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5 Ways to Avoid Video Challenges with Specialty Storage

  • 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.

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5 Ways to Avoid Video Challenges with Specialty Storage

  • 1 | 2 | 3 | 4 | 5 | 6 | 7
  • 5 Ways to Avoid Video Challenges with Specialty Storage-2

    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.

Video is everywhere. Mobile, analytics and the Internet of Things are driving exponential growth of video datasets. Business Insider reported that 35 billion video ads were viewed last December, representing year-over-year growth of over 100 percent.

Because video has the highest click-through rate of all digital ad formats, marketing departments are rushing to generate video sales calls to more than a billion smart devices. Video is also increasingly used for public safety, as concerns about security drive major growth in surveillance. In short, virtually every industry is seeing growth in video data to some degree.

This creates a big problem for data managers because video data storage challenges management in four ways:

  1. Performance requirements of video are not served well by traditional storage architectures
  2. Rapid video growth can overwhelm storage environments while resource utilization is masked by virtualization
  3. Use of traditional backup tools make data protection for video expensive and challenging
  4. The long-term value of video data means that this is not a temporary problem

According to Janae Lee, SVP of strategy at Quantum, high-value video data demands special treatment. Move this data to specialty storage that is architected to meet the unique demands of video, and you'll soon achieve five noticeable benefits.