We went through various configurations/deployments of ES in-house, and eventually outsourced the job. The fickle nature of cluster restarts/upgrades were frustrating along with the unassigned & lost indexes that would often result. Then there were cluster partitions that wouldn't heal without a lot of manual intervention.

The tradeoff in value wasn't worth the time it was requiring, so we outsourced to compose.io -- they've been a good fit price & stability-wise, and feel pretty close to a blackbox for the benefit. If you need a large cluster however, you'll pay handsomely with any of the SaaS providers when last I looked at it. For large quantity work we've moved to AWS Redshift.

It's actually fairly difficult. There are so many different possible combinations of incoming data quality, quantity, system and disk configuration, performance and internal ES settings. Only an administrator would be familiar enough with the environment to monitor and tweak the configuration to make it the most performant.

There are a few hosted elasticsearch services available (Elastic Cloud, AWS ES, Qbox, etc) which would likely be a better option for the team that needed a hands-off elasticsearch cluster.

Our indexes are probably very small (about 40gb total) but I've found if you value speed and consistency over all else.... just run a single, 1 shard node and have a fallback in case of random errors. I just do major version upgrades and rebuild the indexes, no real maintenance.

I should add that all "hot" data fits in 24g of memory.

If what you need is just search, you could try a SaaS, such as Algolia (https://www.algolia.com/)

Who'd pay them for support if everything ran smoothly?

We've run it without supervision for about a year now at multiple sites, and have not had any major issues.