![]() ![]() When I first learned about the Operator Pattern, I had an overwhelming feeling of hype. Why Use the Elasticsearch Operator: Pros and Cons? It also makes it much easier to handle operational and cluster administration tasks. Like playing with Lego bricks, changing things around is incredibly simple. You can add, remove, and update resources with ease. For the rest of this tutorial, I’ll demo how to manage and run this particular Elasticsearch Operator.ĮCK simplifies deploying the whole Elastic stack on Kubernetes, giving you tools to automate and streamline critical operations. However, I won’t go into details about them except for the official ECK Operator built by Elastic. Some of them are made by active open-source contributors, however, only one is written and maintained by Elastic. There are a few different Elasticsearch Operators you can choose from. ![]() The Elasticsearch Operator automates the process of managing Elasticsearch on Kubernetes. Let me explain what the Elasticsearch Operator is first. The Controller will normally run outside of the control plane, much as you would run any containerized application. You deploy an Operator by adding the Custom Resource Definition and Controller to your cluster. It captures how you can write code to automate a task beyond what Kubernetes itself provides. The point of using the Operator Pattern is to help you, the DevOps engineer, automate repeatable tasks. It serves and handles the storage of your custom resource. What’s so cool about this? Well, you don’t have to write a custom configuration to handle the custom resource. When you define a CRD object, it creates a new custom resource with a name and schema that you specify. In this tutorial, you’ll learn how to create a custom resource in a separate namespace. By using the CustomResourceDefinition (CRD) API resource, you can define custom resources. ![]() Operators are extensions to Kubernetes that use custom resources to manage applications. With that out of the way, let’s jump into the tutorial! It automates the deployment, provisioning, management, and orchestration of Elasticsearch on Kubernetes.īefore we get into the bulk of this tutorial, keep in mind that if you need some direct help, Sematext offers a full range of services for Elasticsearch. The Elasticsearch Operator I’ll be using in this tutorial is the official Operator from Elastic. At Sematext, we’re using the StatefulSet approach, which works great for us. Both solutions are valid but are useful for different scenarios. Keep in mind there are no silver bullets. You can also peek at Kubernetes monitoring integration on your own. I will also explain how to quickly set up basic monitoring with the Sematext Elasticsearch monitoring integration. It will also guide you through installing and running the Elasticsearch Operator on a Kubernetes cluster. This article will show you the pros and cons of using the Operator Pattern versus StatefulSets like I explained in our previous tutorial about Running and Deploying Elasticsearch on Kubernetes. The Operator Pattern is set out to help DevOps teams manage a service or set of services by automating repeatable tasks. Operators follow Kubernetes principles, including the control loop. With the addition of custom resources and the operator pattern, you can now make use of extensions, or add-ons as I like to call them, to the Kubernetes API that help you manage applications and components. Have you ever grown tired of running the same kubectl commands again and again? Well the good folks over at the Kubernetes team understand you. Final Thoughts About the Elasticsearch Operator.Cleaning Up and Deleting the Elasticsearch Operator.How to Run and Deploy Kibana with the Elasticsearch Operator.Upgrade and Configure the Elasticsearch Cluster.How to Run and Deploy the Elasticsearch Operator on Kubernetes.Why Stay Away From the Elasticsearch Operator?.Why Use the Elasticsearch Operator: Pros and Cons?. ![]()
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