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Kibana

Information Technology > Business intelligence and data analysis

Description

Kibana is a data visualization and exploration tool used for log and time-series analytics, application monitoring, and operational intelligence use cases. It offers intuitive charts and reports that you can use to interactively navigate through large amounts of log data. You can set up dashboards that provide at-a-glance visualizations of key metrics and trends. With Kibana, you can perform advanced data analysis and adjust your queries in real-time. It's part of the Elastic Stack (formerly known as ELK Stack), which includes Elasticsearch for search, Logstash for centralized logging and Beats for data collection. Kibana makes it easy to understand large volumes of data, and its simple, browser-based interface enables you to quickly create and share dynamic dashboards.

Stack

ELK

Expected Behaviors

LEVEL 1

Fundamental Awareness

At the fundamental awareness level, individuals should understand what Kibana is and its purpose. They should be familiar with basic Kibana concepts and have an awareness of Kibana's role in the ELK Stack. This level is about gaining a basic understanding and knowledge of the tool.

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LEVEL 2

Novice

Novices should be able to install and set up Kibana, navigate the interface, and create simple visualizations. They should understand Kibana index patterns and be able to perform basic data exploration using the Discover feature. At this stage, users are starting to apply their knowledge practically.

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LEVEL 3

Intermediate

Intermediate users should be capable of creating complex visualizations, using Kibana Query Language (KQL), setting up dashboards, and working with Kibana Lens and time series visual builder. They should also be able to configure Kibana Spaces for different user groups. This level involves more advanced usage and customization.

LEVEL 4

Advanced

Advanced users should be proficient in performing advanced data analysis using Kibana, implementing machine learning features, securing Kibana with X-Pack security, monitoring and troubleshooting Kibana, optimizing performance, and integrating Kibana with other tools and services. This level requires deep understanding and expertise in managing and optimizing Kibana.

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LEVEL 5

Expert

Experts should be able to design and implement custom Kibana plugins, use ElasticSearch with Kibana at an advanced level, perform root cause analysis with Kibana, develop advanced data visualization strategies, master Kibana's API for automation and integration purposes, and lead and manage large-scale Kibana deployments. This level represents mastery and leadership in Kibana usage.

Micro Skills

LEVEL 1

Fundamental Awareness

Recognizing Kibana as a data visualization tool
Identifying the types of data Kibana can handle
Understanding how Kibana fits into data analysis workflows
Knowing the difference between visualizations and dashboards
Understanding the concept of an index pattern
Recognizing the role of Elasticsearch in Kibana
Understanding the components of the ELK Stack (Elasticsearch, Logstash, Kibana)
Recognizing how Kibana interacts with Elasticsearch and Logstash
Identifying use cases for the ELK Stack
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LEVEL 2

Novice

Downloading the correct version of Kibana
Configuring Kibana with Elasticsearch
Starting and stopping Kibana service
Troubleshooting common installation issues
Understanding Kibana's main menu
Using the search bar
Accessing different features through the side navigation
Customizing the interface settings
Choosing the right visualization type
Configuring the data source for visualization
Customizing visualization appearance
Saving and sharing visualizations
Creating an index pattern
Managing existing index patterns
Understanding the role of index patterns in data visualization
Searching for specific data
Filtering and sorting data
Saving and exporting search results
Understanding the relationship between data fields
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LEVEL 3

Intermediate

Understanding different visualization types
Applying filters and aggregations
Using advanced settings for visualizations
Creating multi-series visualizations
Working with geo data
Writing basic KQL queries
Using KQL operators and functions
Combining multiple KQL queries
Saving and loading KQL queries
Adding visualizations to dashboards
Arranging and resizing dashboard elements
Sharing and exporting dashboards
Configuring dashboard refresh intervals
Creating visualizations with Lens
Changing visualization types in Lens
Working with multiple layers in Lens
Using Lens to create tables
Creating time series visualizations
Configuring axes and series
Adding annotations to time series visualizations
Using mathematical aggregations
Creating and managing Spaces
Assigning users to Spaces
Customizing features per Space
Importing and exporting objects between Spaces
LEVEL 4

Advanced

Applying advanced filters and queries
Using advanced aggregation types
Performing correlation analysis
Creating and interpreting heat maps
Setting up anomaly detection jobs
Configuring machine learning modules
Interpreting machine learning results
Integrating machine learning with dashboards
Configuring role-based access control
Setting up authentication providers
Implementing field and document level security
Enabling audit logging
Using Kibana's monitoring app
Interpreting Kibana logs
Troubleshooting common Kibana issues
Optimizing Kibana for better performance
Tuning Elasticsearch for Kibana
Optimizing dashboard loading times
Managing Kibana's memory usage
Scaling Kibana for large datasets
Integrating Kibana with Logstash and Beats
Embedding Kibana visualizations in external applications
Connecting Kibana to third-party APIs
Automating tasks with Kibana's API
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LEVEL 5

Expert

Understanding Kibana plugin architecture
Creating a basic Kibana plugin
Adding advanced features to Kibana plugins
Testing and debugging Kibana plugins
Deploying and maintaining Kibana plugins
Mastering ElasticSearch query DSL
Optimizing ElasticSearch for Kibana
Implementing advanced search strategies with ElasticSearch and Kibana
Troubleshooting complex ElasticSearch issues within Kibana
Using Kibana visualizations for root cause analysis
Applying machine learning features for anomaly detection
Interpreting Kibana logs for root cause analysis
Correlating events across multiple data sources in Kibana
Designing complex data visualizations
Implementing interactive dashboards
Using advanced features of Kibana Lens
Optimizing visualizations for performance
Understanding Kibana's REST API
Automating tasks using Kibana's API
Integrating Kibana with other services using the API
Securing Kibana's API
Planning and designing large-scale Kibana deployments
Managing Kibana clusters
Monitoring and optimizing Kibana performance at scale
Implementing security best practices for large-scale Kibana deployments

Skill Overview

  • Expert2 years experience
  • Micro-skills102
  • Roles requiring skill2

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