# Scaling time series indices **URL:** \ **Category:** Elasticsearch\ **Created:** [July 10, 2016, 5:02pm UTC](https://discuss.elastic.co/t/scaling-time-series-indices/55135 "2016-07-10T17:02:27Z")\ **Posts on this page:** 3\ **Page:** 1
**Author:** ![shushu](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/shushu/32/10037_2.png) [@shushu](https://discuss.elastic.co/u/shushu)\ **Post date:** [July 10, 2016, 5:02pm UTC](https://discuss.elastic.co/t/scaling-time-series-indices/55135/1 "2016-07-10T17:02:27Z")
Hi, I am running a time series elasticsearch cluster (on top of AWS service). Using template, I create a daily index. 5 shards, 2 replicas, on 10 nodes + 4 masters. Once the number of clients went high up - all stopped working - CPU maximum went to 100%, while CPU average kept low (~40%). My guess is that the main searches are done against the latest days, so it focus on the nodes that has latest data - while the rest stays idle. My question is - what would be the right scale mechanism ? I think that I should by default, in the template, give the maximum number of replicas (10), so latest data will have as many replicas as possible. Once data become old - in couple of days - reduce the number of replicas to 2. Is this sounds like a decent methodology ? Any other recommendations ? ---
**Author:** ![nik9000](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/nik9000/32/44947_2.png) [@nik9000](https://discuss.elastic.co/u/nik9000)\ **Post date:** [July 10, 2016, 8:04pm UTC](https://discuss.elastic.co/t/scaling-time-series-indices/55135/2 "2016-07-10T20:04:05Z")
It is likely a lot more efficient to use bigger hardware (ssds, ram, CPU) for the new indices and use forced allocation awareness to control indices location. I don't know how you'd do that with any cloud service. Replicas scale reads well but not writes because replicas just perform the same write as the primary. shushu [http://discuss.elastic.co/users/shushu](http://discuss.elastic.co/users/shushu) Shushu Inbar [http://discuss.elastic.co/users/shushu](http://discuss.elastic.co/users/shushu) July 10 Hi, I am running a time series elasticsearch cluster (on top of AWS service). Using template, I create a daily index. 5 shards, 2 replicas, on 10 nodes + 4 masters. Once the number of clients went high up - all stopped working - CPU maximum went to 100%, while CPU average kept low (~40%). My guess is that the main searches are done against the latest days, so it focus on the nodes that has latest data - while the rest stays idle. My question is - what would be the right scale mechanism ? I think that I should by default, in the template, give the maximum number of replicas (10), so latest data will have as many replicas as possible. Once data become old - in couple of days - reduce the number of replicas to 2. Is this sounds like a decent methodology ? Any other recommendations ? Visit Topic [http://discuss.elastic.co/t/scaling-time-series-indices/55135/1](http://discuss.elastic.co/t/scaling-time-series-indices/55135/1) or reply to this email to respond. You are receiving these emails cause you have enabled mailing list mode. To unsubscribe from these emails, click here [http://discuss.elastic.co/email/unsubscribe/218e18220e3ce0d999d16a32978f5dcc3428ad3a81bc02edb9c8a875720d4730](http://discuss.elastic.co/email/unsubscribe/218e18220e3ce0d999d16a32978f5dcc3428ad3a81bc02edb9c8a875720d4730) . ---
**Author:** ![system](https://us1.discourse-cdn.com/elastic/original/3X/1/a/1ac57faf039f6b580b3f104ef42a2a89e41014de.png) [@system](https://discuss.elastic.co/u/system)\ **Post date:** [July 5, 2017, 10:36pm UTC](https://discuss.elastic.co/t/scaling-time-series-indices/55135/3 "2017-07-05T22:36:46Z")