In this chapter, we focused more on the Elasticsearch configuration and new features that were introduced in Elasticsearch 1.0. We configured discovery and recovery, and we used the human-friendly Cat API. In addition to that, we used the backup and restore functionality, which allowed easy backup and recovery of our indices. Finally, we looked at what federated search is and how to search and index data to multiple clusters, while still using all the functionalities of Elasticsearch and being connected to a single node.

In the next chapter, we will focus on the performance side of Elasticsearch. We will start by optimizing our queries with filters. We will discuss the garbage collector work, and we will benchmark our queries with the new benchmarking capabilities of Elasticsearch. We will use warming queries to speed up the query execution time, and we will use the Hot Threads API to see what is happening inside Elasticsearch. Finally, we will discuss Elasticsearch scaling and prepare...