Book Image

Learning Kibana 5.0

By : Bahaaldine Azarmi
Book Image

Learning Kibana 5.0

By: Bahaaldine Azarmi

Overview of this book

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.
Table of Contents (17 chapters)
Learning Kibana 5.0
About the Author
About the Reviewers
Customer Feedback

Chapter 1. Introduction to Data-Driven Architecture

If you are reading this book, it certainly means that you and I have something in common: we are both looking for a solution to effectively visualize and understand our data.

Data can be anything: business data, infrastructure data, accounting data, numbers, strings, structured, or unstructured. In any case, all organizations reach a point where trying to understand data and extract the value of it begins to be a real challenge, for different reasons:

  • Data brings complexity: If we take the example of an e-commerce IT operation team where one must find why the orders just dropped, it can be a very tricky process to go to the log to get the issue.

  • Data comes from a variety of sources: Infrastructure, applications, devices, legacy systems, databases, and so on. Most of the time, you need to correlate them. In the e-commerce example, maybe the drop is due to an issue in my database?

  • Data increases at a very fast pace: Data growth implies some new questions, such as which data should I keep? Or how do I scale my data management infrastructure?

The good news is that you won't need to learn it the hard way, as I'll try in this book to explain how I've tackled data analytics projects for different use cases and for different types of data based on my experience.

The other good news is that I'm part of the Solutions Architecture (SA) team at Elastic, and guess what? We'll use the Elastic stack. By being part of the SA team, I'm involved in a variety of use cases, from small to large scale, with different industries; the main goal is always to give to our users better management of and access to their data, and a better way to understand their data.

In this book, we'll dig into the use of Kibana, the data analytics layer of the Elastic stack. Kibana is the data visualization layer used in an overall data-driven architecture.

But what is data-driven architecture? This is the concept I will illustrate in this chapter by going through industry challenges, the usual technology used to answer this need, and then we'll go into the description of the Elastic stack.