The 6 Best Kibana Books You Should Read In 2022

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If you are a program developer or data engineer who wants to kick off your career in search and analytics or take your skills to the next level, these books can help you achieve that goal.

These books focus on a practical approach to learning, enabling you to apply the knowledge and skills you learn. Therefore, we compiled this list of the best Kibana books you should read.

These books cover topics from the introduction of Elasticsearch to the most advanced Elasticsearch capabilities that focus on enhancing your skills in Kibana and teach you to use it professionally.

1. Elasticsearch in Action

This book introduces you to the basics of Elasticsearch and how to integrate it with your application.

Why It Belongs On This list

The writers have taken an engaging, hands-on approach that provides a comprehensive learning experience that gives you all the required skills and resources. In addition, the book teaches you the core features of Elasticsearch and how to integrate it into your applications professionally and gives you fundamental knowledge and skills for using Elasticsearch.

The Book Description

Elasticsearch in Action covers all the basic features and capabilities that Elasticsearch has to offer, including how to build scalable search applications, using different analyzers, and efficient indexing. The books also cover optimizing your design and performance, relevancy rankings, use of data from prior user searches, and some “exotic” features, perfect for developers and administrators of search-orientated applications.

The book teaches you how to incorporate professional quality searches into any application. Elasticsearch’s real-time search and analytic engine allow you to give users a great experience without complex coding and advanced data science algorithms. The book includes source codes of the examples used and additional features in the appendixes. Prior experience working with Elasticsearch is not required.

What You Will Learn

Elasticsearch in Action will teach you how to add basic search features to any application, enhance search capabilities by adding predictive analysis and relevancy ranking, and use data from previous searches. In addition, this book will teach you how to use Elasticsearch and its features in various other programming languages.

Who This Book Is For

This book is for developers and administrators developing and maintaining applications that use search-orientated features.

Featured Content

1. Introducing Elasticsearch
2. Diving into the functionality
3. Indexing, updating, and deleting data
4. Searching your data
5. Analyzing your data
6. Searching with relevancy
7. Exploring your data with aggregations
8. Relations among documents
9. Scaling out
10. Improving performance
11. Administering your cluster’

2. Kibana 7 Quick Start Guide

Kibana 7 Quick Start Guide: Visualize your Elasticsearch data with ease 1st Edition aims to explain the essential aspects of Elasticsearch, additional tools, and plugins

Why It Belongs On This list

The book offers a hands-on guide to the core concept of Kibana, Elasticsearch data, and navigating the Elastic Stack. By using a step-by-step learning process, it is easy to follow along and build your skills and knowledge in Elasticsearch

The Book Description

Kibana 7 Quick Start Guide: Visualize your Elasticsearch data easily, explain the Elastic Stack’s growth, and deal with the tools added to use it more effectively. In addition, it explains the core functionality of Kibana and how you can use its full capabilities. The book is progressive for you to follow along as you advance your learning and work through the book.

Kibana 7 Quick Start Guide uses practical examples and explanations to enable you to apply those examples in real-time for a better understanding. In addition, it provides you with the required methods to implement your knowledge and skills. You can use this book as a reference guide for the primary and more advanced learning of Kibana. In addition, it teaches you how to create machine learning jobs using Kibana.

The practical examples used in the book include creating dashboards from CSV data, application RDBMS data, APM agents, log file data, and managing search results and system metrics. In addition, these examples provide you with various drop-off points that you can use to fetch any data type for analysis or dashboarding using Kibana. The in-depth demonstrations mean prior experience working with Elasticsearch is not required.

What You Will Learn

Kibana 7 Quick Start Guide will teach you how to fetch CSV data using Logstash, create indexing patterns, build dashboards, apply data filters, generate reports, find data anomalies, save, share, inspect, and edit visualizations. In addition, this book will teach you how to install and use various Kibana plugins.

Who Is The Book For

This book is for new and existing Elasticsearch developers who want to learn the fundamentals of using Elasticsearch for visualization.

