Unlocking the Power of Flink with Kubernetes Operator: Simplify Data Management for Data as a Service

In my previous blog post, I discussed deploying Flink jobs on Kubernetes without using a Flink operator. While this approach was functional, it required manual actions to manage the Flink clusters. Today, we take a step further by adding Flink Operator on Kubernetes to orchestrate and manage the lifecycle of the Flink clusters efficiently.

Don’t forget to dive into the previous posts of the series Data as a Service:

• Data as a Service using ScyllaDB
• Enhancing Data as a Service with GraphQL

Why Flink Kubernetes Operator

The Apache Flink documentation highlights the key aspects of the Flink Kubernetes Operator:

The Flink Kubernetes Operator extends the Kubernetes API with the ability to manage and operate Flink Deployments. The operator features the following amongst others:

- Deploy and monitor Flink Application and Session deployments
- Upgrade, suspend and delete deployments
- Full logging and metrics integration
- Flexible deployments and native integration with Kubernetes tooling
- Flink Job Autoscaler