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Learning Kibana 5.0

Learning Kibana 5.0

By : Bahaaldine Azarmi
3.5 (2)
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Learning Kibana 5.0

Learning Kibana 5.0

3.5 (2)
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 (10 chapters)
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Combining Prelert, alerting, and Timelion


Prelert detects anomalies in data indexed in Elasticsearch, stores its results in Elasticsearch, but also provides out of the box dashboards to explore and understand anomalies. The Elastic stack provides a holistic platform for data analysis, in which we can just pick products to extend our anomaly detection experience. X-Pack alerting is the first choice as it could consume Prelert results to trigger relevant and accurate alerts. Timelion is also a fantastic choice to correlate the anomaly detection result to source data by using the statistics functions and customization features that it offers.

As said earlier, Prelert exposes a REST API that allows you to manage a job and get the result of the analysis.

Job details and endpoints

The preceding image details an Endpoint links section in which the REST APIs that we are going to use for alerting are listed. All APIs are documented at http://www.prelert.com/docs/products/latest/engine_api_reference...

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