Linux by Ripudaman Singh

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Customize the Bash [Linux] Your terminal window generally has username@hostname but you can change that we will discuss here how to change it.   link for details: Read-1 Read-2 Read-3 Let's make the Example setup as in above picture with live time cp ~/.bashrc ~/.bashrc.bak  In case of a problem it will help to get back the old file  nano ~/.bashrc Add the follwing line at the Last PS1="\e[0;35m\w\e[m\n\@ \e[0;35m$\e[m " close the nano by ctrl X, Y enter. making Changes active by source ~/.bashrc To customize in your own way see the above links. Get the localhost at some other name [Linux] Open your terminal and type  sudo nano /etc/hosts map your name with localhost address like 127.0.0.1       localhost 127.0.1.1       ripudaman # The following lines are desirable for IPv6 capable hosts ::1 ctrl X, y enter All done you can access the localhost at your describe name for me its ripudaman (helpful when making twitt...
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ElasticSearch

ElasticSearch:

ElasticSearch is an analysis, store, search product. It can be locally installed on the server or it can be cloud-hosted. ElasticSearch is like a NoSQL database, data is stored as a document that is indexed.
ElasticSearch let us perform various operations on the document very easily and in near real-time. ElasticSearch has REST API which allows you to integrate, manage and query the indexed data. Some of the API Call:
Document API: Used to create a document in an index, update them, move them to another index or remove them.
Index API: This API allows users to manage indices, mapping, and templates.
Cluster API: These are cluster-specific API calls that allow you to manage and monitor your Elasticsearch cluster. 
Search API: These API calls can be used to query indexed data for specific information

What is the ELK stack?

ELK stack is ElasticSearch, Logstash, and Kibana.
Logstash is used to ingest the data in ElasticSearch so that it can be stored analyze and searchable.
Kibana is a WebClient for ES for the monitoring and managing of the data. It is most widely used for the visualization of the ES data. Very useful in logging data.

WHY ElasticSearch?

Scalability: We can scale our ElasticSearch cluster by adding more nodes.
Really Fast: Uses the Best Algorithms and techniques to provide the result.
Data Security: We can replicate our data on a different node (another computer in a cluster) so if one node is a failure the data loss can be recovered.

Use of ElasticSearch?

ElasticSearch is very useful in logging data of the server. Problems in server failure are easy to catch when using ElasticSearch as it provides Best text-based searches.

ElasticSearch is also used in the search of our local database (like MONGO, SQL, etc). BlackBox is when the search request is made, it is transferred to the /_search endpoint of the ElasticSearch (which have a duplicate data of the local database) and the result of which is sent to the local Database from which only GET request action is made to perform. The action from the ElasticSearch is fast as it uses caching and Algorithms to perform its action. 

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