Introduction to Akka Framework

Current challenge in writing Distributed Application

 Writing concurrent programs is hard. Having to deal with threads, locks, race conditions, and so on is highly error-prone and can lead to code that is difficult to read, test, and maintain.

My assumption is that most of people have worked with the Java multithreading model, and they are aware of the fact that it is very difficult to write multithreaded concurrent applications. This is because we have to manage low-level details like locking an object, releasing the lock on the object, notifying, waiting for threads to join each other to complete a task, and freeing up resources that a thread holds. It is difficult for us to write multithreaded programs, because we have to focus more on thread management details instead of focusing on business logic only.

Many therefore prefer to avoid multithreading altogether. Instead, they employ single-threaded processes exclusively, relying on external services (such as databases, queues, etc.) to handle any needed concurrent or asynchronous operations. While this approach is in some cases a legitimate alternative, there are many scenarios in which it is simply not a viable option. Many real-time systems – such as trading or banking applications, or real-time games – don’t have the luxury of waiting for a single-threaded process to complete (they need the answer now!). Other systems are so compute- or resource-intensive that they would take an inordinate amount of time (hours or even days in some cases) to run without introducing parallelization into their code.

One fairly common single-threaded approach is to use an event-based, non-blocking paradigm. While this does help performance by avoiding context switches, locks, and blocking, it still does not address the issues of using multiple processors concurrently (doing so would require launching, and coordinating between, multiple independent processes).

So does this mean you have no choice but to journey deep into the bowels of threads, locks, and race conditions in order to build a concurrent application?

Thanks to the Akka framework, the answer is no. 

Akka Framework

In today's world, computer hardware is becoming cheaper and more powerful, as we have multiple cores on a single CPU chip. As cores keep on increasing, with the increasing power of hardware, we need a state of the art software framework which can use these cores efficiently.

Akka is such a framework, or you can say, a toolkit, which utilizes the hardware cores efficiently and lets you write performant applications.

As we are living in big data world, a lot of traffic comes to our servers, and we want our servers to respond in milliseconds instead of seconds. Akka is here to scale up the application as the load on it increases.

We want our application to run day and night continuously with high availability.
Akka is here to build fault tolerance for our application.

Akka is a toolkit for writing truly concurrent, fault-tolerant, distributed, and scalable applications, which can run for days, months, and years without stopping, and can heal themselves in case of failure. It is very hard to write concurrent applications using the plain Java multithreading model, which also satisfies fault-tolerant, distributed, and scalable properties. Akka provides a high-level of abstraction to build such an application that satisfy these properties. 

In short Akka is open source middleware for building highly concurrent distributed and fault tolerant systems on the JVM. Akka is built with Scala, but offers both Scala and Java APIs to developers

Akka follows reactive model principles.Reactive applications aim at replacing traditional multithreaded applications with an architecture that satisfies these requirements:

• Resilient: Applications that can heal themselves, which means they can recover from failure, and will always be responsive, even in case of failure like if we get errors or exceptions
• Elastic: A system which is responsive under varying amount of workload, that is, the system always remains responsive, irrespective of increasing or decreasing traffic, by increasing or decreasing the resources allocated to service this workload
• Message Driven: A system whose components are loosely coupled with each other and communicate using asynchronous message passing, and which reacts to those messages by taking an action
• Responsive: A system that satisfies the preceding three properties is called responsive