Flink for Developers builds skills in designing and building stream processing applications with Apache Flink, across two intensive, hands-on days. The course covers the key concepts needed to design and build a stream processing application from scratch. Day one starts with core Flink concepts and moves into design patterns for event-driven applications, data analytics applications, and data pipeline applications. Day two goes deeper into production concerns: state management, connectors and integrations, and how to monitor application metrics, APIs, and logging.
The Apache Flink Overview module introduces the DataStream API and Flink’s event-time processing model before attendees write their first streaming job. Event-Driven Applications shows how to react to individual events in near real time, using patterns like the process function and side outputs. Data Analytics Applications shifts focus to windowing, aggregation, and continuous queries over unbounded streams, while Data Pipeline Applications closes day one by building ETL-style jobs that move and transform data between systems.
Day two turns to production concerns, starting with Flink State Management, where attendees checkpoint and recover application state after failures. Connectors and Integrations follows, connecting Flink jobs to Kafka, databases, and file systems attendees are likely to use at work. The course closes with two operational modules: Metrics, Monitoring, and API covers exposing job health through Flink’s REST API and metrics system, while Logging rounds out the course with practical guidance on diagnosing failed or slow-running jobs.
Who Should Attend
Developers, IT and QA Staff, Technical Managers, DevOps and Build personnel
What Attendees Will Learn
Upon completing Flink for Developers, attendees will be able to:
- Explain Apache Flink architecture and stream processing concepts
- Build event-driven applications using Apache Flink
- Build data analytics applications with Flink
- Build data pipeline applications with Flink
- Manage application state in Flink stream processing jobs
- Integrate Flink with external systems using connectors
- Monitor Flink applications using metrics, APIs, and logging
Prerequisites
Basic Linux command line skills are valuable but not required.