It was brittle beyond belief. The process would run out of memory and crash really easily. You are supposed to dimension resources well, but of course you'd like to handle things more gracefully when a huge inflow of data or requests comes in, good engineering is "graceful failure" such as just rejecting requests, instead of total mayhem and destruction. It was "interesting" to discover that the monitoring plugins included by default would bring down the entire cluster. 5 beefy AWS machines brought down when pointing their own monitor at them! Yes there was significant input traffic, but I would expect more solid behavior from production-ready software.

Shard migration and duplication was a beauty to watch when it worked well, but very often it wouldn't. I tried to establish a procedure to bring instances back up safely and repeatably, but sometimes I would just have to try and try again, no procedure guaranteed restoring operation in all cases. I do remember spending more than one weekend babysitting that cluster. There's a special place in my heart for that memory, and it's not a beautiful one.

I was very surprised to see them IPO successfully - this test was before they were public. I assumed the open source version was just missing the kind of tools and know how to be able to work solidly without paying them or their consultants. These days, I think it's poor engineering resulting in brittleness, we shouldn't have put so much traffic to it, and probably everyone out there experiences the same behavior unless they ensure much safer margins, which probably makes it expensive but I guess who's complaining.

I ended up designing and writing my own (much simpler) distributed system for what I needed (much simpler than everything ElasticSearch does, of course), and it's been in reliable operation since summer 2015. Good engineering goes a long way. Now in the process of turning that approach into a startup. If I get 1/10th as successful as ES I will be a happy camper :)