> For the complete documentation index, see [llms.txt](https://bigdata-2.gitbook.io/bd201notes/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://bigdata-2.gitbook.io/bd201notes/elk.md).

# ELK

![ELK stack](https://3047264112-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-LoWAdFshQklZGvmhPe2%2F-M5TtGoxgTgHRvqcjFNu%2F-M5TtHX1rBaqsHNqH9VI%2FIMG_0.png?generation=1587508751162715\&alt=media)

## Introduction

"ELK" is the acronym for three open source projects:

* Elasticsearch
* Logstash
* Kibana.

Elasticsearch is a search and analytics engine.

Logstash is a server‑side data processing pipeline that ingests data from multiple sources simultaneously, transforms it, and then sends it to a "stash" like Elasticsearch.

Kibana lets users visualize data with charts and graphs in Elasticsearch.

Elasticsearch is used for a lot of different use cases:

* "classical" full text search
* analytics store
* auto completer
* spell checker
* alerting engine
* and document store as a general purpose. 

One of the most popular user case for ELK cluster – is analytics, logs and events gathering with future ability to search, visualize and analyse these time series data.