Message brokers are specialised pieces of enterprise middleware designed to support integrating applications in a decoupled (in both time and location) manner, using messaging channels, implemented as either queues (for single consumer) or topics (for multiple consumers). Whilst deploying and operating a broker has an additional, ongoing cost for a business, if the scale of integration in your system and the non-functional requirements warrant it, they can can provide a flexible, better performing and more scalable solution than the alternative of implementing message queues in your database, especially, as is often the case, the latter is already overloaded.There are a considerable number of proven message brokers available today from a variety of vendors. Before committing to building your integrations on a particular broker, you should give careful consideration to how well it satisfies your requirements. I recently went through such an evaluation exercise, and ended-up choosing Amazon Simple Queue Service (SQS). While we haven’t regretted this decision, I did learn a few things along the way. In this post I’ll share a list of the functional and non-functional (technical) requirements that you should consider as part of evaluating a message broker, and also my opinion on how SQS measures up to other brokers in each case, and the trade-offs.

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When building a message consumer you need to handle the various errors that will inevitably occur during message processing. If you’re using Amazon SQS as your message broker it provides some built-in support for error handling that you can utilise. But, if you want to handle all types of errors efficiently you should also add your own custom error handler. This post explains how you can do both these things, including how to classify message processing errors.

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