5.4.2 / 21 June 2017; 3 months ago (2017-06-21)
KIBANA is an open source data visualization plugin for Elasticsearch. It provides visualization capabilities on top of the content indexed on an Elasticsearch cluster. Users can create bar, line and scatter plots, or pie charts and maps on top of large volumes of data.
The combination of Elasticsearch, Logstash, and Kibana (also known as ELK stack or Elastic stack) is available as products or service. Logstash provides an input stream to Elastic for storage and search, and Kibana accesses the data for visualizations such as dashboards.
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Kibana is an open source data visualization platform that allows you to interact with your data through stunning, powerful graphics. Its simple, browser-based interface enables you to quickly create and share dynamic dashboards that display changes to Elasticsearch queries in real time.
In this book, you ll learn how to use the Elastic stack on top of a data architecture to visualize data in real time. All data architectures have different requirements and expectations when it comes to visualizing the data, whether it s logging analytics, metrics, business analytics, graph analytics, or scaling them as per your business requirements. This book will help you master Elastic visualization tools and adapt them to the requirements of your project.
You will start by learning how to use the basic visualization features of Kibana 5. Then you will be shown how to implement a pure metric analytics architecture and visualize it using Timelion, a very recent and trendy feature of the Elastic stack. You will learn how to correlate data using the brand-new Graph visualization and build relationships between documents. Finally, you will be familiarized with the setup of a Kibana development environment so that you can build a custom Kibana plugin.
By the end of this book you will have all the information needed to take your Elastic stack skills to a new level of data visualization.
Bahaaldine Azarmi, Baha for short, is a Solutions Architect at Elastic. Prior to this position, Baha co-founded reachfive, a marketing data-platform focused on user behavior and social analytics. Baha also worked for different software vendors such as, Talend or Oracle, where he held the positions of Solutions Architect and Architect. Before Learning Kibana 5.0, Baha authored books such as Scalable Big Data Architecture, by Apress and Talend for Big Data, by Packt Publishing. Baha is based in Paris and has a Master's Degree in computer science from Polytech'Paris.
Applied ELK Stack will teach you to configure the software, install tools, and build a data pipeline. You will learn the key features of Logstash and its role in the ELK stack, including creating Logstash plugins, which will enable you to use your own customized plugins. The importance of Elasticsearch and Kibana in the ELK stack is covered, along with various types of advanced data analysis, including charts, tables, and maps.
The simple and powerful nature of ELK stack has contributed to its quick adoption.
With this book you will learn:
Elasticsearch in Action teaches you how to build scalable search applications using Elasticsearch. You'll ramp up fast, with an informative overview and an engaging introductory example. Within the first few chapters, you'll pick up the core concepts you need to implement basic searches and efficient indexing. With the fundamentals well in hand, you'll go on to gain an organized view of how to optimize your design. Perfect for developers and administrators building and managing search-oriented applications.
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
About the Technology
Modern search seems like magicâyou type a few words and the search engine appears to know what you want. With the Elasticsearch real-time search and analytics engine, you can give your users this magical experience without having to do complex low-level programming or understand advanced data science algorithms. You just install it, tweak it, and get on with your work.
About the Book
Elasticsearch in Action teaches you how to write applications that deliver professional quality search. As you read, you'll learn to add basic search features to any application, enhance search results with predictive analysis and relevancy ranking, and use saved data from prior searches to give users a custom experience. This practical book focuses on Elasticsearch's REST API via HTTP. Code snippets are written mostly in bash using cURL, so they're easily translatable to other languages.
About the Reader
For developers and administrators building and managing search-oriented applications.
About the Authors
Radu Gheorghe is a search consultant and software engineer. Matthew Lee Hinman develops highly available, cloud-based systems. Roy Russo is a specialist in predictive analytics.
Table of Contents
Whether you need full-text search or real-time analytics of structured dataâor bothâthe Elasticsearch distributed search engine is an ideal way to put your data to work. This practical guide not only shows you how to search, analyze, and explore data with Elasticsearch, but also helps you deal with the complexities of human language, geolocation, and relationships.
If youâre a newcomer to both search and distributed systems, youâll quickly learn how to integrate Elasticsearch into your application. More experienced users will pick up lots of advanced techniques. Throughout the book, youâll follow a problem-based approach to learn why, when, and how to use Elasticsearch features.
Use the many types of tools required to navigate and maintain a microservice ecosystem. This book examines what is normally a complex system of interconnected services and clarifies them one at a time, first examining theoretical requirements then looking at concrete tools, configuration, and workflows.
Building out these systems includes many concerns such as containerization, container orchestration, build pipelines and continuous integration solutions, automated testing, service discovery, logging and analytics. You will examine each of these tools and understand how they can be combined within an organization. You will design an automated build pipeline from Pull Request to container deployment, understand how to achieve High Availability and monitor application health with Service Discovery, and learn how to collaborate with other teams, write documentation, and describe bugs.
Covering use of Jenkins, Docker, Kubernetes, the ELK stack (Elasticsearch, Logstash, and Kibana), and StatsD and Grafana for analytics, you will build on your existing knowledge ofÂ Service-Oriented ArchitectureÂ and gain an advanced, practical understanding of everything from infrastructure development to team collaboration.Â
What You'll Learn
Who This Book Is For
Get the most out of the Elastic Stack for various complex analytics using this comprehensive and practical guide
This book cater to developers using the Elastic stack in their day-to-day work who are familiar with the basics of Elasticsearch, Logstash, and Kibana, and now want to become an expert at using the Elastic stack for data analytics.
Even structured data is useless if it can't help you to take strategic decisions and improve existing system. If you love to play with data, or your job requires you to process custom log formats, design
Build mesmerizing visualizations, analytics, and logs from your data using Elasticsearch, Logstash, and Kibana
If you are a developer or DevOps engineer interested in building a system that provides amazing insights and business metrics out of data sources, of various formats and types, using the open source technology stack that ELK provides, then this book is for you. Basic knowledge of Unix or any programming language will be helpful to make the most out of this book.
The ELK stackâElasticsearch, Logstash, and Kibana, is a powerful combination of open source tools. Elasticsearch is for deep search and data analytics. Logstash is for centralized logging, log enrichment, and parsing. Kibana is for powerful and beautiful data visualizations. In short, the Elasticsearch ELK stack makes searching and analyzing data easier than ever before.
This book will introduce you to the ELK (Elasticsearch, Logstash, and Kibana) stack, starting by showing you how to set up the stack by installing the tools, and basic configuration. You'll move on to building a basic data pipeline using the ELK stack.
Next, you'll explore the key features of Logstash and its role in the ELK stack, including creating Logstash plugins, which will enable you to use your own customized plugins. The importance of Elasticsearch and Kibana in the ELK stack is also covered, along with various types of advanced data analysis, and a variety of charts, tables ,and maps.
Finally, by the end of the book you will be able to develop full-fledged data pipeline using the ELK stack and have a solid understanding of the role of each of the components.
This book is a step-by-step guide, complete with various examples to solve your data analytics problems by using the ELK stack to explore and visualize data.
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