Implementing the reliability pattern in CloudHub with VM queues

Question

I have more-or-less implemented the Reliability Pattern in my Mule application using persistent VM queues CloudHub, as documented here. While everything works fine, it has left me with a number of questions about actually ensuring reliable delivery of my messages. To illustrate the points below, assume I have http-request component within my "application logic flow" (see the diagram on the link above) that is throwing an exception because the endpoint is down, and I want to ensure that the in flight message will eventually get delivered to the endpoint:

1. As detailed on the link above, I have observed that when the exception is thrown within my "application logic flow", and I have made the flow transactional, the message is put back on the VM queue. However all that happens is the message then repeatedly taken off the queue, processed by the flow, and the exception is thrown again - ad infinitum. There appears to be no way of configuring any sort of retry delay or maximum number of retries on VM queues as is possible, for example, with ActiveMQ. The best work around I have come up with is to surround the http-request message processor with the until-successful scope, but I'd rather have these sorts of things apply to my whole flow (without having to wrap the whole flow in until-successful). Is this sort of thing possible using only VM queues and CloudHub?
2. I have configured my until-successful to place the message on another VM queue which I want to use as a dead-letter-queue. Again, this works fine, and I can login to CloudHub and see the messages populated on my DLQ - but then it appears to offer no way of moving messages from this queue back into the flow when the endpoint comes back up. All it seems you can do in CloudHub is clear your queue. Again, is this possible using VM queues and CloudHub only (i.e. no other queueing tool)?

Answer 1

VM queues are very basic, whether you use them in CloudHub or not.

1. VM queues have no capacity for delaying redelivery (like exponential back-offs). Use JMS queues if you need such features.
2. You need to create a flow for processing the DLQ, for example one that regularly consumes the queue via the requester module and re-injects the messages into the main queue. Again, with JMS, you would have better control.

Alternatively to JMS, you could consider hosted queues like CloudAMQP, Iron.io or AWS SQS. You would lose transaction support on the inbound endpoint but would gain better control on the (re)delivery behaviour.