Training

This course is a hands-on introduction to Apache Flink for Java and Scala developers who want to learn to build streaming applications.

After taking this course you will have learned enough about Flink's core concepts, its DataStream API, and its distributed runtime to be able to develop solutions for a wide variety of use cases, including data pipelines and ETL jobs, streaming analytics, and event-driven applications. 

The programming exercises are oriented around common use cases, and will give you a chance to see how the pieces of the API work together to solve real problems. Other hands-on sessions provide an introduction to practical topics, such as how to deploy, stop, upgrade, and rescale your jobs

• Introduction to Stream Processing and Apache Flink
• Foundations of the DataStream API
• Data Pipelines and Stateful Stream Processing
• Event Time and Watermarks
• Process Functions, Side Outputs, and Timers
• Windows and Streaming Analytics
• Testing
• The Flink Runtime
• Fault Tolerance
• The Connector Ecosystem
• Application Patterns: Data Enrichment, Joins, Broadcast State
• Application Evolution

No prior knowledge of Apache Flink is required.

For the hands-on exercises you will need a laptop with at least 8 GB RAM (MacOS, Linux, or Windows), with these tools installed:

• Git
• Java 8 or 11 JDK (a JRE is not sufficient)
• An IDE for Java (or Scala) development
• Docker

Format

As a remote, instructor-led training, this is delivered as three sessions, each about 2.5 hours long, with the hands-on portions assigned as homework to be done between the training sessions.

This course is a hands-on introduction to key topics relating to putting Flink applications into production, including configuring and tuning your job, deployment, operations, and maintenance. Also included is a solid introduction to the organization of the Flink runtime to help you tune and troubleshoot your applications. The exercises provide a hands-on introduction to these same topics.

The intended audience includes both developers and operations staff.

• Intro to Stateful and Timely
• Streaming with Flink
• Flink’s Runtime Architecture
• Fault Tolerance
• Managing Flink: the CLI, WebUI, and REST API
• Metrics, Monitoring, and Alerting
• Scaling: Configuring and Managing State Backends and Checkpointing
• Capacity Planning
• Deployment
• Application Evolution
• Filesystems

No prior knowledge of Apache Flink is required, but the course assumes familiarity with issues arising in distributed systems.

You will need a laptop with at least 8 GB RAM and Docker installed.

Format

As a remote, instructor-led training, this is delivered in two 3-hour sessions, with hands-on exercises assigned as homework to be done between the training sessions.