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Learning ELK Stack

You're reading from   Learning ELK Stack Build mesmerizing visualizations, analytics, and logs from your data using Elasticsearch, Logstash, and Kibana

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Product type Paperback
Published in Nov 2015
Publisher
ISBN-13 9781785887154
Length 206 pages
Edition 1st Edition
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Author (1):
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Saurabh Chhajed Saurabh Chhajed
Author Profile Icon Saurabh Chhajed
Saurabh Chhajed
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System scalability


As the data in the application grows, it is essential that the log analytics system should scale well with the system. Also, there are times when your systems are under a heavy load, and you need your log analytics systems to analyze what is going on with the application. ELK Stack provides that capability where you can easily scale each component as per your needs. You can always add more Elasticsearch nodes (master nodes and data nodes) in the cluster. It is recommended that you have three master nodes (one primary and two backup) for large clusters. Also, load balancing or routing nodes can be added for high volume searches and indexing requirements. You can also get more Logstash and Redis instances, and add more than one Kibana instance too. A typical scaled architecture may look like this:

ELK Architecture with Cluster

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