Kibana 8.x - A Quick Start Guide to Data Analysis

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
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Part 1: Exploring Kibana
Chapter 1: Introduction to Kibana
	Technical requirements
	Getting an overview of Kibana
		Installation
		Configuration
		Running Kibana
	Understanding data integrations
	Summary
Chapter 2: Creating Data Views and Introducing Spaces
	Technical requirements
	Exploring data views
	Creating spaces
	Understanding saved objects in Kibana
	Summary
Chapter 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
Chapter 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
Chapter 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
Chapter 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
Chapter 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
Chapter 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
Chapter 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
Chapter 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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