Thus, ELK is a log management platform that works by enabling you to gather massive amounts of log data from anywhere across your infrastructure into a single place, then search, analyze and visualize it in real time. Beats is a family of lightweight data shippers that collect and send data from different machines and systems to the stack, in this case, to Logstash or Elasticsearch.Īlthough all four are independent projects run by Elastic, they were designed to complete each other into an end-to-end log analysis solution. Recently, however, a fourth project was added to the mix – Beats – which led to the stack being rebranded as the Elastic Stack. And finally, Kibana provides a user interface, allowing users to visualize, query, and analyze their data via graphs and charts. Logstash is a log aggregator that collects and processes data from multiple sources, converts, and ships it to various destinations, such as Elasticsearch. Elasticsearch is a full-text search and analytics engine. The ELK stack is an acronym used to describe a collection of three open-source projects – Elasticsearch, Logstash, and Kibana. Keep on reading and find out how the ELK works, why do you need it, and how you can leverage it to manage massive amounts of log data and extract valuable insights to improve your business operations. From what is the ELK stack to how to install and configure it, how to use it for analysis, use cases, and best practices. In this ELK stack tutorial, we answer that and more. But what is the Elastic stack and what makes it so good that millions of people prefer it over any other log management platform – even the historical leader Splunk? When it comes to log management and log management solutions, there is one name that always pops up – the Elastic Stack, formerly known as ELK Stack. ELK Stack Tutorial: A Guide to Using ELK for Log Management
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