Section outline

• Select section Day 1: Introduction & Setup

  Day 1: Introduction & Setup

  Collapse all Expand all

  • What is Apache Flink and stream processing

  • Job Manager, Task Manager, Flink deployments (Local, YARN, Kubernetes)

  • DataStream vs Dataset API, Web UI overview

  • Lab: Set up Flink and run your first Flink job
• Select section Day 2: DataStream API & State Management

  Day 2: DataStream API & State Management

  • Kafka integration, Flink transformations, event-time processing

  • Checkpointing, fault tolerance, and Flink savepoints

  • Stateful operators and windowing (Tumbling, Sliding, Session)

  • Lab: Implement custom sources/sinks, use Watermarks and state
• Select section Day 3: Table API, SQL & Security

  Day 3: Table API, SQL & Security

  • Table API and SQL queries on streaming data

  • Flink Connectors (Kafka, S3, JDBC, Elasticsearch)

  • Authentication (Kerberos, OAuth), RBAC, TLS configuration

  • Lab: SQL queries on Kafka streams, secure Flink job deployment
• Select section Day 4: Tuning & Real-World Use Cases

  Day 4: Tuning & Real-World Use Cases

  • Resource optimization, memory and GC tuning, Flink metrics

  • Complex Event Processing (CEP), Flink ML use cases

  • Final capstone project: end-to-end Flink pipeline (fraud detection, analytics, etc.)

  • Quiz and best practices for production