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 4. Logging Analytics with Kibana 5.0

The previous chapter showed how to use the Elastic stack for a business (logging) use case, which confirms that Elastic is not only a solution made for technical use cases, but rather a data platform that you can shape depending on your needs.

In the logging use case field, one of the most implemented within the technical domain is the web server logging use case. This chapter is a continuation of the previous one in the sense that we are dealing with logs, but addresses the problem from a different angle.

The goal here is first to understand the web logs use case, then to start importing both data in Elasticsearch, and dashboards in Kibana. We will go through the different visualizations available as part of the dashboard to see what key performance indicators can be extracted from the logs.

Finally, we'll ask our dashboard a question and deduce some more high-level considerations from the data, such as security or bandwidth insights.