Taking its name after a Greek word that translates as helmsman, Kubernetes is an open source container-orchestration system that enables you to automate application deployment, scaling, and management.

While containerized deployments have enabled enterprises to reduce overhead by more effectively managing IT infrastructure resources while increasing portability, efficiency, and operation, managing a large number of containers at scale can be a nearly impossible task. This is where Kubernetes adds a lot of value to an organization by automating this management to keep your apps running efficiently and effectively. 

But what is a Kubernetes Operator? And why do enterprises need Operators, when Kubernetes is meant to enable them to automate deployment, scaling, and lifecycle management out-of-the-box?

The most common definition for a Kubernetes Operator that you’ll find is that it’s “a method of packaging, deploying and managing a Kubernetes application.”

However, that definition doesn’t seem very helpful until we define the specific challenges that Operators help enterprises overcome when managing containerized applications on Kubernetes.

The Problem That Kubernetes Operators Solve

Where Kubernetes has always delivered on its promise of automation is when an organization is deploying and scaling a stateless application, which doesn’t save client data from one session to another. However, when dealing with a stateful application which depends on valuable information from one session to another, the situation gets a little bit more complicated.

Jeremy Thompson, the CTO at Solodev summarizes the problem this way: “Adding or removing instances may require preparation and/or post-provisioning steps – for instance, changes to its internal configuration, communication with a clustering mechanism, interaction with external systems like DNS, and so forth.”

He goes on to say, “Historically, this often required manual intervention, increasing the DevOps burden and increasing the likelihood of error. Perhaps most importantly, it obviates one of Kubernetes’ main selling points: automation.”

So at the heart of it, Kubernetes Operators are intended to enable you to experience the benefit of Kubernetes automation in a broader set of containerized deployment situations.

Why Use An Operator?

Kubernetes Operators extend the functionality of Kubernetes to automate deployments based on your organization’s specific needs. Essentially, they increase your ability to automate more complex functions.

Dasha Gurova summarizes it this way: “an Operator essentially is codified knowledge on how to run the Kubernetes application.” Kubernetes Operators operationalize and automate the specific domain expertise necessary to manage and scale your enterprises’ specific containerized applications. They are particularly useful when you need to increase the efficiency of actions that go beyond a simple restart of a container when an instance fails.

For example, let's say you’re a system admin, and as a human operator, you know that there are specific ways to get your application up and running that go beyond just restarting the container. Or perhaps you have a specific procedure for bringing your system back up when an exception occurs. In cases like these, you can customize an Operator to perform these tasks automatically, which saves you time and decreases the likelihood of human error in the process.

Kubernetes Operators enable you to experience less complexity when managing your applications by embedding your team’s human expertise into the code itself. Furthermore, Operators are able to run on whatever infrastructure where you’re currently running Kubernetes, whether it is a public, private, hybrid, or multi-cloud setting.

When To Use An Operator

Your teams should consider creating a Kubernetes Operator where the investment of time and resources is greater than the value of the time currently being spent to complete those tasks manually.

Even beyond the initial building of Operators, you will need to continue to expend resources to maintain them. Ben Bromhead, CTO at Instaclustr says this: “Developer teams attempting to manage [Kubernetes Operators] in-house really must keep close track of Operator changes and proactively plan for upgrades. They will absolutely need to manually intervene when things go wrong since Kubernetes Operators can and will get into weird states that require hands-on attention.”

This means that not every situation will call for a Kubernetes Operator. So understanding your context is key in deciding whether or not you think your organization will benefit from having one for a particular application.

Some key contexts where you may consider an Operator are databases, for security, networking, as well as CI/CD. If you are looking to create a custom Kubernetes Operator for your application, Google Cloud offers best practices for building Operators that can be found here.

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Entando is open source with available enterprise support. Begin developing on the platform today, and get a quote to see how our Professional Services team can help your enterprise build better apps, sites, and portals--faster.