# How to estimate the maximum users for Kibana?

**URL:** <https://discuss.elastic.co/t/how-to-estimate-the-maximum-users-for-kibana/68679>\
**Category:** Kibana\
**Created:** [December 12, 2016, 8:44am UTC](https://discuss.elastic.co/t/how-to-estimate-the-maximum-users-for-kibana/68679 "2016-12-12T08:44:42Z")\
**Posts on this page:** 3\
**Page:** 1

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**Author:** ![Carlos\_Vega\_Moreno](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/carlos_vega_moreno/32/3773_2.png) [@Carlos\_Vega\_Moreno](https://discuss.elastic.co/u/Carlos_Vega_Moreno)\
**Post date:** [December 12, 2016, 8:44am UTC](https://discuss.elastic.co/t/how-to-estimate-the-maximum-users-for-kibana/68679/1 "2016-12-12T08:44:42Z")

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I would like to know how can estimate the maximum number of users that can visit Kibana without making Elasticsearch crash.  
Is there any way to limit the max amount of connections or queries?  
Is there any way to prioritise index operatios over search operations?

How can I increase the number of queries to resolve at the same time? At the moment I have a single instance of Elasticsearch, would a second help? or could even decrease the performance because of the syncronization burden?

Thanks in advance 🙂

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**Author:** ![warkolm](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/warkolm/32/39224_2.png) [@warkolm](https://discuss.elastic.co/u/warkolm)\
**Post date:** [December 13, 2016, 3:44am UTC](https://discuss.elastic.co/t/how-to-estimate-the-maximum-users-for-kibana/68679/2 "2016-12-13T03:44:20Z")

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The best way is to just test.  
Build a dashboard that you expect users will use, then take the query that it runs and test it with [https://github.com/elastic/rally](https://github.com/elastic/rally)

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**Author:** ![system](https://us1.discourse-cdn.com/elastic/original/3X/1/a/1ac57faf039f6b580b3f104ef42a2a89e41014de.png) [@system](https://discuss.elastic.co/u/system)\
**Post date:** [January 10, 2017, 3:44am UTC](https://discuss.elastic.co/t/how-to-estimate-the-maximum-users-for-kibana/68679/3 "2017-01-10T03:44:37Z")

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