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

Understanding the concept of anomaly detection

In this section, we'll try to summarize how Prelert solves the challenge of anomaly detection by first understanding why data visualization is a sufficient medium when it comes to pointing out an anomaly, and then we'll see why traditional alerting systems cannot be used at scale for anomaly detection.

Understanding human limits with regard to data visualization

Anomaly detection is the art of detecting things that shouldn't occur, or that differ from normal occurrences. Anomaly detection is the general name given to a statistical modeling technique used to identify unusual patterns in time-based events.

If we take the following dashboard, we can see different things happening:

IT ops dashboard with potential anomalies

In the preceding screenshot, we can see a significant drop in the first graph (point 1). This looks suspicious, and may indicate a problem. Now, compared with the rest of the charts alongside it, we see that the increases in points...