How to Deploy Apache Flink on Kubernetes as a Self-Hosted GCP Dataflow Alternative

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Apache Flink is an open-source distributed stream and batch processing engine that replicates most capabilities of Google Cloud Dataflow without incurring managed service costs or vendor lock-in. A technical guide outlines how to deploy Flink on Kubernetes using the Flink Kubernetes Operator, covering both Session and Application Cluster configurations. The setup supports stateful processing, exactly-once Kafka integration, checkpointing, savepoints, and Apache Beam pipelines via the Flink Runner. Monitoring can be handled through Prometheus and Grafana, while high availability and security are addressed using native Kubernetes RBAC and network controls. The guide also includes migration strategies for teams looking to move existing workloads from Google Cloud Dataflow to a self-managed Flink environment.

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