Learning Elastic Stack 6.0
A beginner's guide to distributed search, analytics, and visualization using Elasticsearch, Logstash and Kibana
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- 2017.12.22. 전자책 출간
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<Learning Elastic Stack 6.0> ▶Book Description
The Elastic Stack is a powerful combination of tools for distributed search, analytics, logging, and visualization of data from medium to massive data sets. The newly released Elastic Stack 6.0 brings new features and capabilities that empower users to find unique, actionable insights through these techniques. This book will give you a fundamental understanding of what the stack is all about, and how to use it efficiently to build powerful real-time data processing applications.
After a quick overview of the newly introduced features in Elastic Stack 6.0, you'll learn how to set up the stack by installing the tools, and see their basic configurations. Then it shows you how to use Elasticsearch for distributed searching and analytics, along with Logstash for logging, and Kibana for data visualization. It also demonstrates the creation of custom plugins using Kibana and Beats. You'll find out about Elastic X-Pack, a useful extension for effective security and monitoring. We also provide useful tips on how to use the Elastic Cloud and deploy the Elastic Stack in production environments.
On completing this book, you'll have a solid foundational knowledge of the basic Elastic Stack functionalities. You'll also have a good understanding of the role of each component in the stack to solve different data processing problems.
▶What You Will Learn
⦁ Familiarize yourself with the different components of the Elastic Stack
⦁ Get to know the new functionalities introduced in Elastic Stack 6.0
⦁ Effectively build your data pipeline to get data from terabytes or petabytes of data into Elasticsearch and Logstash for searching and logging
⦁ Use Kibana to visualize data and tell data stories in real-time
⦁ Secure, monitor, and use the alerting and reporting capabilities of Elastic Stack
⦁ Take your Elastic application to an on-premise or cloud-based production environment
⦁ Get to grips with the new features introduced in Elastic Stack 6.0
⦁ Get valuable insights from your data by working with the different components of the Elastic stack such as Elasticsearch, Logstash, Kibana, X-Pack, and Beats
⦁ Includes handy tips and techniques to build, deploy and manage your Elastic applications efficiently on-premise or on the cloud
▶Who This Book Is For
This book is for data professionals who want to get amazing insights and business metrics from their data sources. If you want to get a fundamental understanding of the Elastic Stack for distributed, real-time processing of data, this book will help you. A fundamental knowledge of JSON would be useful, but is not mandatory. No previous experience with the Elastic Stack is required.
▶What this book covers
⦁ Chapter 1, Introducing Elastic Stack, motivates the reader by introducing the core components of Elastic Stack, importance of distributed, scalable search and analytics that Elastic Stack offers with use cases of ElasticSearch. The chapter gives a brief introduction to all core components, shows where do they fit in the overall stack, and details the purpose of each component. It concludes with instructions for downloading and installing ElasticSearch and Kibana to get started.
⦁ Chapter 2, Getting Started with ElasticSearch, introduces the core concepts involved in ElasticSearch, which forms the backbone of the Elastic Stack. Concepts such as indexes, types, nodes, and clusters are introduced. The reader is introduced to the REST API for performing essential operations, datatypes, and mappings.
⦁ Chapter 3, Searching What Is Relevant, focuses on the search use-case for ElasticSearch. It introduces the concepts of text analysis, tokenizers, analyzers, and the need for analysis and relevance-based searching. The chapter uses and example use-case to cover the relevance based search topics.
⦁ Chapter 4, Analytics with ElasticSearch, covers various types of aggregations with examples to gain fundamental understanding. It starts off with very simple to complex aggregations to get powerful insights from terabytes of data. The chapter also covers reasons for using different types of aggregations.
⦁ Chapter 5, Analyzing Log Data, lays the foundation for the motivation behind logstash, the architecture of logstash, and installing and configuring logstash to set up basic data pipelines. Elastic 5 introduced Ingest Node, which can be used instead of a dedicated Logstash setup. We will also cover building pipelines using Elastic Ingest Nodes.
⦁ Chapter 6, Building Data Pipelines with Logstash, builds on the fundamental knowledge of Logstash by transformations and aggregation related filters. It covers how a rich set of filters brings Logstash closer to the other real-time and near-real-time stream processing frameworks with zero coding. It introduces the Beats platform, and the FileBeat component, which is used to transport log files from the edge machines.
