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Mastering Apache Cassandra 3.x

You're reading from   Mastering Apache Cassandra 3.x An expert guide to improving database scalability and availability without compromising performance

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Product type Paperback
Published in Oct 2018
Publisher Packt
ISBN-13 9781789131499
Length 348 pages
Edition 3rd Edition
Languages
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Authors (2):
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Aaron Ploetz Aaron Ploetz
Author Profile Icon Aaron Ploetz
Aaron Ploetz
Tejaswi Malepati Tejaswi Malepati
Author Profile Icon Tejaswi Malepati
Tejaswi Malepati
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Table of Contents (12) Chapters Close

Preface 1. Quick Start FREE CHAPTER 2. Cassandra Architecture 3. Effective CQL 4. Configuring a Cluster 5. Performance Tuning 6. Managing a Cluster 7. Monitoring 8. Application Development 9. Integration with Apache Spark 10. References 11. Other Books You May Enjoy

Log stack

During an issue, logging on to each node and checking its logs is tiresome. Instead, we can use a logging stack or a built, custom logging stack with tools available based on our use case. The following stack is a subset of the Elasticsearch, Logstash, Kibana (ELK) stack. We wouldn't require a complex aggregation of logs across nodes, so logstash can be eliminated and we can use a simple Filebeat for log-forwarding, Elasticsearch for storage and querying, and Kibana for visualization and filtering. Moreover, this entire stack can be integrated with any application stack and all the logs across stacks can be visualized on a centralized backend with a single frontend along with all open source community tools. This wouldn't require a license as this logging stack is more of a replacement for a proprietary log aggregator:

Figure 7.33: Log stack built with all...
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