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Elasticsearch index

An Elasticsearch index is a named, searchable collection of documents organized for querying and distributed across storage shards and replicas.

How 2 Manning books explain it

Elasticsearch in Action, Second Edition

An Elasticsearch index is a logical collection of searchable documents distributed across shards and replicas.

How it is used
Groups related JSON documents for indexing, retrieval, search, and operational management.
How deep it goes
Defines logical and shard-backed structure, then details creation, mappings, replicas, reindexing, and lifecycle-oriented management.
Examples
Uses books, cars, news, trades, and a 50-book bookstore dataset indexed through REST, Kibana, and the bulk API.
What you can do after
Operate/configure it by creating indexes, choosing mappings and replica settings, and reindexing schema changes into a replacement index.

Read how Elasticsearch in Action, Second Edition explains Elasticsearch index →

Learn Docker in a Month of Lunches, Second Edition

An Elasticsearch index is a named collection of documents that can be searched and queried as a unit.

How it is used
Supports centralized container-log storage, search, filtering, and time-based exploration through Kibana.
How deep it goes
Defines indexes as document collections and demonstrates naming, data views, and searches, but does not detail Elasticsearch internals.
Examples
Uses Fluentd-created fluentd-{date} indexes containing timecheck and other container log documents.
What you can do after
Operate/configure an EFK exercise, create a Kibana data view, and search collected container-log documents.

Read how Learn Docker in a Month of Lunches, Second Edition explains Elasticsearch index →

Related concepts

These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.