Akka Streams with Java/Scala

Overview:

This hands-on training is designed to provide a comprehensive understanding of Akka Streams, a powerful toolkit for building asynchronous, non-blocking, and resilient stream processing applications in both Scala and Java. Participants will gain practical experience in implementing stream-based systems, a key paradigm shift from traditional batch and request/response processing models.

Who Should Attend:

• Software engineers and developers familiar with Scala or Java who want to explore reactive programming and stream-based data processing.
• Architects and technical leads aiming to design scalable and resilient data pipelines.
• Data engineers and backend developers interested in enhancing their skills in building real-time and large-scale data streaming applications.

Key Topics:

Introduction to Akka Streams:

• Understanding the basics of Akka Streams and its integration with the Akka ecosystem.
• Differences between traditional data processing models and stream-based processing.

Getting Started with Akka Streams:

• Setting up the development environment for Akka Streams in Scala/Java.
• Creating your first stream and understanding core concepts like Source, Sink, Flow, and Graph.

Stream Composition and Transformation:

• Implementing basic stream processing using various transformation stages.
• Working with custom processing stages to build complex stream topologies.

Backpressure and Buffering:

• Understanding the importance of backpressure in stream processing.
• Implementing buffering strategies to manage varying data rates in streams.

Stream Materialization and Lifecycle:

• Managing stream materialization and understanding the lifecycle of streams.
• Exploring the role of materialized values in stream processing.

Advanced Stream Patterns:

• Implementing advanced patterns like fan-out, fan-in, and dynamic stream handling.
• Designing fault-tolerant streams with supervision strategies.

Integration with External Systems:

• Connecting Akka Streams with external data sources and sinks, including databases, file systems, and web services.
• Managing data flow between Akka Streams and other reactive systems.

Testing and Debugging Streams:

• Writing test cases for streams using Akka TestKit and Akka Stream TestKit.
• Debugging stream pipelines and understanding common pitfalls.

Practical Exercises:

• Hands-on labs to reinforce each concept with practical coding exercises.
• Real-world scenarios where participants will design, implement, and troubleshoot stream-based systems.

Takeaways:

By the end of this training, participants will have the skills and confidence to build robust, scalable, and resilient stream processing applications using Akka Streams. You will walk away with code samples, design patterns, and best practices that you can immediately apply to your projects.

Prerequisites:

• Basic knowledge of Scala or Java.
• Familiarity with concurrent programming and reactive principles is beneficial but not required.

Duration:

• Number of sessions: 5-7 (can be adjusted based on the depth of content and participant needs).