Elasticsearch is a real-time search and analytics engine that promises horizontal scalability and high performance almost out of the box. Still, even though it's incredibly easy to get started with Elasticsearch, there is ample room for decisions that look good at first but might bite you later in production. Luckily, with Elasticsearch we are usually able to solve all the challenges that arise, but it's just so much nicer if we already know what to look out for right from the start than having to fix it in hindsight.
This talk builds on the combined experience that codecentric has gathered from developing and operating the Elasticsearch-based cloud service CenterDevice as well as various customer projects done over the last two years. It formulates important lessons learned regarding Elasticseahttp://berlinbuzzwords.de/session/analytics-age-internet-thingsrch scalability and performance as easy-to-remember Do's and Don'ts, backed up with anecdotes from actual events. The topics covered range from mapping and query definition over data modeling to cluster configuration and zero downtime re-indexing. Nothing is held back - we share all the things we wished we had known two years ago.