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You're reading from  Learning ELK Stack

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Published inNov 2015
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ISBN-139781785887154
Edition1st Edition
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Author (1)
Saurabh Chhajed
Saurabh Chhajed
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Saurabh Chhajed

Saurabh Chhajed is a technologist with vast professional experience in building Enterprise applications that span across product and service industries. He has experience building some of the largest recommender engines using big data analytics and machine learning, and also enjoys acting as an evangelist for big data and NoSQL technologies. With his rich technical experience, Saurabh has helped some of the largest financial and industrial companies in USA build their large product suites and distributed applications from scratch. He shares his personal experiences with technology at http://saurzcode.in. Saurabh has also reviewed books by Packt Publishing, Apache Camel Essentials and Java EE 7 Development with NetBeans 8, in the past.
Read more about Saurabh Chhajed

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Visualizing with Kibana


Now that you have verified that your data is indexed successfully in Elasticsearch, we can go ahead and look at the Kibana interface to get some useful analytics from the data.

Running Kibana

As described in Chapter 1, Introduction to ELK Stack, we will start the Kibana service from the Kibana installation directory:

$ bin/kibana

Now, let's see Kibana up and running with a screen similar to the following screenshot on the browser with this URL:

http://localhost:5601

We can verify our index and fields in the Settings page under the indices tab as follows:

Kibana Settings page

It shows all our fields that were indexed, their data types, index status, and popularity value.

As we have already set up Kibana to take the logstash-* indexes by default, it starts to display the indexed data as a histogram of counts, and the associated data as fields in the JSON format as follows:

The Kibana Discover page showing indexed values

Searching on the Discover page

After our data is indexed...

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Learning ELK Stack
Published in: Nov 2015Publisher: ISBN-13: 9781785887154

Author (1)

author image
Saurabh Chhajed

Saurabh Chhajed is a technologist with vast professional experience in building Enterprise applications that span across product and service industries. He has experience building some of the largest recommender engines using big data analytics and machine learning, and also enjoys acting as an evangelist for big data and NoSQL technologies. With his rich technical experience, Saurabh has helped some of the largest financial and industrial companies in USA build their large product suites and distributed applications from scratch. He shares his personal experiences with technology at http://saurzcode.in. Saurabh has also reviewed books by Packt Publishing, Apache Camel Essentials and Java EE 7 Development with NetBeans 8, in the past.
Read more about Saurabh Chhajed