⦁ Chapter 7, Visualizing Data with Kibana, covers how to effectively use Kibana to build beautiful dashboards for effective storytelling about your data. It uses a sample dataset and provides step-by-step guidance on creating visualizations in a few clicks.
⦁ Chapter 8, Elastic X-Pack, since we have covered ElasticSearch and the core components that help us build data pipelines and visualize data, it's now time to add the extensions needed for specific use cases. This chapter shows you how to install and configure X-Pack components in Elastic Stack and teaches you to secure, monitor, and use alerting extensions.
⦁ Chapter 9, Building a Sensor Data Analytics Application, puts together a complete application for sensor data analytics with the concepts learned so far. It shows you how to model your data in ElasticSearch, how to build the data-pipeline to ingest the data and how to visualize it using Kibana. The chapter also demonstrates how to effectively use X-Pack components to secure and monitor your pipeline, and get alerts when certain conditions are met.
⦁ Chapter 10, Running Elastic Stack in Production, covers recommendations on how to deploy Elastic Stack to production. It provides recommendations for taking your application to production and guidelines on typical configurations that need to be looked at for different use cases. It also covers deploying into cloud-based hosted providers such as Elastic Cloud.
⦁ Chapter 11, Monitoring Server Infrastructure, shows how we can use Elastic Stack to set up a real-time monitoring solution for your servers, applications that are built completely using Elastic Stack. It introduces another component of the Beats platform, MetricBeat, which is used to monitor servers/applications.
Elastic Stack is a powerful combination of tools for the distributed search, analytics, logging, and visualization of data from medium to massive data sets. The newly released Elastic Stack 6.0 brings new features and capabilities that empower users to find unique, actionable insights through these techniques. This book will give you a fundamental understanding of what the stack is all about, and how to use it efficiently to build powerful real-time data processing applications.
After a quick overview of the newly introduced features in Elastic Stack 6.0, you'll learn how to set up the stack by installing the tools, and see their basic configurations. Then the book shows you how to use Elasticsearch for distributed searching and analytics, along with Logstash for logging, and Kibana for data visualization. It also demonstrates the creation of custom plugins using Kibana and Beats. You'll find out about Elastic X-Pack, a useful extension for effective security and monitoring. We also provide useful tips on how to use the Elastic Cloud and deploy Elastic Stack in production environments.
⦁ Pranav Shukla
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 diverse experience of over 14 years 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. He is a big data engineering, analytics, and machine learning enthusiast.
Pranav founded Valens DataLabs with a vision to help companies leverage data to their competitive advantage. Valens DataLabs specializes in developing next-generation, cloud-based, reactive, and data-intensive applications using big data and web technologies. The company believes in agile practices, lean principles, test-driven and behavior-driven development, continuous integration, and continuous delivery for sustainable software systems.
In his free time, he enjoys reading books, playing musical instruments, singing, listening to music, and watching cricket. You can follow him on Twitter at @pranavshukla81.
⦁ Sharath Kumar M N
Sharath Kumar M N has done his masters in Computer Science at The University of Texas, Dallas, USA. He has been in the IT industry for more than ten years now and is the Elasticsearch Solutions Architect at Oracle. He is an Elastic Stack advocate, and being an avid speaker he has also given several tech talks in conferences such as the Oracle Code Event. 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 enjoys trekking, listening to music, playing with his lovely pets Guddu and Milo and the geek in him loves exploring his Python skills for stock market analysis.
▶TABLE of CONTENTS
1: INTRODUCING ELASTIC STACK
2: GETTING STARTED WITH ELASTICSEARCH
3: SEARCHING-WHAT IS RELEVANT
4: ANALYTICS WITH ELASTICSEARCH
5: ANALYZING LOG DATA
6: BUILDING DATA PIPELINES WITH LOGSTASH
7: VISUALIZING DATA WITH KIBANA
8: ELASTIC X-PACK
9: RUNNING ELASTIC STACK IN PRODUCTION
10: BUILDING A SENSOR DATA ANALYTICS APPLICATION
11: MONITORING SERVER INFRASTRUCTURE
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