Highly Scalable Storage for Splunk Environments
With Qumulo and Splunk, you can search, explore, browse, navigate, analyze and visualize petabytes of data from one place.
Splunk storage, designed for massive data
QF2 by Qumulo was designed to address massive volumes of file data in a linear and predictable fashion. QF2 can be integrated with Splunk as a single volume data source to allow collections from a centralized mount point, or as the Splunk data store, providing the performance and capacity needed to address Splunk workloads.
QF2 provides built-in data analytics to provide detailed information on the efficiency and usage of the Splunk deployment.
Scales linearly
Splunk handles petabytes of data. With QF2, you simply add more nodes as your Splunk environment grows. Performance and capacity scale linearly. Use any mix of large and small files and store as many files as you need. There is no practical limit with QF2’s advanced file-system technology.
Uses a single namespace
A single namespace simplifies your Splunk environment. You set your Splunk home variable once and never change it again, even when you add more QF2 nodes.
Real-time analytics.
You get immediate insight into what’s happening in your Splunk environment, down to the file level. For instance, get up-to-date information on IOPS and the number of reads versus the number of writes.
See how it works!
See IOPS hot spots in a running cluster.
Why you Should be Managing Splunk Data, Not the Storage
In this webinar, you will learn how to understand your Splunk repository at the file level using real-time file system analytics and eliminate silos of storage using a single storage namespace for all Splunk data.
QF2 demo with 10.4 billion files
Watch a demo of QF2 running with over 10 billion files. You will see how the integrated analytics in QF2 provide instant, actionable information about your file system, even into the petabyte scale with billions of files.