How PayPal Scaled to Billions of Transactions Daily Using Just 8VMs

How did Paypal take a billion hits a day system that might traditionally run on a 100s of VMs and shrink it down to run on 8 VMs, stay responsive even at 90% CPU, at transaction densities Paypal has never seen before, with jobs that take 1/10th the time, while reducing costs and allowing for much better organizational growth without growing the compute infrastructure accordingly?
PayPal moved to an Actor model based on Akka. PayPal told their story here: squbs: A New, Reactive Way for PayPal to Build Applications. They open source squbs and you can find it here: squbs on GitHub.
The stateful service model still doesn't get enough consideration when projects are choosing a way of doing things. To learn more about stateful services there's an article, Making The Case For Building Scalable Stateful Services In The Modern Era, based on an great talk given by Caitie McCaffrey. And if that doesn't convince you here's WhatsApp, who used Erlang, an Akka competitor, to achieve incredible throughput: The WhatsApp Architecture Facebook Bought For $19 Billion.
I refer to the above articles because the PayPal article is short on architectural details. It's more about the factors the led the selection of Akka and the Continue reading
Some vendors do similar work for each service provider.