Chapter 1, Understanding Your Data for Kibana, introduces the notion of data drive architecture by explaining the main challenges in the industry, how the Elastic Stack is structured, and what data we'll use to implement some of the use cases in Kibana.
Chapter 2, Installing and Setting Up Kibana, walks the reader through the installation of the Elastic Stack on different platforms.
Chapter 3, Business Analytics with Kibana, describes what a business analytics use case is through a real-life example, and then walks the reader through the process of data ingestion.
Chapter 4, Data Visualization Using Kibana, describes visualization and dashboarding. The readers will learn how to create different visualizations, before moving on to how to create a dashboard using these visualizations.
Chapter 5, Dev Tools and Timelion, is focused on Dev Tools and Timelion in Kibana. The readers will learn different options of Dev Tools, such as using Console to run Elasticsearch queries right from the Kibana interface. Then we will cover using Search Profiler to profile the Elasticsearch queries, and using Grok Debugger to create a Grok pattern with which we can convert unstructured data into structured data through Logstash. After that, we will cover Timelion, with which we can play with time-series data, because it provides some functions that can be chained together to create a complex visualization for specific use cases that can't be created using the Kibana Visualize option.
Chapter 6, Space and Graph Exploration in Kibana, describes the Elastic Stack Graph plugin, which provides graph analytics. The reader will be walked through the main use cases that the Graph plugin tries to solve, and will see how to interact with the data. After that, we will cover how to create different Spaces and add them with different roles and users.
Chapter 7, Elastic Stack Features, describes the importance of Elastic features. We will cover security using user and role management, and will then cover reporting, with which we can export CSV and PDF reports. After that, we will explore how to use monitoring to monitor the complete Elastic Stack, and with Watcher, we will configure the alerting system to send an email whenever a value crosses a specified threshold.
Chapter 8, Kibana Canvas and Plugins, describes the Kibana Canvas and explains how we can create custom dashboards with it.
Chapter 9, Application Performance Monitoring, describes Application Performance Monitoring (APM) and how it can be configured to monitor an application. We will cover the installation of APM Server and configure it to receive data from APM agents. Then, we will cover the installation and configuration of APM agents with the application in order to fetch the application data. Lastly, we will explain how to explore data with the built-in APM UI or Kibana Dashboard.
Chapter 10, Machine Learning with Kibana, introduces machine learning and explores how to find data anomalies and predict future trends.