The Business Case for Actors and Akka.NET

From the 1980s to Present Day

Akka.NET is a .NET implementation of the actor model.

The actor model is an old technology, originating in 1973 as an approach to parallel computing at a time when it looked like the computers of the future might be constructed using thousands of small, low-powered CPUs. History didn’t turn out that way thanks to Moore’s Law; CPUs became faster and faster and modern machines were developed with a small number of very high-powered CPUs.

Despite that, the actor model is immensely popular and runs some of the world’s most important software today. Amazon’s SimpleDb, RabbitMQ, Riak, CouchBase, Goldman Sachs, Motorola, Blizzard Games, Cisco, eBay, Credit Suisse, AMN Healthcare, Bank of America, McGraw Hill Financial, and scores of other major organizations use implementations of the actor model to power mission-critical applications responsible for the world’s largest companies.

So why is the actor model so popular today? Why are so many businesses using it for mission-critical applications?

First Adopters of the Actor Model: Telecoms

The truth of the matter is, the actor model has been popular for a long time through the Erlang programming language. Erlang was the first large-scale, production usable implementation of the actor model - developed originally by Joe Armstrong as a proprietary language at Ericsson in 1986 (open sourced later) to build telephone exchanges. Today it’s used to power the GPRS, 3G, and LTE cellular networks that depend Ericsson’s products.

Erlang Logo

Although the actor model was originally developed as a means for running applications on types of computer hardware that never really took off, the emergence of electronic computer networks in the late 70s and early 80s gave the actor model an extremely viable commercial application: distributed and concurrent systems.

As the Internet grew and more...

Performance Testing Should be Mandatory

Plus, How to Actually do it Right

Back in December I released the first publicly available version of NBench - Petabridge’s automated .NET performance testing and benchmarking framework.

NBench Logo

NBench has proven itself to be an invaluable part of our QA process for Akka.NET and scores of other projects, for one critical reason: performance is a mission critical feature for an increasingly large number of applications. And if you can’t measure performance, then you’re shipping a totally untested feature to your end-users.

The Impact of Poor Performance

A simple anecdote to illustrate the real-world impact of shipping non-performant software.

One of my favorite musicians, whom I have never seen live before, is coming to town and I wanted to purchase a ticket. I was out of the country the day tickets went on sale, so if I wanted to attend I’d need to buy a ticket from a secondary market.

I decided to give a new company I’d never purchased tickets through before, SeatGeek, a try. I quickly found two tickets for about $100 each, went through the checkout process, put in my payment information, and submitted payment. A few seconds later I get an error message back letting me know that the tickets were no longer available. So I repeat this process a few more times with progressively more expensive tickets with no success.

Eventually I just gave up and SeatGeek lost about $500 worth of revenue, because I lost any confidence that their reported ticket inventory was available. The crucial error was that the underlying software responsible for reporting inventory availability under-performed - it wasn’t able to keep up with the demand of actual customers, and as a result they nearly lost my business. I tried again on a whim immediately before writing this post and...

This is a follow-up to our last post, “How to Guarantee Delivery of Messages in Akka.NET.” In that post we introduced the AtLeastOnceDeliveryActor and talked about strategies for retrying deliveries of messages in order to make sure they’re successfully procssed.

In this post we’re going to talk about “At Least Once” delivery’s big brother, “Exactly Once” delivery - and why you should try to avoid it if at all possible.