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Deploying and Scaling Logstashedit
The Elastic Stack is used for tons of use cases, from operational log and metrics analytics, to enterprise and application search. Making sure your data gets scalably, durably, and securely transported to Elasticsearch is extremely important, especially for mission critical environments.
The goal of this document is to highlight the most common architecture patterns for Logstash and how to effectively scale as your deployment grows. The focus will be around the operational log, metrics, and security analytics use cases because they tend to require larger scale deployments. The deploying and scaling recommendations provided here may vary based on your own requirements.
Getting Startededit
For first time users, if you simply want to tail a log file to grasp the power of the Elastic Stack, we recommend trying Filebeat Modules. Filebeat Modules enable you to quickly collect, parse, and index popular log types and view pre-built Kibana dashboards within minutes. Metricbeat Modules provide a similar experience, but with metrics data. In this context, Beats will ship data directly to Elasticsearch where Ingest Nodes will process and index your data.
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