Elasticsearch, Logstash & Kibana

Hi Friends, In this blog we are going to learn about Elasticsearch, Logstash and Kibana.

Elasticsearch:

Elasticsearch is a NoSQL database. It is based on Lucene search engine, and it is built with RESTful APIs.

It offers simple deployment, maximum reliability, and easy management. It also offers advanced queries to perform detail analysis and stores all the data centrally. It is helpful for executing a quick search of the documents.

Elasticsearch also allows you to store, search and analyze big volume of data.It has been adopted in search engine platforms for modern web and mobile applications. Apart from a quick search, the tool also offers complex analytics and many advanced features.

Features of Elastic search:

• Used to index any kind of heterogeneous data
• Has REST API web-interface with JSON output
• Full-Text Search
• Manipulate your data record by record with the help of Multi-document APIs
• Perform filtering and querying your data for insights
• Sharded, replicated searchable, JSON document store
• Schema-free, REST & JSON based distributed document store

Logstash:

Logstash is the data collection pipeline tool.It collects data inputs and feeds into the Elasticsearch.

It gathers all types of data from the different source and makes it available for further use.

It consists of three components:

• Input: passing logs to process them into machine understandable format
• Filters: It is a set of conditions to perform a particular action or event
• Output: Decision maker for processed event or log

Features of Logstash:

• Events are passed through each phase using internal queues
• Allows different inputs for your logs
• Filtering/parsing for your logs
• Offers centralize the data processing
• It analyzes a large variety of structured/unstructured data and events
• ELK Logstash offers plugins to connect with various types of input sources and platforms

Kibana:

Kibana is a data visualization which completes the ELK stack. This tool is used for visualizing the Elasticsearch documents and helps developers to have a quick insight into it.

Kibana dashboard offers various interactive diagrams, geospatial data, and graphs to visualize complex quires.

In Kibana there are different methods for performing searches on your data.Here are the most common search types:

• Free text searches: It is used for searching a specific string
• Field-level searches: It is used for searching for a string within a specific field
• Logical statements: It is used to combine searches into a logical statement.
• Proximity searches: It is used for searching terms within specific character proximity.

Features of Kibana:

• Powerful front-end dashboard which is capable of visualizing indexed information from the elastic cluster
• Enables real-time search of indexed information
• You can search, View, and interact with data stored in Elasticsearch
• Execute queries on data & visualize results in charts, tables, and maps
• Capable of providing historical data in the form of graphs, charts, etc.
• Real-time dashboards which is easily configurable
• Kibana Elasticsearch enables real-time search of indexed information
• Allows sharing of snapshots of the logs searched through
• Permits saving the dashboard and managing multiple dashboards

Conclusion

In this Blog, we have learned basic things about Elasticsearch, Logstash and Kibana. Hope to see you all in my next blog post, Until then Take Care! Keep Learning!

Thank You For Reading this Blog………

Have a Nice Day……

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