5 Ways to Avoid Video Challenges with Specialty Storage

Higher Performance with No 'Frame Drops'

Video has different characteristics and performance requirements from traditional corporate data.
A single video file is often a TB or more. In addition, collaborative video processing applications (e.g., postproduction) may or may not be IOPS- or bandwidth-centric, but they often require almost zero latency.

This combination of large files and latency sensitivity is a challenge for traditional storage architectures. Traditional storage arrays utilize intelligent memory caches to deliver performance; having written data to the cache, the application is freed to perform its next operation. However, these software-managed caches are not large or flexible enough to manage unpredictable video data streams.

Video files overflow storage caches, causing the array to pause while it pages data to and from the disk. Meanwhile, the latency-sensitive video application continues to send data. This results in "frame drop" – writes that are not serviced rapidly enough are "dropped" by the storage system – a performance problem that may, in some cases, cause data loss.

When video causes this data traffic jam, other transactional or productivity data that is better suited for this architecture isn't getting serviced either. Resources are being used, but nobody's getting good performance.

Segregating out large, latency-sensitive video data – and applying specialty storage that is engineered to match its needs – gives the applications better data access and performance.