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You are here: Home / Videos / MinIO as a Splunk SmartStore

MinIO as a Splunk SmartStore



Storage Field Day 19


This video is part of the appearance, “MinIO Presents at Storage Field Day 19“. It was recorded as part of Storage Field Day 19 at 14:00-16:00 on January 24, 2020.


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AB Periasamy, Founder and CEO, and Eco Willson, Support Lead, demonstrate MinIO as a Splunk SmartStore. MinIO can handle the performance and volume of data required to make Splunk a true enterprise IT operations data source.

The presentation outlines how Splunk recognized the rapid growth in log data and the limitation of traditional methods to handle this explosion in volume, particularly emphasizing the need to transition to a cloud-native architecture. This necessitated disaggregating storage and compute, allowing organizations to scale their infrastructures efficiently and respond to burgeoning storage needs.

The speakers highlight that Splunk evolved early on to address the disaggregation problem while others, such as MariaDB, are only now catching up. By leveraging MinIO as an object storage backend, Splunk can better accommodate the colossal amounts of data generated by enterprise IT operations. The presentation includes a demonstration showing how straightforward it is to configure Splunk to utilize MinIO. By adjusting a few lines in the Splunk configuration file, users can enable object storage, allowing Splunk to offload data to MinIO while maintaining operational efficiency with local cache management.

Additionally, the discussion on operational monitoring and automation reflects the priorities of modern DevOps teams. MinIO provides tools for system health monitoring and integrates seamlessly with Prometheus for alerting and dashboard visualization. However, the emphasis remains on automation, allowing DevOps professionals to set up rules for critical alerts rather than manually observing systems. By streamlining these processes, MinIO enables organizations to scale their Splunk environments effectively, supporting petabytes of data while maximizing performance and reliability.

Personnel: AB Periasamy, Eco Willson


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