Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Mastering Kibana 6.x

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

Arrow left icon
Product type Paperback
Published in Jul 2018
Publisher Packt
ISBN-13 9781788831031
Length 376 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
Anurag Srivastava Anurag Srivastava
Author Profile Icon Anurag Srivastava
Anurag Srivastava
Arrow right icon
View More author details
Toc

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

Data source functions


Kibana Timelion provides us with the option to load the data into the graph. We have already discussed one data source, function.es(), which loads data from Elasticsearch. Apart from .es(), Timelion also provides us with some more data sources from whuch we can load the data.

Some of them are World Bank and Quandl. We will now discuss the sources one by one.

Elasticsearch

The first data source is Elasticsearch and it is applied by default when we open the Timelion interface on Kibana. It is denoted with the .es() function and provides a lot of functionalities through which we can play around on the Elasticsearch index data.

The .es() function has different parameters, which we have already discussed such as split, which splits the series plot by the value of a specific field and the metric parameter to control the calculation of the y axis value. We can specify additional metrics aggregation, for example, avg, min, or max:

.es(metric='max:system.memory.used.bytes').label...
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image