Elastic Stack

Elastic Stack

Document database, connector, visualization capabilities

 

Making sense of your data is an inevitable part of the on-going digital transformation where the massively popular Elastic has combined it’s document database, connector, visualization capabilities and beyond with Elasticsearch, Logstash, Kibana and the plug-ins. It has created a versatile end-to-end stack of open source that gathers and delivers actionable insights in real time from almost any type of structured and unstructured data source.

As more and more enterprises have started believing in getting immediate, actionable insight from data matters, Elastic has moved further with more tools that integrate with the platform such as Beats, X-Pack extensions like Shield (security), Watcher (alerting), and Marvel (monitoring) to create an insightful ecosystem for enterprises. Large enterprises like Netflix, Sales force, Twitter, Facebook, Linkedin, and Microsoft of the worlds have realized the powerful promises of Elastic Stack which ranges from search, log analysis to analytics use cases. Adoption of NoSQL database and related technologies have helped them make crucial, informed, real-time decisions using data to gain flexibility and scalability. Also, lets note that all of these open source capabilities are spread across a variedrange of languages. With many languages and an open codebase, users can feel free to get involved with the feature development and bug fixing activities as per their requirements.

Some of the use cases include:

  • Agility, where the developers have the freedom
  • Customer 360° View
  • Personalize search experience (mobile and web) with data search and indexing
  • Real time performance monitoring and security
  • Log management and analytics
  • User behavior analytics and Visualization
  • Business risk management and fraud detection
  • Search engine scoring
  • Internet of Things

Elastic Stack Capabilites

  • Elasticsearch: Distributed, scalable, and highly available indexing, search, and analytics of log data using Sophisticated RESTful API
  • Logstash : Centralized data processing, normalize varying schema and formats, log data collection and extend to custom log formats, add plugins for custom data sources
  • Beats: Lightweight open source data shippers for data types to be processed with Logstash, searched and analyzed in Elasticsearch, and visualized in Kibana
  • Kibana: Real-time analytics, log reporting and visualization with an user interface
  • Integration with Elastic’s X-Pack plug-ins like Security (Shield), Alerting (Watcher), Monitoring (Marvel), Graph, and Reporting