# Scaling experiments memory

**URL:** <https://discuss.elastic.co/t/scaling-experiments-memory/68630>\
**Category:** Elasticsearch\
**Created:** [December 10, 2016, 7:06pm UTC](https://discuss.elastic.co/t/scaling-experiments-memory/68630 "2016-12-10T19:06:02Z")\
**Posts on this page:** 2\
**Page:** 1

<div class="post-metadata">

**Author:** ![vss](https://avatars.discourse-cdn.com/v4/letter/v/3ec8ea/32.png) [@vss](https://discuss.elastic.co/u/vss)\
**Post date:** [December 10, 2016, 7:06pm UTC](https://discuss.elastic.co/t/scaling-experiments-memory/68630/1 "2016-12-10T19:06:03Z")

</div>

Hi, I am trying to run a few experiments to understand scale better for my workload. One of the questions I had was how much memory is too small to understand scaling.

Let's say I have 3 nodes (running ES 2.3) each with 1GB RAM on 10GB SSD's and with about 2.5 million docs and 1 replica, I've noticed that the JVMMemoryPressure stays at around 70% which seems rather high. The problem is with this load the queries are taking much longer to complete i.e. much more latency.

**Question:** Does anyone have any pointers on how I should approach determining what is causing this latency?

I am guessing it's the memory pressure, but I am not sure how to understand the node stats metrics to see why there is so much JVMMemoryPressure.

---

<div class="post-metadata">

**Author:** ![system](https://us1.discourse-cdn.com/elastic/original/3X/1/a/1ac57faf039f6b580b3f104ef42a2a89e41014de.png) [@system](https://discuss.elastic.co/u/system)\
**Post date:** [January 7, 2017, 7:06pm UTC](https://discuss.elastic.co/t/scaling-experiments-memory/68630/2 "2017-01-07T19:06:59Z")

</div>

Closed on January 7, 2017, 7:06pm UTC

This topic was automatically closed 28 days after the last reply. New replies are no longer allowed.