Jonas Bonér, CTO of LightBend and creator Akka, discusses using Akka when developing distributed systems. He talks about the Actor Model, and how every Microservice needs to be viewed as a system to be successful. 

Why listen to this podcast:

 - Akka is JVM-based framework design for developing distributed systems leveraging the Actor Model - an approach for writing concurrent systems that treat actors as universal primitives and the most successful model with abstraction has been streaming
 - Circuit breakers in Akka are a backup and retry policy; they protect you by capturing failure data and allow you to roll back 
 - Every Microservice needs to be viewed as a system, it needs to have multiple parts that run on different machines in order to function and be fully resilient - thus is a Microsystem
 - Two different trends have emerged when it comes to hardware and environments: one is the trend toward Multi-core, the is a movement toward virtualized environments and the cloud
 - Saga pattern of managing long running transactions in a distributed system fits very well with messaging style architectures

Notes and links can be found on: http://bit.ly/2kwB2eB

Akka
The Actor Model
When Akka and the Actor Model is the perfect choice
Circuit breakers patterns in distributed systems
Two trends toward Multi-core
Reactive Manifesto
Event Driven vs. Message Driven
Reactive Programming and Streams
Microliths to Microsystems
What do you have to get right before you start trying to deploy a distributed systems?
Working with ML / AI at Lightbend to understand tracing through distributed system
Saga Pattern

More on this:
Quick scan our curated show notes on InfoQ http://bit.ly/2kwB2eB

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Show Notes

Jonas Bonér on the Actor Model, Akka, Reactive Programming, Microservices and Distributed Systems

The promise of Java has always been, “write once, run anywhere.” This was enabled through just-in-time compilation, which allowed developers to target a platform at compilation. But, this flexibility has given rise to comments like, “Java is slow.” What if you could compile Java to Native Code? On this podcast, we’re talking to Thomas Wuerthinger, a senior research director at Oracle Labs. Leading programming language implementation teams for Java, JavaScript, Ruby, and R. He is the architect of the Graal compiler and the Truffle self-optimizing runtime.

Why listen to the podcast:

 - The GraalVM project was initially just a replacement for the JVM C2 just-in-time compiler, but has evolved to include support for multiple languages, as well as an ahead-of-time compiling mode.
 - Support for multiple languages can provide better performance for some languages, as well as making direct calls without inter-process communication.
 - With GraalVM’s AOT compilation, you can statically link system libraries, which allows you to run a static binary on a bare-metal Docker image, without even a Linux distribution.
 - The major benefits of AOT are minimized startup time, memory footprint, and packaging size. This can come with a trade-off in reduced maximum throughput and higher latency.
 - The GraalVM roadmap includes supporting additional platforms, such as Windows and mobile, as well as performance improvements for both the JIT and AOT compilers.

More on this: Quick scan our curated show notes on InfoQ https://bit.ly/2Y2hPk2
You can also subscribe to the InfoQ newsletter to receive weekly updates on the hottest topics from professional software development. bit.ly/24x3IVq

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Thomas Wuerthinger on GraalVM and Optimizing Java With Ahead-of-Time Compilation

Software engineers, architects and team leads have found inspiration to drive change and innovation in their team by listening to the weekly InfoQ Podcast. They have received essential information that helped them validate their software development map. We have achieved that by interviewing some of the top CTOs, engineers and technology directors from companies like Uber, Netflix and more. Over 1,200,000 downloads in the last 3 years.

Thomas Wuerthinger on GraalVM and Optimizing Java With Ahead-of-Time Compilation

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