This is the code repository for Learning Elastic Stack 7.0 - Second Edition, published by Packt.
Distributed search, analytics, and visualization using Elasticsearch, Logstash, Beats, and Kibana
The Elastic Stack is a powerful combination of tools for techniques such as distributed search, analytics, logging, and visualization of data. Elastic Stack 7.0 encompasses new features and capabilities that will enable you to find unique insights into analytics using these techniques. This book will give you a fundamental understanding of what the stack is all about, and help you use it efficiently to build powerful real-time data processing applications.
This book covers the following exciting features:
- Install and configure an Elasticsearch architecture
- Solve the full-text search problem with Elasticsearch
- Discover powerful analytics capabilities through aggregations using Elasticsearch
- Build a data pipeline to transfer data from a variety of sources into Elasticsearch for analysis
- Create interactive dashboards for effective storytelling with your data using Kibana
- Learn how to secure, monitor and use Elastic Stack’s alerting and reporting capabilities
- Take applications to an on-premise or cloud-based production environment with Elastic Stack
If you feel this book is for you, get your copy today!
All of the code is organized into folders. For example, Chapter02.
The code will look like the following:
A block of code is set as follows:
POST _analyze
{
"tokenizer": "standard",
"text": "Tokenizer breaks characters into tokens!"
}
Following is what you need for this book: This book is for entry-level data professionals, software engineers, e-commerce developers, and full-stack developers who want to learn about Elastic Stack and how the real-time processing and search engine works for business analytics and enterprise search applications. Previous experience with Elastic Stack is not required, however knowledge of data warehousing and database concepts will be helpful.
With the following software and hardware list you can run all code files present in the book (Chapter 1-11).
| Chapter | Software required | OS required |
|---|---|---|
| 1-3 | Elasticsearch 7.x, Kibana 7.x | Windows, Mac OS X, and Linux (Any) |
| 4-5 | Elasticsearch 7.x, Kibana 7.x, Logstash 7.x | Windows, Mac OS X, and Linux (Any) |
| 6 | Elasticsearch 7.x, Kibana 7.x, Filebeat-oss | Windows, Mac OS X, and Linux (Any) |
| 7-8 | Elasticsearch 7.x-oss, Kibana 7.x-oss | Windows, Mac OS X, and Linux (Any) |
| 9 | Elasticsearch 7.x, Kibana 7.x | Windows, Mac OS X, and Linux (Any) |
| 10 | Elasticsearch 7.x, Kibana 7.x, Logstash 7.x, MySql 5.5 or higher | Windows, Mac OS X, and Linux (Any) |
| 11 | Elasticsearch 7.x, Kibana 7.x, Metricbeat-oss | Windows, Mac OS X, and Linux (Any) |
We also provide a PDF file that has color images of the screenshots/diagrams used in this book. Click here to download it.
Pranav Shukla is the founder and CEO of Valens DataLabs, a technologist, husband, and father of two. He is a big data architect and software craftsman who uses JVM-based languages. Pranav has over 14 years' experience in architecting enterprise applications for Fortune 500 companies and start-ups. His core expertise lies in building JVM-based, scalable, reactive, and data-driven applications using Java/Scala, the Hadoop ecosystem, Apache Spark, and NoSQL databases. Pranav founded Valens DataLabs with the vision of helping companies to leverage data to their competitive advantage. In his spare time, he enjoys reading books, playing musical instruments, singing, listening to music, and watching cricket.
Sharath Kumar M N did his master's in computer science at the University of Texas, Dallas, USA. He is currently working as a senior principal architect at Broadcom. Prior to this, he was working as an Elasticsearch solutions architect at Oracle. He has given several tech talks at conferences such as Oracle Code events. Sharath is a certified trainer – Elastic Certified Instructor – one of the few technology experts in the world who has been certified by Elastic Inc. to deliver their official from the creators of Elastic training. He is also a data science and machine learning enthusiast. In his free time, he likes playing with his lovely niece, Monisha; nephew, Chirayu; and his pet, Milo.
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