Learning Kibana 7: Build powerful Elastic dashboards with Kibana’s data visualization capabilities, 2nd Edition
- Length: 280 pages
- Edition: 2
- Language: English
- Publisher: Packt Publishing
- Publication Date: 2019-07-19
- ISBN-10: 1838550364
- ISBN-13: 9781838550363
- Sales Rank: #170468 (See Top 100 Books)
A beginner’s guide to analyzing and visualizing your Elasticsearch data using Kibana 7 and Timelion
Key Features
- Gain a fundamental understanding of how Kibana operates within the Elastic Stack
- Explore your data with Elastic Graph and create rich dashboards in Kibana
- Learn scalable data visualization techniques in Kibana 7
Book Description
Kibana is a window into the Elastic Stack, that enables the visual exploration and real-time analysis of your data in Elasticsearch. This book will help you understand the core concepts of the use of Kibana 7 for rich analytics and data visualization.
If you’re new to the tool or want to get to grips with the latest features introduced in Kibana 7, this book is the perfect beginner’s guide. You’ll learn how to set up and configure the Elastic Stack and understand where Kibana sits within the architecture. As you advance, you’ll learn how to ingest data from different sources using Beats or Logstash into Elasticsearch, followed by exploring and visualizing data in Kibana. Whether working with time series data to create complex graphs using Timelion or embedding visualizations created in Kibana into your web applications, this book covers it all. It also covers topics that every Elastic developer needs to be aware of, such as installing and configuring Application Performance Monitoring (APM) servers and agents. Finally, you’ll also learn how to create effective machine learning jobs in Kibana to find anomalies in your data.
By the end of this book, you’ll have a solid understanding of Kibana, and be able to create your own visual analytics solutions from scratch.
What you will learn
- Explore the data-driven architecture of the Elastic Stack
- Install and set up Kibana 7 and other Elastic Stack components
- Use Beats and Logstash to get input from different data sources
- Create different visualizations using Kibana
- Build enterprise-grade Elastic dashboards from scratch
- Use Timelion to play with time series data
- Install and configure APM servers and APM agents
- Work with Dev Tools, Spaces, Graph, and other important tools
Who this book is for
If you’re an aspiring Elastic developer or data analysts, this book is for you. You’ll also find it useful if you want to get up to speed with the new features of Kibana 7 and perform data visualization on enterprise data. No prior knowledge of Kibana is expected, but some experience with Elasticsearch will be helpful.
Table of Contents
- Understanding Your Data for Kibana
- Installing and Setting Up Kibana
- Business Analytics with Kibana
- Visualizing Data Using Kibana
- Dev Tools and Timelion
- Space and Graph Exploration in Kibana
- Elastic Stack Features
- Kibana Canvas and Plugins
- Application Performance Monitoring
- Machine Learning with Kibana
Title Page
Copyright and Credits
Learning Kibana 7 Second Edition
Dedication
About Packt
Why subscribe?
