Akka.NET The Future of Distributed Programming in .NET Aaron Stannard, Co-founder Akka.NET @Aaronontheweb

High Expectations for Backend Developers

And the obvious ways to scale are wrong.

Enterprise CRUD App

Scenario 1: Surge in User Activity

Obvious Solution: Sharding

Brittle

Scenario 2: Real-time User Interactivity

Obvious Solution: Read-after-Write

Reality

Why is Distributed Programming Hard?

Enter the Actor Model

Actor Model Core Concepts

Actor Model for .NET

Akka.NET Modules Akka – core actor library Akka.Remote – cross-node actor deployment / communication Akka.Cluster – elastic actor networks (HA) Akka.Persistence – event-sourcing, durable actor state & recovery Akka.Streams – streaming workflows Akka.Cluster.Tools – cluster singleton, distributed pub sub Akka.Cluster.Sharding – durable state partitioning Akka.DData – eventually consistent data replication

What's an Actor?

Actors live in a family tree

Actors process one message at a time

Properties of Messages

Messaging Patterns

Messaging Protocols

Communicate with Actors via Reference

Actor References Have Transparent Locations

Akka.Remote & Akka.Cluster: Location Doesn't Matter

Benefits of Clustering

Elastic (Join)

Elastic (Leave)

No Configuration Changes

Recover from Failures

Decentralized

Fastest Response Time?

Stateful Apps Serve Results from Memory

State Locality

State Makes Protocols Work

CAP Theorem

CAP Terminologies

CAP & Protocols

Clustering is for AP (by default)

Fault and Resource Isolation with Actors

Actor Lifecycle Phases

"Just let it crash"

DeathWatch: Subscribe to Actors' Lifecycle

Petabridge