Splunk can acquire data that is sourced from programs, or manually uploaded files. A search head distributes search requests to indexers and merges the results for the user.An indexer stores and manages the data.A forwarder is an instance that sends data to an indexer or another forwarder.The Splunk ArchitectureĪ Splunk system consists of forwarders, indexers, and search heads. My experience is mainly with Splunk, but the approaches I cover in this post should be applicable to alternative solutions, such as the ELK stack. Disclaimer: I’m not at all a Splunk expert! That said, even with a rudimentary understanding I have found tremendous value in incorporating the use of Splunk into my daily workflow. I will cover how we can use it to search and interpret data, generate reports and dashboards, as well as pointing out features that have been very helpful for me as a developer. In this blog post I want to give an introduction to Splunk. A data platform could give insight into many aspects of a system, including: application performance, security, hardware monitoring, sales, user metrics, or reporting and audits. Since Splunk is intended to index massive amounts of machine data, it has a large scope of use cases. The idea of Splunk is to be a data platform that captures and indexes all this data so that it can be retrieved and interpreted in a meaningful way. Systems generate a lot of machine data from activity such as events and logs.
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