Understanding Kubernetes Operators


Automation is one of the fundamental components that makes Kubernetes so robust as a containerization engine. Even complex cloud infrastructure creation can be automated in order to simplify the process of managing cloud deployments. Despite the capability of leveraging so many resources and components to support an application, your cloud environment can still be fairly manageable.

Despite the many tools available on Kubernetes, the effort to make cloud infrastructure management more scalable and automated is ongoing. Kubernetes operator is one of the tools designed to push automation past its limits. You can do so much more without having to rely on manual inputs every time. 

Getting to Know Kubernetes Operators

A Kubernetes operator, by definition, is an orchestration framework. It is a tool that lets you orchestrate and maintain cloud infrastructures with little to no human input. Kubernetes define operators as software extensions designed to utilize custom resources to manage applications and their components.

Kubernetes operators are not complex at all. Operators use controllers and the Kubernetes API to handle packaging, deployment, management, and maintenance of applications and the custom resources that they need. The whole process is fully automated, plus you can still rely on kubectl tooling for commands and operations.

In other words, an operator is basically a custom Kubernetes controller that integrates custom resources for management purposes. You can define parameters and configurations inside the custom resources directly, and then let the operators translate those parameters and run autonomously. Kubernetes operators’ continuous nature is their defining factor.

More Than Deployment

Kubernetes Operators can be used to do more than automate the deployment of applications. In fact, operators are capable of handling anything as long as the logics and parameters are defined properly. Yes, that includes scaling up your application and the cloud infrastructure it uses, doing upgrades and checking for failures, and keeping the app running smoothly in the long run.

The whole application life cycle can be automated. While Kubernetes does not have built-in features to manage stateful applications without requiring human inputs for domain knowledge, operators can contain the necessary domain knowledge and additional parameters to tackle the same challenge seamlessly.

For example, you can write the site reliability engineering (SRE) rules and parameters into your Kubernetes operator, and have the operator handle ops for you. This allows SRE practices to be standardized and made repeatable across multiple clusters. There is no need to make manual adjustments to the parameters with every deployment and upgrade.

Mimicking Human Operators

The true strength of Kubernetes operators lies in the way they understand how an app or a service is supposed to work. Human operators rely on that knowledge to deploy the application, make adjustments when needed, fix problems that occur along the way, and keep the application running smoothly.

Kubernetes operators can use the same knowledge, embedded in the operators themselves, to perform the necessary tasks. When a cloud resource is not provisioned for an application during an update, for instance, Kubernetes operators can automatically correct the issue without issuing alerts to the human operators.

In essence, Kubernetes operators mimic what human operators do. However, the Kubernetes operators need to be created by someone who understands the logic behind the app and how it needs to be deployed. App deployment and provisioning of resources are the tasks that can be automated first since they are the simplest.

What Can Operators Do?

To get an even better understanding of what operators can do, we need to look at some of the ways operators can be used. The basic things that operators can do include deploying an application when needed, making backups of application states, handling upgrades that require supporting services such as DB to be updated as well, and performing resilience testing by simulating failures.

These are tasks that normally require a lot of human input. When simulating failure, human operators need to manually trigger errors in select parts of the application, and then monitor the output to mark the point of failure. Automating the process saves a lot of time and resources; it certainly allows human operators to focus on other, more important tasks.

On top of that, operators can handle specific and complex situations. For example, you can use an operator to deploy a resource and configure it to be discoverable by a handful of services or pods. The operator can check the control plane of that resource, and then make adjustments if needed. Using the Kubernetes API, it can also take snapshots or perform updates.

The latter can have more parameters coded into the process. For instance, you can have a seamless update process preventing the entire app from going offline by deploying a new updated resource, telling the cluster to use that new resource, and then deleting both the StatefulSet and Volumes of the previous resource.

Utilizing Operators

Deploying operators is easier than you think. You only need to define a Custom Resource Definition and its Controller to your cluster, and you are all set. The real challenge is making an operator that suits your specific needs. The same kubectl commands can be used to perform certain operations as you begin using the operator.

You can use kubectl get resourceName to find the configured resourceName. You can then run kubectl edit resourceName/example-resource to make changes to the resources. Operators can be used to make any type of changes to a cluster, including high-level configuration changes as needed. There are even ready-made operators that you can pull from some repositories.

Of course, you can always code your own operators if you want them to handle specific functions. By creating an operator as a client for the Kubernetes API, you can access more features and automate virtually every deployment, management, and maintenance tasks. You can also use tools like kubebuilder and Operator Framework to get started.

Operator Framework is a great starting point indeed. It is an open-source toolkit for managing Kubernetes native operators. Explore its functionalities to learn more about how you can utilize operators to simplify your cloud infrastructure management.

Caylent provides a critical DevOps-as-a-Service function to high growth companies looking for expert support with Kubernetes, cloud security, cloud infrastructure, and CI/CD pipelines. Our managed and consulting services are a more cost-effective option than hiring in-house, and we scale as your team and company grow. Check out some of the use cases, learn how we work with clients, and read more about our DevOps-as-a-Service offering.


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