Introduction to Elasticsearch

Elasticsearch helps a developer or administrator search and analyze document sets of up to several billion documents, with responses measured in the tens of milliseconds or less.  Elasticsearch provides a REST-based, JSON-oriented API for managing the data and managing the servers themselves.  The servers scale out horizontally.  A new server can be installed in 10 minutes, and additional nodes are just as easy to add

This talk provides a technical introduction to Elasticsearch and two related open source projects, Logstash and Kibana.  We present common developer use cases for Elasticsearch, from Twitter feed tracking to product catalog storage and search, as well as devops use cass like log storage and analytics at scale.  The talk also gives examples of the features available in Elasticsearch to enable these use cases.

Elasticsearch can support simple deployments or complex, multi-site ones.  This talk presents decision points in the design of your Elasticsearch cluster and guidance on making those key decisions to build a successful data platform.  What deployment architecture will you need?  What performance is possible, and what will it cost you to get those levels of performance?

The Elasticsearch community and feature set are both growing rapidly. There are many ways to join and contribute, and a brief introduction to the software architecture is provided to help developers understand where they could integrate their favorite projects or contribute to Elasticsearch. Some thoughts for potential future directions for open source search and analytics are presented as well.