Elastic Search

Using Elastic search Kibana and Logstash for Log analysis

Ankit Verma
Latest posts by Ankit Verma (see all)

Elastic Search :

Elastic search provides a distributed, multitenant-capable full-text search engine with an HTTP web interface and schema-free JSON documents.

Kibana :

Kibana lets you visualize your Elastic search data and navigate the Elastic Stack, so you can do anything from learning why you’re getting paged at 2:00 a.m. to understanding the impact rain might have on your quarterly numbers.

Logstash:

Logstash is an open source, server-side data processing pipeline that ingests data from a multitude of sources simultaneously, transforms it, and then sends it to your favorite “stash.” (Ours is Elasticsearch, naturally.)

Filebeats:

Filebeat comes with internal modules (auditd, Apache, NGINX, System, MySQL, and more) that simplify the collection, parsing, and visualization of common log formats down to a single command. They achieve this by combining automatic default paths based on your operating system, with Elasticsearch Ingest Node pipeline definitions, and with Kibana dashboards. Plus, a few Filebeat modules ship with preconfigured machine learning jobs.

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For further ref please do look

https://www.elastic.co/products/

Steps to follow :

Create Filebeats.yml

https://bitbucket.org/ankverma191/elasticsearch-sample/src/master/filebeats/filebeat.yml

Create logstash.yml

https://bitbucket.org/ankverma191/elasticsearch-sample/src/master/logstash/

Sample run :

Elastic Search

So we can see that once we write a log that log carries itself to elasticsearch via filebeats and logstash.

Enjoy reading logs developers .!!!