# Avoid eventual consistency in time series event **URL:** \ **Category:** Elasticsearch\ **Created:** [May 14, 2018, 3:22pm UTC](https://discuss.elastic.co/t/avoid-eventual-consistency-in-time-series-event/131775 "2018-05-14T15:22:55Z")\ **Posts on this page:** 2\ **Page:** 1
**Author:** ![LucaMazzanti](https://avatars.discourse-cdn.com/v4/letter/l/77aa72/32.png) [@LucaMazzanti](https://discuss.elastic.co/u/LucaMazzanti)\ **Post date:** [May 14, 2018, 3:22pm UTC](https://discuss.elastic.co/t/avoid-eventual-consistency-in-time-series-event/131775/1 "2018-05-14T15:22:55Z")
Hi, i'm logging time series events, and some clients read from this index sequentially, they take the top X items filtered by a fixed teanant query, and the next time they poll, the continue filtering by an orderer id \> previous one. Logstash act as bridge from rabbit, batching inserts. The data is replicated for HA on 2 replicas. I want to avoid eventual consistency for the latest inserted items, to avoid to skip them and skip forward next time. Which is a good practice? Can I filter always data inserted in the latest few finutes (1-2) to avoid missing data on replicas? I can monitor my nodes to undertand the speed rate of inserts, and mantain the 1s near real time buffer. Otherwise can I route clients to read fixed replicas to let them read always data in the way is sync, then next time they will continue read without loose data? Thanks, Luca. ---
**Author:** ![system](https://us1.discourse-cdn.com/elastic/original/3X/1/a/1ac57faf039f6b580b3f104ef42a2a89e41014de.png) [@system](https://discuss.elastic.co/u/system)\ **Post date:** [June 11, 2018, 3:23pm UTC](https://discuss.elastic.co/t/avoid-eventual-consistency-in-time-series-event/131775/2 "2018-06-11T15:23:10Z")
Closed on June 11, 2018, 3:23pm UTC This topic was automatically closed 28 days after the last reply. New replies are no longer allowed.