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Reactive Applications with Akka.NET
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Reactive Applications with Akka.NET is a hands-on book that builds on fundamental concepts to teach you how to create reliable and resilient applications in the reactive style.An introduction to how we're going to write software in the future.
Table of Contents takes you straight to the bookdetailed table of contents
Part 1 The road to reactive
1 Why reactive?
1.1 The heart of the Reactive Manifesto
1.2 Reactive systems vs. reactive programming
1.3 Applying Akka.NET
1.3.1 Where to use Akka.NET
1.3.2 Where not to use Akka.NET
1.4 How does Akka.NET work?
Summary
2 Reactive application design
2.1 Basic reactive system design
2.2 Reactive e-commerce application with actors
2.2.1 A reactive shopping cart
2.2.2 Changing states of actors
2.2.3 Making the purchase
2.2.4 Data transfer between services
2.2.5 Scaling work with routers
2.2.6 Wrapping up
2.3 Building on reactive foundations
2.3.1 Publishing the e-commerce application to the world
2.3.2 Storing state within actors
2.3.3 Scaling out across a cluster of machines
2.3.4 Continuing to react to environmental changes
2.3.5 Wrapping up
Summary
Part 2 Digging in
3 Your first Akka.NET application
3.1 Setting up an application
3.2 Actors
3.2.1 What does an actor embody?
3.2.2 What can an actor do?
3.2.3 Defining an actor
3.2.4 Wrapping up
3.3 Deploying an actor
3.3.1 The actor system
3.3.2 Spawning an actor
3.3.3 Wrapping up
3.4 Communicating with actors
3.4.1 Actor addresses and references
3.4.2 Sending a message
3.4.3 Wrapping up
3.5 Case study: Actors, concurrency, and phone billing
Summary
4 State, behavior, and actors
4.1 Preparing for the next message
4.2 Setting appropriate runtime behaviors
4.2.1 Switchable behaviors
4.2.2 Become and unbecome
4.2.3 Wrapping up
4.3 Finite state machines
4.3.1 Understanding finite state machines
4.3.2 Using finite state machines in a concurrency model
4.3.3 Converting a finite state machine into an actor
4.3.4 Using the finite state machine actor
4.3.5 Wrapping up
4.4 Case study: State machines, states and events, marketing analytics campaign
Summary
5 Configuration, dependency injection, and logging'
5.1 Why do you need configuration?
5.2 Configuring an actor deployment
5.2.1 Understanding Props
5.2.2 Wrapping up
5.3 Dependency injection (DI)
5.3.1 Introducing dependency injection
5.3.2 Configuring a DI container
5.3.3 Wrapping up
5.4 Configuring with HOCON
5.4.1 What is HOCON?
5.4.2 Loading configuration into an actor system
5.4.3 Wrapping up
5.5 Logging
5.5.1 Why do you need logging?
5.5.2 Writing to the log
5.5.3 Customizing a logger deployment
5.5.4 Wrapping up
5.6 Case study: Configuration and distributed systems
Summary
6 Failure handling
6.1 Understanding failures
6.2 Handling application-level failures
6.2.1 Responding to application errors
6.2.2 The Akka.NET supervision tree
6.2.3 Failing fast
6.2.4 The actor lifecycle
6.2.5 Watching for the deaths of other actors
6.2.6 Interface-level failures
6.2.7 Wrapping up
6.3 Understanding transport-level failures
6.3.1 Writing applications that handle message loss
6.3.2 Wrapping up
6.4 Case study: Supervision, failure, chat bots
Summary
7 Scaling in reactive systems
7.1 Scaling up and scaling out
7.2 Distributing work
7.2.1 Routers
7.2.2 Pools and groups
7.2.3 Wrapping up
7.3 Routing strategies
7.3.1 Random routing
7.3.2 Round-robin routing
7.3.3 Smallest-mailbox router
7.4 Case study: Scaling, throughput, advertising systems
Summary
8 Composing actor systems
8.1 Introducing Akka.NET remoting
8.2 Preparing to use remoting
8.2.1 Installing Akka.Remote
8.2.2 Configuring remoting for a project
8.3 Communicating with remote actors
8.3.1 Sending messages to remote actors
8.3.2 Remote deployment of actors
8.3.3 Wrapping up
8.4 Elastic scale across machines
