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

Create a machine learning job


We have covered different types of jobs that we can create in X-Pack machine learning, so now we will create the jobs, execute them, and then see a result of the analysis.

Before starting job creation, we have to ensure the following system requirements for running machine learning jobs:

  • Elasticsearch 6.x for storing the index data on which we will perform the machine learning analysis
  • X-Pack 6.x to provide the machine learning capabilities for Elasticsearch as well as Kibana
  • Kibana 6.x to provide the UI for creating, executing, and obtaining the machine learning analysis results

I will show you the index pattern to be used. I am going to use the server-metrics index data in which we have the following data format:

        "_index" : "server-metrics",
        "_type" : "metric",
        "_id" : "258427",
        "_score" : 1.0,
        "_source" : {
          "@timestamp" : "2018-04-01T01:10:00",
          "accept" : 54709,
          "deny" : 4437,
          "host...