On-demand webinar Apache Spark has become the de facto open source standard for big data processing for its ease of use and performance. The open source Delta Lake project improves Spark’s data reliability, with new capabilities like ACID transactions, Schema Enforcement, and Time Travel.
A short video where we walk through the basics of the actor model writing an actor in Java with the new Actor APIs Akka 2.6
Today’s applications are expected to support a multitude of devices, employ hybrid cloud deployments, persist petabytes of data, deliver millisecond response time and have near-perfect reliability. Traditional patterns and practices for enterprise Java application development simply can’t support these demands, or are so complicated that entire systems can be brought down by single points of failure.
Still chugging along with a monolithic enterprise system that’s difficult to scale and maintain, and even harder to understand? In this three-part series on Microservices for enterprise architects, we explain why a microservice-based architecture that consists of small, independent services is far more flexible than the traditional all-in-one systems that continue to dominate today’s enterprise landscape.
The term ‘streams’ has been getting pretty overloaded recently–it’s hard to know where to best use different technologies with streams in the name. In this talk by noted hAkker Konrad Malawski, we’ll disambiguate what streams are and what they aren’t, taking a deeper look into Akka Streams (the implementation) and Reactive Streams (the standard).
Microservices has become a difficult term to pinpoint as more people use it to describe various approaches to building service-based applications. Many of these approaches have become anti-patterns to scale, such as sharing code between services and traditional monolithic CRUD data storage strategies.
What type of platform does it take to live stream the world’s biggest media and sports events to mobile devices? In this webinar with special guest Christopher Webster, Associate Fellow at Verizon, you can get a feel of what it takes to power one of Verizon’s latest offerings, its go90 platform.
Why have stream-oriented data systems become so popular, when batch-oriented systems have served big data needs for many years? Batch-mode processing isn’t going away, but exclusive use of these systems is now a competitive disadvantage.
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.
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.
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.
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.