MongoDB Gives Users a Simple Way to Install Atlas Kubernetes Operator and Import MongoDB Atlas Clusters via the Atlas CLI

As time to market and rapid innovation get ever more critical to business success, the last thing your team needs is to spend more time than necessary managing infrastructure.

In our most recent update to the MongoDB Atlas Kubernetes Operator, we’ve made it even easier to manage Atlas through the same mechanism that your team is using to manage their applications in Kubernetes. The Atlas Operator enables teams to deploy simple yaml configuration to Kubernetes, where the Operator automates the use of the Atlas Admin APIs to make the changes. It's now possible to install the Atlas Operator through a single command via a tool they already have: the Atlas CLI. Additionally, we’ve given users the optional ability to import existing Atlas projects and deployments into management through the Operator, as part of the installation or as a stand alone operation, making it easy to adopt existing Atlas deployments into management through the Operator.

Keep reading to learn how your team can automate the installation and import of Atlas projects in order to enable easy self-service use of Atlas for your engineering teams.

But first, a little context

The MongoDB Atlas Kubernetes Operator enables teams to manage Atlas from within Kubernetes the same way they would any other service in their Kubernetes stack. By doing this, the Operator removes the need for custom scripts and switching between UIs in order to use the two together.

Instead, teams are able to manage their Atlas projects, deployments and database users through yaml that can either live in their Kubernetes cluster, or, more commonly, in a repository alongside their other infrastructure as code configuration. Many customers choose to use a deployment tool like ArgoCD or Flux to automate applying those into Kuberentes, where the Atlas Operator picks them up and uses APIs to make the changes to Atlas. All your teams need to worry about is the yaml in their repo!

Previously, setting up the Atlas Kubernetes Operator was a multi-step, manual process. First teams had to use Kubernetes tooling to install the Atlas Kubernetes Operator within a Kubernetes cluster. Teams then had to create an API key in Atlas and a corresponding Kubernetes secret required to authenticate the Atlas Kubernetes Operator to Atlas. It was only after all of that work that they could then create a database or import existing Atlas deployments into the Atlas Kubernetes Operators control.

While exporting Atlas configuration into Kubernetes was generally a simple process, it still required some manual steps to bridge the Atlas CLI (which offered a compatible export of Atlas configuration) and Kubernetes (where the configuration needed to be imported). Because of this, secrets either had to be exported in plaintext onto the user’s machine, or entered manually later.

All of this to say, it was possible… it just wasn't a piece of cake.

Enter a more simplified approach

Now, it’s easier than ever to get started with Kubernetes-native management of Atlas.

First, we’ve made the installation of the Atlas Kubernetes Operator a simpler process by enabling teams to use the Atlas CLI to install the Atlas Kubernetes Operator. Through a single command in the CLI, Atlas users are able to easily install the Atlas Kubernetes Operator into their currently connected Kubernetes cluster. Including the automated creation of an Atlas API key and storing it in a Kubernetes secret for use by the Operator.

Additionally, users can now export Atlas configuration for projects, deployments and users directly into Kubernetes, either as part of the install or as a separate operation. This saves users from needing to always having to export to their own machine before applying to Kubernetes, though exporting like this is still available to support GitOps workflows. With these options, it’s much easier for teams to take control of their projects and clusters and manage them through the Atlas Operator.

By simplifying the use of the Atlas Kubernetes Operator with these updates, we have significantly reduced the amount of toil that went into getting started with Atlas.