Book Image

Mastering Kibana 6.x

Book Image

Mastering Kibana 6.x

Overview of this book

Kibana is one of the popular tools among data enthusiasts for slicing and dicing large datasets and uncovering Business Intelligence (BI) with the help of its rich and powerful visualizations. To begin with, Mastering Kibana 6.x quickly introduces you to the features of Kibana 6.x, before teaching you how to create smart dashboards in no time. You will explore metric analytics and graph exploration, followed by understanding how to quickly customize Kibana dashboards. In addition to this, you will learn advanced analytics such as maps, hits, and list analytics. All this will help you enhance your skills in running and comparing multiple queries and filters, influencing your data visualization skills at scale. With Kibana’s Timelion feature, you can analyze time series data with histograms and stats analytics. By the end of this book, you will have created a speedy machine learning job using X-Pack capabilities.
Table of Contents (21 chapters)
Title Page
Copyright and Credits
Packt Upsell
Contributors
Preface
Index

Chapter 14. Best Practices

In this chapter, we will cover best practices for Elastic Stack. These practices are very important to optimize Elastic Stack performance and to avoid security threats. Elastic Stack best practices are there to ensure that we follow the proper ways for data handling in Logstash, Elasticsearch, and Kibana. There are different aspects where we need to ensure best practices, such as avoiding large documents and unrelated data in the same index and returning large result sets.

We will cover different aspects of, and best practices for, Kibana, Elasticsearch, and Logstash. In this chapter, we will cover why a test environment is required for our Elastic Stack setup, why we should pick the right time filter field, and why we should avoid indexing large documents. After that, we will discuss sparsity and different ways to avoid it, such as normalizing the document, avoiding unrelated data in the same index, and avoiding different document types in an index.