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You're reading from  Monitoring Elasticsearch

Product typeBook
Published inJul 2016
PublisherPackt
ISBN-139781784397807
Edition1st Edition
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Authors (3):
Dan Noble
Dan Noble
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Dan Noble

About the Author Dan is a software engineer with a passion for writing secure, clean, and articulate code. He enjoys working with a variety of programming languages and software frameworks, particularly Python, Elasticsearch, and frontend technologies. Dan currently works on geospatial web applications and data processing systems. Dan has been a user and advocate of Elasticsearch since 2011. He has given talks about Elasticsearch at various meetup groups, and is the author of the Python Elasticsearch client “rawes.” Dan was also a technical editor for the Elasticsearch Cookbook, Second Edition, by Alberto Paro (ISBN: 1783554835). Acknowledgements I would like to thank my beautiful wife, Julie, for putting up with me while I wrote this book. Thanks for supporting me every step of the way. I would also like to thank my friends and colleagues James Cubeta, Joe McMahon, and Mahmoud Lababidi, who shared their insight, time, and support. I would like to give a special thanks to Abe Usher – you have been an incredible mentor over the years. Finally, thanks to everyone at Packt Publishing for helping to make this book happen. A special thanks to Merint Mathew, Sonali Vernekar, Husain Kanchwala, and Amey Varangaonkar for your valuable and careful feedback.
Read more about Dan Noble

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Understanding the Marvel dashboard


This section covers how to use the Marvel dashboard to better understand the state of your cluster.

To make monitoring our cluster more interesting, we'll stream more Twitter data into it using the stream2es program, and run random queries against the index using a custom bash script described in this section.

See Chapter 3, Elasticsearch-head and Bigdesk for detailed instructions on how to install and use stream2es, but, for quick reference, start stream2es using the following command:

./stream2es twitter --target http://elasticsearch-node-01:9200/twitter/status

Next, we'll simulate user interactions by running random queries against the twitter index. Create a new bash script called run_queries.sh with the following content:

#!/bin/sh

# Path to dictionary file
DICTIONARY_PATH=/usr/share/dict/words
ELASTICSEARCH_URI=http://elasticsearch-node-01:9200/twitter

# Total dictionary words
TOTAL_WORDS=`wc -l $DICTIONARY_PATH | awk '{print $1}'`

while :
do
    ...
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Monitoring Elasticsearch
Published in: Jul 2016Publisher: PacktISBN-13: 9781784397807

Authors (3)

author image
Dan Noble

About the Author Dan is a software engineer with a passion for writing secure, clean, and articulate code. He enjoys working with a variety of programming languages and software frameworks, particularly Python, Elasticsearch, and frontend technologies. Dan currently works on geospatial web applications and data processing systems. Dan has been a user and advocate of Elasticsearch since 2011. He has given talks about Elasticsearch at various meetup groups, and is the author of the Python Elasticsearch client “rawes.” Dan was also a technical editor for the Elasticsearch Cookbook, Second Edition, by Alberto Paro (ISBN: 1783554835). Acknowledgements I would like to thank my beautiful wife, Julie, for putting up with me while I wrote this book. Thanks for supporting me every step of the way. I would also like to thank my friends and colleagues James Cubeta, Joe McMahon, and Mahmoud Lababidi, who shared their insight, time, and support. I would like to give a special thanks to Abe Usher – you have been an incredible mentor over the years. Finally, thanks to everyone at Packt Publishing for helping to make this book happen. A special thanks to Merint Mathew, Sonali Vernekar, Husain Kanchwala, and Amey Varangaonkar for your valuable and careful feedback.
Read more about Dan Noble