Kibana makes data analytics easy. It is one of the elites in providing visualization solutions for enterprises for data sets including runtime data, server logs, market statistics, geo-spatial data mappings, density graphs. It works with Elasticsearch and supports machine learning.
The tool can unravel secrets such as trends/patterns from the superficial metadata. It has become the default choice for visualization of predictive analysis of data accumulated in Elasticsearch.
The open-source data visualization dashboard is known as a charting tool for ELK or Elastic stack. It acts as a user interface for monitoring, managing and securing the Elastic cluster. Elastic refers to Kibana as the window into the Elastic Stack, offering a portal for users and companies.
ELK StackThe stack comprises Elasticsearch, Logstash, and Kibana. They work in perfect sync with each other. Elasticsearch is a search and analytics application. Logstash is a server-side data processing pipeline that ingests the data from various sources, transforms and sends it to a stash like Elasticsearch. Kibana visualizes data with charts and graphs. An Elastic stack is the newer and more flexible version of ELK stack. It comes with a lightweight, single-purpose data agent called ‘Beats’. |
Kibana provides rich built-in tools for different data sets to match custom visualization requirements. Like Timelion for time series data, Canvas for creating dynamic, multi-page, pixel-perfect displays, Maps for defining geospatial data. These built-in features of Kibana give immense flexibility and customization.
Usability and dynamics
The tool is also known for its great usability and dynamics. It can monitor the entire solution including bare metal servers, services, databases, network, individual applications. Kibana and indexing with Elasticsearch can easily generate daily/weekly/seasonal operation reports and calculation of load distribution.
Ability to integrate
Another important feature is its ability to integrate with various technologies for trading data. With the growing popularity of Elasticsearch, many technology solution vendors are now providing adaptors and connectors for integration with Elasticsearch. For example, Kafka Connect framework has a production-ready connector for Elasticsearch.
Please find the link here from Confluent’s official webpage: Kafka Connect Elasticsearch connector
All the Elastic components are open-sourced and are freely available for commercial and personnel use under Apache 2.0 license. Besides having strong community support for the Elastic stack, Elastic itself provides managed services in the cloud and on-premise. This enables organizations having mission-critical use-case to opt for Elastic support.
You can find more details here: Kibana official release
For a better understanding of Kibana working with Elasticsearch, refer and implement the POC below.
Please find the link here: ingest visualize CVC
This POC is to understand the working of Elasticsearch (enabled with Cerebro UI) to ingest a CSV containing Geo-coordinates and visualize the latter with Kibana. Please find the related artifacts in the same repository.
* Cerebro is an open source (MIT License) Elasticsearch web admin tool built using Scala, Play Framework, AngularJS and Bootstrap.
Written by Amit Sahu
For similar articles, please read further:
http://elastic.co/products/kibana
http://github.com/elastic/kibana
http://logz.io/blog/kibana-tutorial/
https://aws.amazon.com/elasticsearch-service/the-elk-stack/
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