Kibana 8.x - A Quick Start Guide to Data Analysis: Learn about data exploration, visualization, and dashboard building with Kibana [1 ed.] 9781803232164

Table of contents :
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
Why subscribe?
Other Books You May Enjoy
Packt is searching for authors like you
Share your thoughts
Download a free PDF copy of this book