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

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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

Today on The InfoQ Podcast, Wes Reisz talks with Peter Bourgon. Peter is a distributed system engineer working on Fastly. His area of interest is around coordination free replicated systems. The two engineers talk about the space of Conflict-Free Replicated Data Types (CRDTs) specifically in the context of edge compute. Topics covered on the podcast include Edge compute, CRDTs, CAP Theorem, and challenges around building distributed systems. 

Why listen to this podcast:

 - CRDTs (conflict-free replicated data types) are a class of coordination free replication systems (or systems that don’t require strategies such as leader election).
 - An easy way to think of a CRDT is as an associative, commutative, and idempotent data structure plus the operations needed to use it.
The edge is an overloaded term that people tend to define based on where they sit on a spectrum between the customer and the data center. Fastly’s edge is away from the data center and but not to the telephone pole or handset. 
 - RAFT and Gossip are two alternative approaches to using a coordination free replication system like CRDTs.
To get the properties of a CRDT and have useful data types, you have to pay a cost in size and often bytes on the wire. These are challenges that continue to need solutions.
 - Modern Distributed systems and data structures like CRDTs require you to start thinking about state in the system itself. It’s not unusual for a system today to give you multiple results back that the system will have to handle or merge.

More on this: Quick scan our curated show notes on InfoQ https://bit.ly/3dTZOO4
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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Peter Bourgon on CRDTs and State at the Edge

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Peter Bourgon on CRDTs and State at the Edge

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