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Priya Panke


Lagging Behind Because of Logs? ELK Stack to the Rescue!

Posted on November 22, 2016 by Priya Panke | Comments(0)

One of the common mistakes done by most of the professionals is not using valuable data called ‘Logs’. Because of the quantity of logs generated, the chances of using them becomes very less. Logs are used only to debug in case of failure or issues, but it can be used for much more For Example: Monitor processes Finding the root cause of the issue being faced Analyze flow and performance of processes and many more The collections and analyzing of the log becomes extremely difficult because of the diversity generated. For example we have access logs, error logs, application logs etc. which are associated with an application or a server. In this blog, I will be demonstrating how to install and configure ELK Stack. ELK stands for: Elasticsearch, Logstash and Kibana. Before we begin, let’s have a quick overview of the overall architecture with their components, followed by the implementation procedure.   Architecture of ELK Stack:   ElasticSearch: It is an Indexing, Storage and Retrieval engine Powerful open-source full-text search library A Document is the unit of search and index Fast search against large volumes De-normalized document storage: Fast, direct access to the data Broadly distributed and highly scalable Logstash:

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