Contributors
About the authors
About the reviewer
Packt is searching for authors like you
Preface
Who this book is for
What this book covers
To get the most out of this book
Download the example code files
Download the color images
Conventions used
Get in touch
Reviews
Section 1: Understanding Kibana 7
Understanding Your Data for Kibana
Industry challenges
Use cases to explain industry issues
Understanding your data for analysis in Kibana
Data shipping
Data ingestion
Storing data at scale
Visualizing data
Technology limitations
Relational databases
Hadoop
NoSQL
Components of the Elastic Stack
Elasticsearch
Beats
Logstash
Kibana
X-Pack
Security
Monitoring
Alerting
Reporting
Summary
Installing and Setting Up Kibana
Installing Elasticsearch
Elasticsearch installation using the .zip or .tar.gz archives
Downloading and installing using the .zip archive
Downloading and installing using the .tar.gz archive
Running Elasticsearch
Elasticsearch installation on Windows using the .zip package
Downloading and installing the .zip package
Running Elasticsearch
Installing Elasticsearch as a service
Elasticsearch installation using the Debian package
Installing Elasticsearch using the apt repository
Manually installing using the Debian package
Elasticsearch installation using RPM
Installing using the apt repository
Manually installing using RPM
Running Elasticsearch
Running Elasticsearch with SysV
Running Elasticsearch with systemd
Checking whether Elasticsearch is running
Installing Kibana
Kibana installation using the .zip or .tar.gz archives
Downloading and installing using the .tar.gz archive
Running Kibana
Downloading and installing using the .zip archive
Running Kibana
Kibana installation using the Debian package
Installing using the apt repository
Manually installing Kibana using the Debian package
Running Kibana
Running Kibana with SysV
Running Kibana with systemd
Kibana installation using RPM
Installing using the apt repository
Manually installing using RPM
Running Kibana
Running Kibana with SysV
Running Kibana with systemd
Installing Logstash
Installing Logstash using the downloaded binary
Installing Logstash from the package repositories
Installing Logstash using the apt package
Installing Logstash using the yum package
Running Logstash as a service
Running Logstash using systemd
Running Logstash using upstart
Running Logstash using SysV
Installing Beats
Installing Filebeat
deb
rpm
macOS
Linux
win
Installing Metricbeat
deb
rpm
macOS
Linux
win
Installing Packetbeat
deb
rpm
macOS
Linux
win
Installing Heartbeat
deb
rpm
macOS
Linux
win
Installing Winlogbeat
Summary
Section 2: Exploring the Data
Business Analytics with Kibana
Understanding logs
Data modeling
Importing data
Beats
Configuring Filebeat to import data we need to enable the following command in the input section of the filebeat.yml file
Reading log files using Filebeat
Logstash
Reading CSV data using Logstash
Reading MongoDB data using Logstash
Reading MySQL data using Logstash
Creating an index pattern
Summary
Visualizing Data Using Kibana
Creating visualizations in Kibana
Identifying the data to visualize
Creating an area chart, a line chart, and a bar chart
Creating a pie chart
Creating the heatmap
Creating the data table
Creating the metric visualization
Creating the tag cloud
Inspecting the visualization
Sharing the visualization
Creating dashboards in Kibana
Sharing the dashboard
Generating reports
Summary
Section 3: Tools for Playing with Your Data
Dev Tools and Timelion
Introducing Dev Tools
Console
Search profiler
Aggregation profile
Grok Debugger
Timelion
.es()
.label()
.color()
.static()
.bars()
.points()
.derivative()
.holt()
.trend()
.mvavg()
A use case of Timelion
Summary
Space and Graph Exploration in Kibana
Kibana spaces
Creating a space
Editing a space
Deleting a space
Switching between spaces
Moving saved objects between spaces
Restricting space access
Creating a role to provide access to a space
Creating a user and assigning the space access role
Checking the user space access
Kibana graphs
Differences with industry graph databases
Creating a Kibana graph
Advanced graph exploration
Summary
Section 4: Advanced Kibana Options
Elastic Stack Features
Security
Roles
Users
Monitoring
Elasticsearch Monitoring
Kibana Monitoring
Alerting
Creating a threshold alert
Reporting
CSV reports
PDF and PNG reports
Summary
Kibana Canvas and Plugins
Kibana Canvas
Introduction to Canvas
Customizing the workpad
Managing assets
Adding elements
Data tables
Designing the data table
Pie charts
Images
Creating a presentation in Canvas
Kibana plugins
Installing plugins
Removing plugins
Available plugins
Summary
Application Performance Monitoring
APM components
APM agents
The APM Server
Installing the APM Server
APT
YUM
APM Server installation on Windows
Running the APM Server
Configuring the APM Server
Elasticsearch
Kibana
Configuring an application with APM
Configuring the APM agent for the Django application
Running the Django application
Monitoring the APM data
Summary
Machine Learning with Kibana
What is Elastic machine learning?
Machine learning features
Creating machine learning jobs
Data visualizer
Single metric jobs
Practical use case to explain machine learning
Forecasting using machine learning
Multi-metric jobs
Population jobs
Job management
Job settings
Job config
Datafeed
Counts
JSON
Job messages
Datafeed preview
Forecasts
Summary
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