As you might already know, DBT2 is an OLTP benchmark similar (but not equivalent) to venerable TPC-C. A couple of months ago I tried it with Galera on Amazon EC2 to see how Galera performed in a non-LAN environment. It did quite well, especially in high availability regard. Since then Galera saw a whole lot of bugfixes and improvements, so the time has come to try it once again. This time it will be 'large' AWS instances, almost 8 gigs of RAM and two CPU cores, you know, Big Iron or something.

How would Galera perform in this setup?

Today I have fixed an "optimization" which caused up to 10x performance degradation. In case you are interested, it was my optimization. And no, it was not iterating over 1000000-something long list. And it was not some hastily assembled patch. It was deliberately engineered optimization. I didn't even care to check how well it optimizes - so obviously neat it was.

This is the first in the series of articles about Galera on Amazon EC2, here's the follow up.
Galera benchmarks on Amazon EC2 have been long overdue. There are at least 3 reasons why EC2 performance is so important to Galera project:

If you're about to use the database cluster to scale performance of your application, you need some way to balance the load between the nodes. Ideally application should be smart enough to be able to distribute it's connections between different hosts and fail over. But in practice this is rarely the case.

Bugs always come when you least expect them. Another delay caused by bug hunting. And just as we were ready to release some benchmark results, we realized that this suspicious overhead in case of 100% SELECT load looks like a bug too. Will be looking into it further. We don't want to spoil your viewing pleasure.

It is not unusual for a database application to have a "hot spot" - a table or a row most often accessed. DBT2 benchmark (and therefore TPC-C, I guess) is one such example. It has a 'warehouse' table which is naturally quite short - one row per warehouse. Even for a single MySQL server it becomes a performance bottleneck.