Data Visualization supports users to detect a pattern, monitor the environment and take actions when detecting anomalous behavior. Currently, the market has a huge list of data visualization tools that provide the visibility needed for understanding and analysing the given data.
Elastic Kibana is the most popular open source analytics and visualization platform designed to offer faster and better insights into your data. In this post, we will discuss this cutting- data visualization tool and its important features.
Overview of Elastic Kibana
Kibana is a visual interface tool that allows you to explore, visualize, and build a dashboard over the log data massed in Elastic Search Clusters. Elastic is the company behind Kibana and the two other open source tools – Elastic Search and Logs Tash. The Elastic Search tool serves as the database for document-oriented and semi-structured data. Logs Tash supports to collect, parse, and store logs for future use. These three tools can work well together and popularly known as ELK Stack or Elastic Stack.
The core feature of Kibana is data querying & analysis. In addition, Kibana’s visualization features allow you to visualize data in alternate ways using heat maps, line graphs, histograms, pie charts, and geospatial support. With various methods, you can search the data stored in Elasticsearch for root cause diagnostics.
With Kibana, it is easy to understand big data, and you can quickly build and share dynamic dashboards that frame-out changes to the Elasticsearch query in real-time. This visualization tool is equipped with various options in its left panel as shown below:
The Discover page ensures interactive data exploration by enabling access of each field in conjunction with default time. You can set the time filter, submit search queries, view document data, and filter the search results.
With the broad variety of visualization styles, Kibana allows you to create a visualization of your data in the Elasticsearch indices. The screenshot below depicts the visualization page:
You can combine pie charts, data tables, line charts, single metric visualization, time series, Geo maps, and markdown visualization into dashboards.
The following table lists down the available Kibana visualization types and their description:
This page displays the pool of visualizations and searches. The Kibana dashboard is extremely dynamic and adaptable. For example, you can filter the data on the fly and open the dashboard in full-page format. The customizable dashboard feature allows you to resize, arrange, and modify the dashboard content and save it so that you can share your dashboard.
Timelion analyzes and visualizes the time series data using simple expression language and it is designed to bring together the completely independent data sources within a single interface. It offers a way to define queries, visualization, and transformation in one place.
The complexity and extensions of datasets make it difficult to identify cyber-attacks, infrastructure issues, and business problems. However, the Kibana’s machine learning page intends to create anomaly detection jobs and observe results. This feature automatically models the behavior of the Elastic Search data, including periodicity & trends and spot issues faster thereby reduce false positives.
Application Performance Monitoring system supports users to monitor the applications as well as services and collects deep performance metrics and errors. Thereby the developers can inspect into performance data for their apps and rapidly spot the performance bottlenecks.
The Dev tools of Kibana provide a powerful way to interact with the Elastic Stack. As it includes Console that supports developers to write Elastic Search commands in one tab and view those commands in the different tab. Together with Console, a Grok debugger and a search profiler in this solution allow you to configure the app to meet your needs.
The monitoring page of Kibana serves you in three effective ways:
- You can visualize the data across Elastic Stack as it includes options to monitor the performance data for Elastic Search, Kibana, Logstash as well as Beats in real-time
- You can also analyze the past performance of these products
- You can ensure deep monitoring of Kibana and direct that data towards monitoring cluster
The management page of Kibana is used for performing Kibana’s runtime configuration, which includes three vital actions:
- Index pattern – supports for initial setup & ongoing configuration of index names
- Saved objects – hosts the saved visualization, dashboards, and searches
- Advanced settings – includes setting to tweak the Kibana’s behavior
Therefore, whether it is setting up security controls, adding data sources or handling pipelines, Kibana offers you a single interface solution.
What is Kibana used for?
For those of you who aren’t acquainted with this data analytics and visualization platform, here is a brief about the features that Kibana offers for you:
The in-built intuitive charts and reports of Kibana ensure the interactive navigation through the huge volume of log data. Moreover, you can dynamically zoom in & out the certain data subsets, drag time windows, and drill-down on reports to obtain actionable insights from the data.
Pre-built Aggregations & Filters
These features enable you to run a variety of analytics like top-N queries, histograms, and trends with a few clicks.
As said earlier, the machine-learning feature of this visualization tool supports you to detect anomaly even hidden ones in your data. This capability allows you to identify the root causes of issues as shown below:
Secure Sharing and Collaboration
Kibana ensures secure sharing of your visualization and dashboards, as there is an option that restricts the information viewing to protect data leakage. You can share your data, visualizations and even dashboards with your team members, boss, and customers who want to view the same details what you are viewing in Kibana.
In addition, the Kibana Dashboard Only Mode also supports to build a restricted access user, with limited visibility.
Besides, the plotting of data points, Elastic Kibana allows you to uncover the relationships between them. You can accomplish this with the powerful graphical exploration API, which provides an alternative way to explore as well as summarize information about the data in the Elastic Search index.
The Kibana is empowered with various methods to perform searches on the log data. The following table describes the common search methods that should be considered for optimised user experience:
The powerful geospatial features of Kibana make you seamlessly visualize geographical information over your data and observe the results on maps. The Elastic Maps service drives the geospatial visualisations in Elastic Kibana by aiding shape files, baseman tiles and key features that are vital for geodata visualization. The following screenshot depicts visualization on geospatial data:
In addition, a recent data layer update allows you to view more countries in Kibana region maps.
Canvas application in Kibana offers you a new way of making your data appear outstanding. Rashid Khan, the Kibana’s creator states, “Canvas is a composable, extendable, and a creative space for live data.” Get your imaginations into the live data with logo, colors, text, and shapes, which make your brand unique.
Watcher UI for Threshold-Based Alerts
The new UI of Kibana 6 creates and edits alerts based on thresholds. By previewing the alert constraints, it provides graphical feedback and type-ahead suggestions. In addition, it aids by sending alert messages along with template values to the email, log or slack.
One of the best features of Kibana is its reporting option that allows you to quickly generate reports of your visualization or dashboard. You can schedule the report for later, get it on demand and trigger it as per certain conditions. You can also automatically generate reports by submitting HTTP POST requests and it is possible to share it with others.
In this article, we have shared an overview of Kibana log analysis tool along with its attractive features that illustrate its offerings and capabilities. Undeniably, these features make it the best data visualization tool in the market now.