akka webinars

How to use CQRS in Akka 2_6 video


CQRS is a pattern for decoupling write operations from read operations. This short video illustrates how to implement CQRS with Akka 2.6 by reading tagged events. The video continues from where the Event Sourcing video left off.


akkasoftware development webinars

Managing Blocking in Akka video


A four-minute video explaining why it is bad to block inside an actor, and how you can use custom dispatchers to manage blocking when you cannot avoid it. The slides and sample code are available on GitHub.


akkasoftware development webinars

Cloudstate Towards Stateful Serverless


A four-minute video explaining why it is bad to block inside an actor, and how you can use custom dispatchers to manage blocking when you cannot avoid it. The slides and sample code are available on GitHub.


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Event Sourcing with Akka 2_6 video


An eight minute video demonstrating how to use Event Sourcing in Akka 2.6. Sample code from the Akka CQRS example project (Java or Scala). Including how to integrate with Cluster Sharding and Akka HTTP.


akka-platformakkasoftware development webinars

Lessons From HPE From Batch To Streaming For 20 Billion Sensors With Lightbend Platform


A ten minute overview of Akka Cluster Sharding, how it can help, and a code walk through of basic usage of the Akka Cluster Sharding API. We review the architecture and code in the Akka Cluster Sharding sample Scala app, including how to integrate Akka HTTP with Cluster Sharding.


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Introduction to Akka Cluster Sharding video


A ten minute overview of Akka Cluster Sharding, how it can help, and a code walk through of basic usage of the Akka Cluster Sharding API. We review the architecture and code in the Akka Cluster Sharding sample Scala app, including how to integrate Akka HTTP with Cluster Sharding.


akka-platformakkasoftware development webinars

Concept Drift Monitoring Model Quality in Streaming ML Applications


Most machine learning algorithms are designed to work with stationary data. Yet, real-life streaming data is rarely stationary. Machine learned models built on data observed within a fixed time period usually suffer loss of prediction quality due to what is known as concept drift.


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Lessons Learned From PayPal Implementing Back-Pressure With Akka Streams And Kafka


Akka Streams and its amazing handling of streaming with back-pressure should be no surprise to anyone. But it takes a couple of use cases to really see it in action - especially in use cases where the amount of work continues to increase as you’re processing it.


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Distributed Systems Done Right Why Java Enterprises Are Embracing The Actor Model


Most likely, your job is heavily focused on helping your organization modernize for the digital era. As the days of purely Object-Oriented Programming and related frameworks come to a close, enterprises migrating to distributed, cloud infrastructures are embracing a different approach: the Actor Model.


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The Basics Of Reactive System Design For Traditional Java Enterprises


Like most things in life, in software there exists an Old and a New way of doing things. The growth of computing power, increase in the sheer number of users, cheaper and more available hardware, and the explosive IoT market mandates that we build our systems using modern methods that diverge from past.


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Exploring Reactive Integrations with Akka Streams Alpakka and Kafka


Since its stable release in 2016, Akka Streams is quickly becoming the de facto standard integration layer between various Streaming systems and products. Enterprises like PayPal, Intel, Samsung and Norwegian Cruise Lines see this is a game changer in terms of designing Reactive streaming applications by connecting pipelines of back-pressured asynchronous processing stages.


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