8.4.1 Configuring a router to use multiple machines
8.4.2 Wrapping up
8.5 Failure handling across machines
8.6 Akka.Remote security
8.6.1 Limiting messages that can be sent over the network
8.6.2 Restricting available remote actor targets
8.6.3 Wrapping up
8.7 Case study: Remoting, network applications, web server, and backend server
Summary
Part 3 Real-life usage
9 Testing Akka.NET actors
9.1 Introducing Akka.TestKit
9.2 Unit testing actors
9.2.1 Spawning test actors
9.2.2 Validating internal data
9.2.3 Testing FSMs
9.2.4 Wrapping up
9.3 Integration testing actors
9.3.1 Creating test specifications
9.3.2 Asserting message responses
9.3.3 Time-based testing
9.3.4 Test probes
9.3.5 Wrapping up
9.4 Testing distributed applications with MultiNode TestKit
9.4.1 MultiNode specs
9.4.2 Testing individual actor systems
9.4.3 Barriers
9.4.4 Testing for network failure
9.4.5 Wrapping up
9.5 Case study: Testing, test-driven development, unit testing
Summary
10 Integrating Akka.NET
10.1 Integrating with ASP.NET
10.2 Integrating with SignalR
10.2.1 Communicating through an actor
10.2.2 Connecting to the user’s web browser
10.2.3 Wrapping up
10.3 Custom integrations with akka.io
10.3.1 Creating a listening socket
10.3.2 Sending data through akka.io
10.3.3 Wrapping up
10.4 Case study: IO, integration, IoT applications
Summary
11 Storing actor state with Akka.Persistence
11.1 Understanding event sourcing
11.2 Using Akka.Persistence
11.2.1 Writing persistent actors
11.2.2 Configuring a journal
11.2.3 Wrapping up
11.3 Akka.Persistence performance tuning
11.3.1 Snapshot stores
11.3.2 Async write journals
11.3.3 Wrapping up
11.4 Akka.Persistence performance tuning
11.4.1 At-least-once delivery
11.4.2 Upgrade strategies for applications using event sourcing
11.4.3 Wrapping up
11.5 Case study: Persistence, storage, staged upgrades
Summary
12 Building clustered applications with Akka.Cluster
12.1 Introducing Akka.Cluster
12.2 Cluster-aware routers
12.2.1 Creating cluster-aware router groups
12.2.2 Creating cluster-aware router pools
12.2.3 Wrapping up
12.3 Working with cluster gossip
12.3.1 Retrieving cluster state
12.3.2 Handling cluster gossip messages
12.3.3 Wrapping up
12.4 Cluster singleton
12.4.1 Wrapping up
12.5 Cluster sharding
12.5.1 Creating a new shard
12.5.2 Communicating with actors in a shard
12.5.3 Handling passivation in shards
12.5.4 Wrapping up
12.6 Distributed publish-subscribe
12.6.1 Topic messaging
12.6.2 Point-to-point messaging
12.6.3 Wrapping up
12.7 Cluster client
12.8 Case study: Clustering, scaling, cluster management
Summary
13 Akka.NET and reactive programming in production
13.1 Designing with actors
13.2 Handling failure
13.3 Designing for scale
13.4 Handling configuration
13.5 Ingesting data
13.6 Testing
13.7 Real-time integration
13.8 Data persistence
13.9 Cluster scale-out
13.8 Data persistence
Conclusion
About the Technology
Enterprise-scale software needs to be unfailingly reliable, consistently performant under unpredictable loads, and easy to scale and maintain. Reactive applications guarantee these qualities through clear isolation of system components and message-based communication. Akka.NET ports the battle-tested Akka Actors toolkit from the JVM, radically simplifying the concurrency and asynchronous message handling at the heart of a reactive system.About the book
Reactive Applications with Akka.NET teaches you to write high-performance, concurrent systems without explicitly managing threads and locking. You'll experience the power of Akka.NET and the Actors concurrency model by exploring a real-world case study in each chapter. As you go further, you'll start to grok the power of asynchronous communication in a distributed environment and take on practical tasks like deploying, debugging, and establishing performance guarantees.
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