I’ve been to several customers over the years who have a requirement to consume messages from a JMS queue in an ordered fashion. The discussions always go the same way… It starts out as a simple design, but becomes really problematic when they get to the implementation phase. Turns out, it’s really not all that simple once you try to scale. In this blog post, we’ll explore in a bit more detail and give some possible solutions.
I recently had a customer that wanted us to do some load testing of Red Hat’s JBoss A-MQ for them. In particular, this customer wanted the tests performed using the AMQP protocol instead of ActiveMQ’s native OpenWire. From previous engagements, I knew that there would be a performance difference. But after a quick look I didn’t see any blogs or posts on the subject. More specifically, I didn’t see any posts that detailed how to run the tests yourself so that you could get real numbers in your own environment. So I figured I’d write up some steps and post my results for future reference.
Apache Camel is a pretty full-featured EIP implementation framework. It has several existing strategies for load-balancing right out of the box. Round Robin, Random, Sticky, Weighted Round Robin, Weighted Random,… the list goes on and on. But being that it’s a very well written and pluggable framework, it also gives you the ability to drop in your own custom strategies should you find that none of the existing ones meet your specific needs. So for this post, I created a custom Camel Load Balancer implementation utilizing an Infinispan cache to dynamically discover and load-balance between destination endpoints.
In many environments, it is common to ingest data as a batch process. This is usually accomplished by polling a directory (or FTP server) for files. The issue is that polling for files is a one-way communication. So if you get a file that you can’t parse (or one that is invalid for any other reason), you have no way of communicating that back to the original sender. How do you handle the error? You likely can’t just drop the data on the floor. That really only leaves one option and that is to correct the data and re-ingest it.
This is a follow-on to the excellent blog post that my colleague Christian Posta wrote on doing CI/CD with Fuse Fabric. In particular, this post will extend upon his write-up by showing how to migrate Fabric8 profiles and Maven artifacts into environments which are disconnected from the development environment.
