I have seen it mentioned several times as a best practice that there should be one distributor process configured per message type, but never any explanation as to why this is so. Since increasing the number of distributors increases the deployment complexity, I'd like to know the reasoning behind it. My guess is that if all available subscribers for a given message type are busy, the distributor may be stuck waiting for one to free up, while messages of other types which may have free subcribers are piling up in the distributor's work queue. Is this accurate? Any other reasons?
What is the reason behind NServiceBus one-distributor-per-message-type best practice?
1.3k views Asked by jlew At
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Having one logical endpoint per message type (logical endpoint is equal to either one endpoint or many copies of an endpoint behind a distributor) allows you the flexibility to monitor and scale each use case independently.
Also, it enables you to version the endpoint for one message type independently from all the others.
There is higher deployment complexity in that you have more processes installed, and ultimately you have to strike a balance (as always) between flexibility and complexity, but keep in mind that many of these deployment headaches can be automated away.
It is true that the Distributor will not hand out more work until a Worker is done. Therefore if Workers are tied up with a given message type, the others will sit there until they are done. NSB doesn't have a concept of priority, all messages are created equal. Workers do not subscribe to specific message types, they just get handed work from the Distributor.
If certain message types have "priority" over others, then they should have their own Distributor. If the "priority" is all the same then adding more workers will increase performance to a certain point. This will depend upon what you are resoruce you are operating upon. If it is a database, your endpoint may be more data bound than cpu bound. In that case adding more Workers won't help as they are creating increasing contention on potentially the same resource. In this case you may need to look into partitioning the resource some how.