In the beginning we thought we wanted to start using something like RabbitMQ or maybe Kafka or maybe ActiveMQ. Back then we only had a few developers and no ops people. That has changed now, but we didn't really look forward to setting up a queuing cluster and making sure that all works.

What we did instead was we looked at what services Amazon offers to see if we can use those to build our own messaging system within those services. That's basically what we did. We wrote some clients in Ruby that can basically do the entire orchestration for us, and we run all our messaging on both SNS and SQS. Basically what you can do in Amazon services is you can use Amazon Simple Notification Service, so SNS, for creating topics and you can use queues to subscribe to these topics. That's basically all you need for a messaging system. You don't have to worry about scalability at all. That's what really appealed to us.

This isn't exactly low-latency (10s to 100s of milliseconds), but it has good throughput and a simple API. There is good reliability, and there is no configuration necessary to get up and running. A hosted queue is important when trying to move fast.

The poster child for scalable messaging systems, RabbitMQ has been used in countless large scale systems as the messaging backbone of any large cluster, and has proven itself time and again in many production settings.

Rabbit acts as our coordinator for all actions that happen during game time. All worker containers connect to rabbit in order to receive game events and emit their own events when applicable.

Used as central Message Broker; off-loading tasks to be executed asynchronous, used as communication tool between different microservices, used as tool to handle peaks in incoming data, etc.

RabbitMQ is the enterprise message bus for our platform, providing infrastructure for managing our ETL queues, real-time event notifications for applications, and audit logging.

RabbitMQ is an all purpose queuing service for our stack. We use it for user facing jobs as well as keeping track of behind the scenes jobs.

SQS is the bridge between our new Lambda services and our incumbent Rails applications. Extremely easy to use when you're already using other AWS infrastructure.

Remote broker and local client for incoming data feeds. Local broker for republishing data feeds to other systems.

Primary message queue. Enqueueing operations revert to a local file-system-based queue when SQS is unavailable.

I can't afford to lose data if Dynamo throttles my writes, so everything goes into a message queue first.