubernetes itself by linking controllers to one or more custom resources. Operators are clients of the Kubernetes API that act as controllers for a Custom Resource.
An example Operator
Some of the things that you can use an operator to automate include:
- deploying an application on demand
- taking and restoring backups of that application's state
- handling upgrades of the application code alongside related changes such as database schemas or extra configuration settings
- publishing a Service to applications that don't support Kubernetes APIs to discover them
- simulating failure in all or part of your cluster to test its resilience
- choosing a leader for a distributed application without an internal member election process
What might an Operator look like in more detail? Here's an example:
- A custom resource named SampleDB, that you can configure into the cluster.
- A Deployment that makes sure a Pod is running that contains the controller part of the operator.
- A container image of the operator code.
- Controller code that queries the control plane to find out what SampleDB resources are configured.
- The core of the Operator is code to tell the API server how to make
reality match the configured resources.
- If you add a new SampleDB, the operator sets up PersistentVolumeClaims to provide durable database storage, a StatefulSet to run SampleDB and a Job to handle initial configuration.
- If you delete it, the Operator takes a snapshot, then makes sure that the StatefulSet and Volumes are also removed.
- The operator also manages regular database backups. For each SampleDB resource, the operator determines when to create a Pod that can connect to the database and take backups. These Pods would rely on a ConfigMap and / or a Secret that has database connection details and credentials.
- Because the Operator aims to provide robust automation for the resource it manages, there would be additional supporting code. For this example, code checks to see if the database is running an old version and, if so, creates Job objects that upgrade it for you.
The most common way to deploy an Operator is to add the Custom Resource Definition and its associated Controller to your cluster. The Controller will normally run outside of the control plane, much as you would run any containerized application. For example, you can run the controller in your cluster as a Deployment.
Using an Operator
Once you have an Operator deployed, you'd use it by adding, modifying or deleting the kind of resource that the Operator uses. Following the above example, you would set up a Deployment for the Operator itself, and then:
kubectl get SampleDB # find configured databases kubectl edit SampleDB/example-database # manually change some settings
…and that's it! The Operator will take care of applying the changes as well as keeping the existing service in good shape.
Writing your own Operator
If there isn't an Operator in the ecosystem that implements the behavior you want, you can code your own.
You also implement an Operator (that is, a Controller) using any language / runtime that can act as a client for the Kubernetes API.
Following are a few libraries and tools you can use to write your own cloud native Operator.
- Charmed Operator Framework
- Kopf (Kubernetes Operator Pythonic Framework)
- KubeOps (.NET operator SDK)
- KUDO (Kubernetes Universal Declarative Operator)
- Metacontroller along with WebHooks that you implement yourself
- Operator Framework
- Read the CNCF Operator White Paper.
- Learn more about Custom Resources
- Find ready-made operators on OperatorHub.io to suit your use case
- Publish your operator for other people to use
- Read CoreOS' original article that introduced the Operator pattern (this is an archived version of the original article).
- Read an article from Google Cloud about best practices for building Operators
Items on this page refer to third party products or projects that provide functionality required by Kubernetes. The Kubernetes project authors aren't responsible for those third-party products or projects. See the CNCF website guidelines for more details.
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