You should consider the RAM to CPU/Disk ratio. On systems with huge memory, CPUs have the tendency to become weak, and the I/O subsystem must push data with higher pressure from RAM to drive (spindle or SSD). Huge RAM helps for caching strategies but also creates headaches, large caches must be long lived and must not collapse, which is hard in a large JVM heap, and JVM garbage collection will take more resources and time.
Running multiple JVMs on a single host only looks like a viable solution, but that is not how ES scales. ES scales horizontally over many machines, not vertically over RAM size. So you should take care that your CPU performance is not suffering. There is overhead also on the OS layer and it depends on the setup. A 36 node cluster on 6 machines adds another challenge. You must tell ES how your nodes are organized, in order to get a reliable green/yellow/red cluster health for your shard allocation. Jörg -- You received this message because you are subscribed to the Google Groups "elasticsearch" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To view this discussion on the web visit https://groups.google.com/d/msgid/elasticsearch/CAKdsXoF7PA2nMNOo53dxqcT%3DYOFYfmB5A_YvJGk%3DGCa2Tu3t0A%40mail.gmail.com. For more options, visit https://groups.google.com/groups/opt_out.
