Mastering ElasticSearch 6.x and the Elastic Stack

Video description

Elastic Stack is powered by the most popular open source search engine, ElasticSearch, currently used throughout the world by Fortune 500 companies such as Sprint and Dell and small startups who leverage the power and scalability of the Elastic Stack, without having to pay a fortune in licensing or professional services hours.

Getting ElasticSearch up and running is fairly straightforward, but fully understanding how to use the whole stack, from start to finish, is a rather daunting task. This course will focus on two major use cases with ElasticSearch. The first is leveraging the powerful full-text search engine ElasticSearch is built on, allowing developers to add blazingly fast search features to applications. The second is leveraging different components of the Elastic Stack to continuously monitor applications, infrastructure, or even customer transactions.

Throughout the course, students will go from a beginner to a master of Elastic Stack, via hands-on examples using real data.

What You Will Learn

  • Understand Elastic Stack from start to finish and be able to jump right into a real work project
  • Store structured and unstructured data typically found in system events or log files to gain visibility and understanding of your application
  • Learn the skills required to instantly search petabytes of data and provide amazing customer interactions
  • Build a central log collection system
  • Leverage HTTP-based APIs for ElasticSearch insert, query, and configure operations
  • Take advantage of the huge disk space saving capabilities in ES 6
  • Utilize new features to visualize Logstash pipelines


The course is for developers and system administrators who want to begin storing data in a cost-effective manner and want to leverage the functionality of the Elastic Stack. People with job titles such as Software Developer, Systems or Solutions Architect, System Administrator, DevOps Engineer, and so on will also be particularly interested in this course. Additionally, managers and directors in technology organizations will be able to understand the concepts and discuss them knowledgeably without breaking the budget.

About The Author

Chris Fauerbach: Chris Fauerbach is an avid learner and has been teaching technology in the classroom and business setting since early college. Chris has been dreaming of a Neo4J project for years. After spending countless hours learning the technology, the problem finally arose. While developing a cyber security program, the graph relationship turned out to be the right answer. Relational databases would be too complicated with dynamic relationships just wouldn't work. He has been developing software integration projects for over 20 years. He has a passion for data enrichment, cyber security and full-text search and is a huge proponent of open source software. Chris has a bachelors degree in computer science and a masters degree in information systems. Chris has written web applications, databases driven applications, big data systems etc. He's an expert in languages from C to Python, HTML to SQL. You can find Chris' blog at, his tweets @chrisfauerbach and on LinkedIn at

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Table of contents

  1. Chapter 1 : First Steps with Elasticsearch and Kibana
    1. The Course Overview
    2. Overview of a Final Working Solution – This Is What We're Working Towards
    3. Install and Configure Elasticsearch
    4. Install and Configure Kibana
    5. Enable Monitoring via X-Pack for Elasticsearch and Kibana
    6. Loading Example Data in Elasticsearch
  2. Chapter 2 : Getting Deeper with Elasticsearch
    1. How Do We Store and Group Data – Documents
    2. Specifying Document Attributes – Data Types
    3. Classifying Similar Documents Types
    4. Organizing and Grouping Documents Indexes
    5. Give Me My Data Back – Searches
  3. Chapter 3 : Kibana Deep Dive
    1. Kibana Is Huge – Let’s Take It Apart
    2. Configuring Groups of Data for Querying – Index Patterns
    3. Time Range Queries – Slicing and Dicing
    4. Searches – Refining Queries to Find the Needle in the Haystack
    5. Saving and Sharing – Let Your Friends Know What You Found
  4. Chapter 4 : Data Flow with Logstash and Beats
    1. Logstash – Introduction
    2. Visualizing Pipelines in Kibana
    3. Process Documents with Filters
    4. Get Data into Logstash as a Server
    5. Working with Beats
    6. Outputs – Where Else Can Data Go
  5. Chapter 5 : Kibana Visualizations and Dashboards
    1. Impress Your Boss with Charts and Graphs
    2. Building a Heads Up Dashboard
    3. Sharing Dashboards Recap
    4. Use Kibana to Monitor the Health of Your Elastic Stack
  6. Chapter 6 : Exploring X-Pack
    1. Security – Provide Authentication and Authorization to Kibana
    2. Graph – Use the Built in Graph Interface to Pivot Around Data
    3. Machine Learning Is Hot, See How Elastic Facilitate0073
    4. Application Perfromance Monitoring – APM
    5. Application Performance Monitoring – APM (Continued)
    6. Timelion – Time Series
  7. Chapter 7 : Scaling Elasticsearch
    1. Indexes, Shards, and Replicas
    2. Adding Elasticsearch Nodes to increase query and indexing performance
    3. Use Master Nodes to control the cluster
    4. Master and Data Nodes – Sizing Your Cluster
    5. SaaS offerings of Elasticsearch at AWS and Elastic Cloud

Product information

  • Title: Mastering ElasticSearch 6.x and the Elastic Stack
  • Author(s): Chris Fauerbach
  • Release date: June 2018
  • Publisher(s): Packt Publishing
  • ISBN: 9781788991155