Elastic can be used to search all kinds of documents. It provides scalable search, has near real time search and supports multi tenancy. Elastic is distributed, which means that indices can be divided into shards and each shard can have zero or more replicas. Each node hosts one or more shards, and acts as a coordinator to delegate operations to the correct shard(s). Rebalancing and routing are done automatically. Related data is often stored in the same index, which consists of one or more primary shards, and zero or more replica shards.

Elastic is developed alongside a data collection and log parsing engine called Logstash, an analytics and visualization platform called Kibana. The three products are designed for use as an integrated solution, referred to as the Elastic Stack (formerly the ELK stack)

• All round operational support
• Design & architecting skills for your current & future needs
• Providing automation to address rapidly scaling landscape
• Integration & deployment expertise to simplify the complexities
• Unbiased, independent insights for better & smarter decision making

Based on the Apache Lucene search engine, Elasticsearch is a free and open, full text search and analysis engine. The NoSQL database is used to power applications that achieve search requirements, by enabling indexing and storing the data. Adopted in search engine platforms for modern web & mobile applications, the tool also offers complex analytics and many more advanced features

• Providing RESTful API, it is based on Apache Lucene
• Using Multi-document APIs, it manipulates every your data record by record
• Filtering & Querying of data is order to derive insights
• To make search faster, real time use of indexing is done by horizontal scalability, reliability, and multi-tenant capabilities
• Creates a schema for data while storing schema-less data

Executing different transformations and enhancements, Logstash is a log aggregator collecting data from different input sources and shipping the data to various supported output destinations. It supports cleansing your data for analytics & visualization of use cases, while unifying data from different sources into your desired destinations.

• Analysis of a large variety of structured or unstructured data, events, etc.
• Plugins offered to connect with different types of input sources and platforms
• Enabling centralized data processing

Kibana helps developers get a quick insight into the Elasticsearch documents. It is a visualization layer that works on top of Elasticsearch in order to provide users an interface to visualize and for data querying.

• Instinctive & user friendly interface
• Real time analysis, debugging capabilities, charting and summarization
• Real time search of indexed information
• Integrated totally with Elasticsearch
• Dashboard visualizes indexed information from the cluster

Lightweight agents installed on edge hosts in order to collect the different types of data for forwarding into the stack, they along-with Logstash, take care of data collection & processing. They are commonly used for securing IT environments as well as monitoring and troubleshooting them.