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Mastering Kibana 6.x

You're reading from   Mastering Kibana 6.x Visualize your Elastic Stack data with histograms, maps, charts, and graphs

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Product type Paperback
Published in Jul 2018
Publisher Packt
ISBN-13 9781788831031
Length 376 pages
Edition 1st Edition
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Author (1):
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Anurag Srivastava Anurag Srivastava
Author Profile Icon Anurag Srivastava
Anurag Srivastava
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Table of Contents (16) Chapters Close

Preface 1. Revising the ELK Stack FREE CHAPTER 2. Setting Up and Customizing the Kibana Dashboard 3. Exploring Your Data 4. Visualizing the Data 5. Dashboarding to Showcase Key Performance Indicators 6. Handling Time Series Data with Timelion 7. Interact with Your Data Using Dev Tools 8. Tweaking Your Configuration with Kibana Management 9. Understanding X-Pack Features 10. Machine Learning with Kibana 11. Create Super Cool Dashboard from a Web Application 12. Different Use Cases of Kibana 13. Creating Monitoring Dashboards Using Beats 14. Best Practices 15. Other Books You May Enjoy

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...
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