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Definition: What Is a Kubernetes Operator?

A Kubernetes operator is an application-specific program that automates tasks to manage an application in the Kubernetes ecosystem. Operators are basically automated system administrators. They allow users to extend the capabilities of Kubernetes APIs by structuring a custom process that manages instances of an application. Their role is to maintain the desired state of an application set by the Custom Resources Definitions (CRD). This can be to scale, update, or restart the application.

Operators are exclusive to an application. They can be configured to run day to day tasks of an application. For example, you can configure them to install, configure and recover software running in a Kubernetes cluster. They integrate with the Kubernetes APIs to manage the custom resources needed to run an application.

Need a little help getting started with Kubernetes? Check out the short video below.

Why Does Kubernetes Need Operators?

While Kubernetes can manage stateless applications, like web applications, backends, and APIs, it’s limited to stateful applications. Stateful applications like databases and servers require domain-specific information to run the systems, which Kubernetes does not have. However, Kubernetes needs such information to upgrade, scale, and reconfigure stateful applications.

Operators extend these functionalities. They allow users to configure domain-specific information that manages and automates an application’s life cycle. For example you can upgrade, scale, and manage repeatable tasks in an application using an operator.

At the same time, Kubernetes operators help to automate the maintenance of containerized applications in production in various capacities. They help to customize application management for stateful applications. For example , if a database needs new version, an operator organizes how to upgrade it without you having to do it manually. Operators also improve the management of applications in hybrid environments, whether on-premise or on public clouds.

With operators, you can manage both stateless and complex stateful applications in the cluster.

What Are Operators Used For?

Kubernetes operators can run several tasks for an application. These include:

  • Deploy an application on demand
  • Take and restore backups for the application’s state
  • Handle changes such as upgrades on an application
  • Handle regular backups of an application’s state or database
  • Publish or expose a Service that’s not supported by Kubernetes APIs
  • Test an application’s resilience

How Kubernetes Operators Work

Kubernetes operators use controllers to track an application’s custom resource definition (CRD) objects. A CRD extends the Kubernetes API with endpoints to store and retrieve data. Operators monitor cluster events related to custom resources. When add, update, and delete events happens in the custom resources (CR), the information is sent to the operators. The operators then work to replenish resources to adjust the CR and cluster to the desired state.

Kubernetes Operator Example

Here’s an example of how a Kubernetes operator would look like:

  1. A custom resource that you configure into the cluster. For example a database.
  2. A Pod with the controller part of the operator.
  3. An image of the container with operator code.
  4. A controller querying the control plane for information about resources for the database.
  5. The operator code informs the API server how to maintain conditions for the database. For example when you add the database, the operator allocates ensures enough storage for it, sets a StatefulSet to run the database and a Job to handle configuration. If you delete the database, the operator removes the StatefulSet and Volumes allocated.
  6. The operator maintains database backups. It determines when to create a Pod that connects to the database and take backups. The Pods rely on a ConfigMap and / or a Secret that information about database connection and credentials.
  7. The operator continues to automatically monitor and manage database resources. For example if it identifies a new version of the database, it creates a Job to upgrade it.

Deploying Operators

To deploy an operator, you must add the CRD and its controller to the cluster. Since controllers run outside the control plane like a containerized application, they are deployed the same way. There are two ways to deploy Kubernetes operators: you can use already configured third-party operators or configure your own.

Configuring your operators from scratch can be complex. You require advanced programming skills and thorough knowledge of Kubernetes native controllers and their mechanisms. The following frameworks make it easier to create and configure custom-made operators:

  • Operator Framework
  • Kubebuilder
  • Kubernetes Operators Framework

If you don’t wish to deal with such complexities, use third-party operators that are already configured. These include the Grafana operator, Prothemeus operator, Elastic Cloud operator, etc. Third-party operators are configured to provide solutions to various functions in the cluster. These can include monitoring, upgrading, and creating resources in the cluster. You choose which operator to use based on your application needs.

Using Operators

After injecting an operator into the cluster, create a manifest file to configure an instance of an application based on a custom resource the operator uses. You can then apply the manifest file in the cluster. The operator will monitor and apply the changes maintaining the desired state of the application.

