Course description
Programming Reactive Systems
Reactive programming is a set of techniques for implementing scalable, resilient and responsive systems as per the Reactive Manifesto. Such systems are based on asynchronous message-passing, and their basic building-blocks are event handlers. This course teaches how to implement reactive systems in Scala and Akka by using high-level abstractions, such as actors, asynchronous computations, and reactive streams.
Who should attend?
Prerequisites:
You should have at least one year programming experience, preferably in Scala or a functional language.
Training content
During this course we’ll go through:
- reminder on functional programming in Scala (case classes,higher-order functions, standard collections),
- asynchronous programming with Future API,
- actor programming model,
- introduction to Akka actors,
- failure handling with actors using supervision,
- actor lifecycle monitoring and Receptionist pattern,
- persistent actor state,
- distributing actors in a cluster,
- eventual consistency,
- actor composition,
- scaling actor systems,
- protocols in Akka typed,
- Akka typed adapters,
- challenges of stream processing,
- the Reactive Streams specification,
- introduction to Akka Streams,
- streams failure handling and processing rate
- streaming protocols and stream composition,
- stateful operations and materialized values,
- splitting and merging streams,
- integrating streams with typed actors.
Course delivery details
This course is offered through University of Naples Federico II, a partner institute of EdX.
8-16 hours per week
Costs
- Verified Track -$199
- Audit Track - Free
Certification / Credits
What you'll learn
- use, transform and sequence asynchronous computations using Future values,
- write concurrent reactive systems based on Actors and message passing, using untyped Akka and Akka Typed,
- design systems resilient to failures,
- implement systems that can scale out according to a varying workload,
- transform and consume infinite and intermittent streams of data with Akka Stream in a non-blocking way,
- understand how back-pressure controls flows of data
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