Featured Content

1. Introducing Kibana
2. Getting data into Kibana
3. Exploring Data
4. Visualizing Data
5. X-Pack with Machine Learning
6. Monitoring Applications with APM
7. Kibana Advanced Tools

3. Elasticsearch

Elasticsearch: The Definitive Guide: A Distributed Real-Time Search and Analytics Engine explains how to integrate Elasticsearch into applications to solve complex problems and complete advanced processes.

Why It Belongs On This list

The unique problem-based approach to learning how and when to use Elasticsearch allows you to use your knowledge and skills acquired for real-life problems. The guide feature a comprehensive and information-dense manual that can significantly enhance your Elastcisearch capabilities and expertise.

The Book Description

The Elasticsearch: The Definitive Guide: A Distributed Real-Time Search and Analytics Engine covers how to put your data to work using Elasticsearch. The book shows you how to install, set up, and run Elasticsearch. It explains the terminology, features, processes, and configurations used with Elasticsearch and how to use it to solve complex problems and perform various tasks needed for search and data analysis.

The guide teaches you everything you need to know to integrate Elasticsearch into your application and advanced techniques to improve the efficiency of your application. In addition, it shows you how to search, analyze, and explore data using Elasticsearch and teaches you how to deal with the complexities of human language, relationships, and geolocation. Prior experience with Elasticsearch is helpful to get the most from the guide.

What You Will Learn

Elasticsearch: The Definitive Guide: A Distributed Real-Time Search and Analytics Engine will teach you why, when, and how to use Elasticsearch features such as processes needed to index and query data, relevance, and word proximity, horizontal scalability, and many more.

Who Is The Book For

This book is for new and experienced developers who need to incorporate search and distributed systems into applications.

Featured Content

1. You Know, for Search…
2. Life Inside a Cluster
3. Data In, Data Out
4. Distributed Document Store
5. Searching—The Basic Tools
6. Mapping and Analysis
7. Full-Body Search
8. Sorting and Relevance
9. Full-Body Search
10. Index Management

And Many More…

4. Advanced Elasticsearch 7.0

Advanced Elasticsearch 7.0: A Practical Guide To Designing, Indexing, And Querying Advanced Distributed Search Enginehelps you master the latest Elasticsearch 7.0 capabilities, scale, and speed-up performances.

Why It Belongs On This list

The book teaches advanced Elasticsearch features, where to use them, and how to use them to enhance your application and processes. It also teaches you to scale up your applications’ searching, indexing, and data aggregation.

The Book Description

Advanced Elasticsearch 7.0  focuses on teaching you to build enterprise-grade distributed applications and how to execute routine search operations using Elasticsearch’s core API and latest features. In addition, the book will help you master the advanced features of Elasticsearch and use them to develop sophisticated, real-time search engines quickly.

Advanced Elasticsearch 7.0 introduces machine learning jobs and how to incorporate them to speed up routine tasks. In addition, it teaches you to use advanced Elasticsearch features on Hadoop and Spark and gives you comprehensive knowledge of advanced topics such as Apache Spark support and scikit-learn. It would be best if you had prior experience working with Elasticsearch and its more advanced features to get the most out of this book.

What You Will Learn

Advanced Elasticsearch 7.0  teaches you to preprocess data before indexing by creating ingest pipelines to enhance self-service analytics, model data in the real world, use Kibana, Logstash, and Beats for dashboard applications, build analytics for RESTFul services, use Elasticsearch for real-time analytics, and how to use Elasticsearch to add indexing, searching and querying capabilities to Spring applications

Who Is The Book For

This book is for developers and data engineers who seek to improve their Elasticsearch knowledge and skills to develop enterprise-grade distributed search applications.

Featured Content

1. Overview of Elasticsearch 7
2. Index APIs
3. Document APIs
4. Mapping APIs
5. Anatomy of an Analyzer
6. Search APIs
7. Modeling Your Data in the Real World
8. Aggregations Frameworks
9. Preprocessing Documents in Ingest Pipelines
10. Using ElasticSearch for Exploratory Data Analysis

And Many More…

5. Machine Learning With The Elastic Stack

Machine Learning With The Elastic Stack: Expert Techniques To Integrate Machine Learning With Distributed Search And Analytics focuses on extensive volume data analysis and tools you can use with your Elastic Stack to improve performance.

