If you have a throughput problem you are most likely doing it wrong. If your knee jerk reaction is to scale your messaging up you may want to reconsider. Messaging systems are usually hard to scale up and always very costly to do so compared to the amount of data they are transferring.

The simplest thing you can do is to realise WHY you are using messages. Messages are there to trigger a process. Usually, you don't need a lot of data to trigger a process, the message just needs to let the system know enough to locate all necessary information.

Also, when you are sending information at an extremely high rate, there usually is no difference if each message is processed separately or in batches.

So what you can do in practice?

1) Get the producer to batch the messages. For example set rules like "batch up to 10.000 messages, up to 100ms, up to 100MB of data, whichever comes first". 2) Serialise the batch (for example, if it makes sense, create a compressed JSON file) 3) Upload the file to some high throughput, scalable, cheap storage (for example S3) 4) Send a message to the queue / topic / whatever else you are using with just enough to locate and process the message -- usually just the link to the S3 object.

This usually can be modified depending on specific project needs.

Now your messaging only ever sees a small number of very small messages and you will never have any scaling problems, at least not on messaging side.