Kibana 8.x - A Quick Start Guide to Data Analysis: Learn about data exploration, visualization, and dashboard building with Kibana

Kibana 8.x – A Quick Start Guide to Data Analysis
Contributors
About the author
About the reviewer
Preface
   Who this book is for
   What this book covers
   To get the most out of this book
   Download the example code files
   Conventions used
   Get in touch
   Share your thoughts
   Download a free PDF copy of this book
Part 1: Exploring Kibana
1
Introduction to Kibana
   Technical requirements
   Getting an overview of Kibana
      Installation
      Configuration
      Running Kibana
   Understanding data integrations
   Summary
2
Creating Data Views and Introducing Spaces
   Technical requirements
   Exploring data views
   Creating spaces
   Understanding saved objects in Kibana
   Summary
3
Discovering the Data through Discover
   Exploring your data
      Elasticsearch – a document store
      Datatypes in Elasticsearch
      The Discover page
   Working with queries
      Structuring KQL query (example)
      Pairing the queries with Boolean operators
      Searching numeric fields
      How to search when you don’t know how to spell what you wish to search for
   Creating a saved search
      Steps to create a saved search
   Summary
Part 2: Visualizations in Kibana
4
How About We Visualize?
   Technical requirements
   Exploring Lens visualizations
   Deep diving into the backend of visualizations in Kibana
   Understanding Canvas, Maps, and Markdown visualizations
      Building Canvas visualizations
      Building Maps visualizations
      Building Markdown visualizations
   Summary
5
Powering Visualizations with Near Real-Time Updates
   Technical requirements
   Understanding how to create TSVB visualizations
      Understanding the Aggregation dropdown in the Data tab
      Understanding the Group by dropdown in the Data tab
   Exploring the Metric, Top N, Gauge, Markdown, and Table types of TSVB
      Top N and Gauge
      Markdown and Table
      Putting TSVB to use
   Using Annotations
   Summary
Part 3: Analytics on a Dashboard
6
Data Analysis with Machine Learning
   Technical requirements
   Understanding anomaly detection in time series data
      How does the machine learning algorithm work?
   Analyzing data with entity-centric analysis
      Transforms
      DataFrame analytics
      APIs to implement to know more about machine learning
   Setting up alerts
   Summary
7
Graph Visualization
   Technical requirements
   Creating a graph
   Customizing a graph
   Troubleshooting a graph
      Performance-related issues
      Finding out whether there are any missing results
      Key points for supporting data from multiple indices
   Summary
8
Finally, the Dashboard
   Technical requirements
   Exploring sample dashboards
   Creating a dashboard from scratch
      Understanding a logging use case on a dashboard
   Sharing the dashboard
   Summary
Part 4: Querying on Kibana and Advanced Concepts
9
ES|QL and Advanced Kibana Concepts
   Technical requirements
   Learning the ES|QL building blocks
   Understanding how ES|QL works
   Advanced Kibana concepts
      Runtime fields
      Advanced Kibana settings
   Summary
10
Query DSL and Management through Kibana
   Technical requirements
   Learning about Query DSL
      Full text queries
      Geo queries
      Shape queries
      Joining queries
      Match-all queries
      Term-level queries
      Specialized queries
      Compound queries
   Deep-diving management concepts – RBAC
   Exploring watchers
   Summary
Index
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