Chapter 7. Scaling in reactive systems
This chapter covers
- Evaluating the difficulties of traditional scaling approaches
- Comparing the Akka.NET scaling approach to traditional methods
- Using routers in Akka.NET
- Dynamically scaling actors to react to load changes
In chapter 1, you embraced the goal of building responsive systems to ensure the best possible UX. In chapter 3, you saw how a message-passing architecture lets you break free of systems that rely heavily on blocking API calls. You also saw, in chapter 6, how you can ensure that your applications continue to work in gray-sky as well as blue-sky conditions. By considering where failures are likely to occur and using the failure detection and recovery tooling in Akka.NET, you can respond to errors in your application before they significantly impact your application’s performance and negatively affect the end user’s experience. Now, we’ll look at how you can handle increased traffic and prevent the extra pressure from affecting the performance of your application.