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Monitoring Elasticsearch

Język publikacji: angielskim
Monitoring Elasticsearch Dan Noble, Pulkit Agrawal, Mahmoud Lababidi - okladka książki

Monitoring Elasticsearch Dan Noble, Pulkit Agrawal, Mahmoud Lababidi - okladka książki

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Bądź pierwszym, który oceni tę książkę
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180
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ElasticSearch is a distributed search server similar to Apache Solr with a focus on large datasets, a schema-less setup, and high availability. This schema-free architecture allows ElasticSearch to index and search unstructured content, making it perfectly suited for both small projects and large big data warehouses with petabytes of unstructured data.

This book is your toolkit to teach you how to keep your cluster in good health, and show you how to diagnose and treat unexpected issues along the way. You will start by getting introduced to ElasticSearch, and look at some common performance issues that pop up when using the system. You will then see how to install and configure ElasticSearch and the ElasticSearch monitoring plugins. Then, you will proceed to install and use the Marvel dashboard to monitor ElasticSearch. You will find out how to troubleshoot some of the common performance and reliability issues that come up when using ElasticSearch. Finally, you will analyze your cluster’s historical performance, and get to know how to get to the bottom of and recover from system failures.

This book will guide you through several monitoring tools, and utilizes real-world cases and dilemmas faced when using ElasticSearch, showing you how to solve them simply, quickly, and cleanly.

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O autorze książki

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.

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