Process queues

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

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.

Message queue for our Elastic Beanstalk worker environments.

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.

https://ifunny.co

Great pick-n-go queue, be prepared for occasionally outage in especially us-east-1 region.

Distributed background job queue.

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

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.

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Message queue that the Raspberry Pi will retrieve messages.

For asynchronous data processing

Batch processing.

SQS is the primary means of communication between microservices.