What I found most important is to monitor Elasticsearch while doing that tuning. That's when I set up Graphite and StatsD and https://github.com/ralphm/vor.

First of, you need to make sure Elasticsearch can lock a chunk of memory (using mlock). About half of the available RAM is a good size, as other system processes need some memory, too, and not everything is on the heap.

You want to look for how many items you are indexing and how much of the heap the field data cache is using while doing queries. By default ES tries to keep the total heap size at about 3/4 of the allocated memory. The types of queries are important, too. E.g. if you do faceting or sorting on fields that have many different values, this will fill up the field data cache in no time.

Is that the kind of information you're after? I can go into in more detail if you have more specific question.