Book Image

Kibana 8.x – A Quick Start Guide to Data Analysis

By : Krishna Shah
Book Image

Kibana 8.x – A Quick Start Guide to Data Analysis

By: Krishna Shah

Overview of this book

Unleash the full potential of Kibana—an indispensable tool for data analysts to seamlessly explore vast datasets, uncover key insights, identify trends and anomalies, and share results. This book guides you through its user-friendly interface, interactive visualizations, and robust features, including real-time data monitoring and advanced analytics, showing you how Kibana revolutionizes your approach to navigating and analyzing complex datasets. Starting with the foundational steps of installing, configuring, and running Kibana, this book progresses systematically to explain the search and data visualization capabilities for data stored in the Elasticsearch cluster. You’ll then delve into the practical details of creating data views and optimizing spaces to better organize the analysis environment. As you advance, you'll get to grips with using the discover interface and learn how to build different types of extensive visualizations using Lens. By the end of this book, you’ll have a complete understanding of how Kibana works, helping you leverage its capabilities to build an analytics and visualization solution from scratch for your data-driven use case.
Table of Contents (17 chapters)
Free Chapter
Part 1: Exploring Kibana
Part 2: Visualizations in Kibana
Part 3: Analytics on a Dashboard
Part 4: Querying on Kibana and Advanced Concepts

Advanced Kibana concepts

Kibana has several implementations that are designed for very specific use case requirements, and runtime fields is one of them. Let’s explore and understand them.

Runtime fields

Forget static schemas; Elasticsearch runtime fields are your dynamic paintbrushes! They let you create fields on the fly, transforming your data on demand within your queries. Imagine a data sculptor, molding your documents with temporary fields based on your needs.

There’s no need to re-index or restructure your data. Runtime fields are calculated at query time, pulling information from existing fields or even combining them into new ones. Think of it as a temporary data transformation, enriching your documents without changing their core structure. These dynamic fields are versatile. You can extract specific values using Grok patterns, calculate aggregates such as averages or counts, or even perform complex calculations. They’re perfect for adding context...