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

On today’s podcast, Wes Reisz talks to Matt Klein about Envoy. Envoy is a modern, high performance, small footprint edge and service proxy. While it was originally developed at Lyft (and still drives much of their architecture), it is a fully open source driven project. Matt addresses on this podcast what he sees as the major design goals of Envoy, answers questions about a sidecar performance impact, discusses observability, and thinks out loud on the future of Envoy.

Why listen to this podcast:

- Envoy’s goal is to abstract the network from application programmers. It’s really about helping application developers focus on building business logic and not on the application plumbing.
- Envoy is a large community driven project, not a cohesive product that does one thing. It can be used as a foundational building blocks to extend into a variety of use cases, including as an edge proxy, as a service mesh sidecar, and as a substrate for building new products.
- While there is performance cost for using sidecar proxies, the rich featureset is often a worthwhile tradeoff. With that said, there is work being done that is greatly improving Envoy’s performance.
- Envoy is built to run Lyft. There were no features that were in Envoy when it was open sourced that were not used at Lyft.
- Envoy emits a rich set of logs and has a plugable tracing system. The goal is observability first and one of the main project goals.
- Lyft deploys Envoy master twice per week.
- Envoy’s roadmap includes work on automating settings (rate limits and retries), focus on ease of operation (such as where things got routed what the internal timings), and additional protocol support such as Kafka.

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Matt Klein on Lyft’s Envoy, Including Edge Proxy, Service Mesh, & Potential AI Use Cases

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Matt Klein on Lyft’s Envoy, Including Edge Proxy, Service Mesh, & Potential AI Use Cases

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