Over time, we have seen the number of Kubernetes-related queries on our community mailing list and Slack channels soar. In this post we’d like to explain the basics of a DIY deployment of RabbitMQ on Kubernetes: what Kubernetes resources will be necessary, how to make sure RabbitMQ nodes use durable storage, how to approach configuration of sensitive values, and so on.

So today I would like to talk about some aspects of RabbitMQ’s performance. There are a huge number of variables that feed into the overall level of performance you can get from a RabbitMQ server, and today we’re going to try tweaking some of them and seeing what we can see.

One of the problems we face at the RabbitMQ HQ is that whilst we may know lots about how the broker works, we don’t tend to have a large pool of experience of designing applications that use RabbitMQ and which need to work reliably, unattended, for long periods of time. We spend a lot of time answering questions on the mailing list, and we do consultancy work here and there, but in some cases it’s as a result of being contacted by users building applications that we’re really made to think about long-term behaviour of RabbitMQ. Recently, we’ve been prompted to think long and hard about the basic performance of queues, and this has lead to some realisations about provisioning Rabbits.

From time to time, on our mailing list and elsewhere, the idea comes up of using a different backing store within RabbitMQ. The backing store is the bit that’s responsible for writing messages to disk (a message can be written to disk for a number of reasons) and it’s a fairly frequent suggestion to see what RabbitMQ would look like if its own backing store was replaced with another storage system.

Such a change would permit functionality that is not currently possible, for example out-of-band queue browsing, or distributed storage, but there is a fundamental difference in the nature of data storage and access patterns between a message broker such as RabbitMQ and a generic database. Indeed RabbitMQ deliberately does not store messages in such a database.

In the past year development of the AMQP gem was practicaly stagnating, as its original author Aman Gupta (@tmm1) was busy. A lot of bugs stayed unresolved, the code was getting old and out-dated and no new features or documentation were made.

At this point I started to talk with the RabbitMQ guys about possible collaboration on this. Actually originally I contacted VMware when I saw Ezra Zygmuntowicz looking for people to his cloud team, but when I found that VMware recently acquired the RabbitMQ project in London, I got interested. I signed the contract, switched from script/console to Wireshark and the RabbitMQ Tracer and since November I’ve been happily hacking on the AMQP and AMQ-Protocol gems.

RabbitMQ needs more and better documentation. (And who doesn’t?) In particular, we need more and better introductory material that introduces the reader to various basic concepts, explains why they’re important, and motivates him or her to keep reading and learn more about RabbitMQ. Here’s a cut at Chapter 1 of that introduction. Your comments are welcome, and Chapters 2 and 3 will follow soon. (You probably already know all of this, but a surprising number of people don’t. This introduction is for them.)