Why It Belongs On This List

The book teaches you how to combine machine learning with the analytic capabilities of Elastic Stack, analyze mass search data and get valuable insight from them, and integrate external analytical tools into Elastic Stack to improve its performance significantly.

The Book Description

Machine Learning with the Elastic Stack: Expert techniques to integrate machine learning with distributed search and analytics teaches you how to install Elastic Stacks and combine them with machine learning. It teaches you how to use Elastic Stack to perform time series analysis of different kinds of data, such as log files, network flows, financial data, and metrics of applications.

The book will teach you to use machine learning within the Elastic Stack for security, logging, and metrics. It also shows you how to automate machine learning job distribution and management across Elasticsearch clusters and make them resilient to fail. In addition, it will teach you to incorporate machine learning within Elastic ecosystems and view results directly from Kibana. You should have Prior Elasticsearch experience.

What You Will Learn

Machine Learning with the Elastic Stack: Expert techniques to integrate machine learning with distributed search and analytics will teach you how Elastic Stacks work, how to install them to use machine learning features to their full potential, apply effective anomaly detection, and correlate anomalies of different layers of infrastructure by combining your created jobs.

Who Is The Book For

This book is for developers who want to integrate machine learning within their search and analytic applications and data professionals that want to gain insight into Elasticsearch data without needing machine learning specialists or relying on custom development.

Featured Content

1. Machine Learning for IT
2. Installing the Elastic Stack with Machine Learning
3. Event Change Detection
4. IT Operational Analytics and Root Cause Analysis
5. Security Analytics with Elastic Machine Learning
6. Alerting on ML Analysis
7. Using Elastic ML data in Kibana dashboards
8. Using Elastic ML with Kibana Canvas
9. Forecasting
10. ML Tips and Tricks

6. Elasticsearch 7.0 Cookbook

Elasticsearch 7.0 Cookbook: Over 100 Recipes For Fast, Scalable, And Reliable Search For Your Enterprise covers advanced Elasticsearch features such as Elastic Clouds and nodes

Why It Belongs On This List

Elasticsearch 7.0 Cookbook the knowledge and skills required to deploy and manage Elasticsearch nodes and complex topology clusters, deploy on an Elastic Cloud and explore the capabilities of Elasticsearch 7.0 with recipes are easy to follow.

The Book Description

Elasticsearch 7.0 Cookbook: Over 100 recipes for a fast, scalable, and reliable search for your enterprise, guides you through comprehensive recipes on what’s new in Elasticsearch 7.0, and teaches you how to create and initiate complex queries and analytics. The cookbook has recipes for performing index mapping, aggregation, and scripting using Elasticsearch. In addition, the book teaches you faster and more efficient techniques.

Installing Kibana allows you to monitor and extend a cluster using a variety of plugins. In addition, the book teaches you to integrate your Java, Scala, Python, and big data applications, including Apache Spark and Pig with Elasticsearch. The integration and recipes will enable you to create state-of-the-art data applications powered by enhanced functionalities and custom plugins. You require extensive prior experience with Elasticsearch.

What You Will Learn

Elasticsearch 7.0 Cookbook: Over 100 recipes for fast, scalable, and reliable search for your enterprise 4^th Edition will teach you how to use Elasticsearch to create an efficient architecture, integrate Java, Scala, Python, and big data applications with Elasticsearch, build complex queries, execute analytic aggregation to optimize search results, monitor the performance of your clusters and nodes, deploy an Elastic Cloud, design advanced mapping to take complete control of index steps, and installing Kibana to monitor groups of nodes.

Who Is The Book For

This book is for software engineers, prominent data infrastructure engineers, and Elasticsearch developers. In addition, data professionals can benefit from this book working in the e-commerce and FMCG industries and use Elastic for search analytics and metric evaluations to understand better and make more informed business decisions.

Featured Content

1. Getting started
2. Managing Mapping
3. Basic Operations
4. Exploring Search Capabilities
5. Text and Numeric Queries
6. Relationship and Geo Queries
7. Aggregations
8. Scripting in Elasticsearch
9. Managing Cluster
10. Backup and Restore

And Many More…