Top Kubernetes Operators

There are many operators in Kubernetes. The following are operator types commonly used by Kubernetes administrators.

  • RBAC Manager Operator: Fairwinds designed the Role-Based Access Control (RBAC) operator to simplify using RBAC on Kubernetes. With minimal manual work, the RBAC manager can help to set up and manage RBAC configurations quickly.
  • HPA Kubernetes Operator: Banzai cloud designed the Horizontal Pod Autoscaler operator to help add pod autoscaling functionalities to Helm charts. The operator tracks Deployments or StatefulSets. It then deletes, updates, or creates HPAs according to predefined configurations.
  • Istio Operator: This operator orchestrates, secures, monitors, and manages communications with deployed microservices. Istio operator simplifies installation, upgrading, and troubleshooting tasks.
  • ECK Kubernetes Operator: The Elastic Cloud operator is designed especially for the Elastic Stack (ELK). It automatically deploys and manages ECK and its features. The features include monitoring clusters, scheduling backups, and managing the dynamic scaling of local storage.
  • Grafana Operator: Redhat designed the Grafana operator to create, configure, and manage Grafana instances on Kubernetes. It simplifies Grafana deployments and makes it available on ingress. It also automates the creation of a dashboard and data source discovery.
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Kubernetes Operator vs Helm Charts

Helm is the pre-dominant package manager for Kubernetes, created by Cloud Native Computing Foundation. It’s an open-source tool that creates templates for Kubernetes components and bundles them into packages known as charts. The charts are then versioned and deployed into clusters.

Kubernetes operators extend Helm charts capabilities by including the application lifecycle stages after initial deployment. Operators complement Helm charts. You can build operators from Helm charts without writing any code. The Kubernetes operator software development kit (SDK) has all the tools you need to do that.

Kubernetes Operator vs Controller

In Kubernetes, controllers implement control loops that maintain the cluster’s desired state continuously. In case an event such as adding, deleting, etc., changes the desired cluster state, the controller takes action to fix the problem.

A Kubernetes operator is an application-specific controller. It uses custom resources to manage applications in the ecosystem. Operators contain application-specific configurations and settings provided within a custom resource. The operator implements the directives based on configurations set in the operator’s logic by the user.

Kubernetes Operator vs CRD

A custom resource (CR) is an extension of the Kubernetes API. Its configurations are defined in the custom resource definition (CRD) objects outlining what’s available to operator users. The Kubernetes API handles CRD objects like built-in objects. This includes interacting via kubectl and inclusion in RBAC policies.

A Kubernetes operator monitors a specific CR to maintain its desired state. If there are any changes, the operator adjusts the current state of the CR to the desired state. By tracking a CR, an operator can automatically perform functions like backing up data and upgrading the application over time. Therefore, ensuring the application has continuous uptime.

Monitoring Kubernetes with Sematext

Sematext Monitoring provides advanced Kubernetes monitoring features that make it easier to keep an eye on the health status of your workloads, from deployments to pods and beyond. This infrastructure monitoring tool allows you to monitor pod, container, and host metrics, as well as collect Kubernetes logs, ensuring comprehensive visibility into your Kubernetes environment.

With Sematext’s out-of-the-box dashboards, you can customize your visualizations and correlate all the necessary data to ensure your workloads’ health, including container-specific metrics such as CPU, memory, disk I/O, and network usage on a per-container basis, as well as host-specific metrics, grouping data seamlessly between hosts, containers, and clusters.

You can configure alert rules for each metric and utilize the anomaly detection feature to get notified as soon as something goes wrong within your Kubernetes environment. Sematext offers multiple notification channels such as email, Slack, and PagerDuty to ensure you can respond quickly to any issues.

Sematext is a one-stop-shop solution, which means that it can adapt to your complex and dynamic infrastructure easily, with its service auto-discovery capabilities. It continuously searches for new apps and services, ensuring they are immediately monitored as they come online without requiring additional configuration.

If you’re interested in using Sematext for Kubernetes monitoring, you can take advantage of their 14-day free trial to see for yourself how easy it is to use. Check out the video below if you need more information about Sematext’s features.

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