Smart and modern video surveillance storage

Setting up a video surveillance system is no small feat. Organizations are adding cameras, moving toward higher resolution and keeping their assets longer. Now, a video surveillance system must be able to scale easily with the demands of an organization, who need more and more capacity to store the growing amount of security footage. That is why a smart, modern storage system is critical.

Download the Qumulo Storage for Video Surveillance data sheet

When we say data storage for video surveillance must be smart and modern, we mean a storage system must:

1. Be able to linearly scale both capacity and performance.
2. Provide actionable insights into how data is being used.

That isn’t too much to ask from a storage system, is it? And with those requirements met, organizations can begin to use their storage to scale their video surveillance systems. Let’s explore a few specific examples.

Measure the impact of adding cameras

One attribute of modern storage is its ability to give administrators actionable insights about their system. This doesn’t have to be used exclusively for data usage, however. When scaling video surveillance, check if your storage system has real-time analytics so you can truly see what is happening between the storage and the video management system (VMS).

With storage analytics, administrators can see the throughput increase each time they add a camera to a VMS server. This allows them to make the most of their investment by only adding additional servers when they truly need to. This also helps reduce the licensing cost of the video surveillance system so they can keep their storage systems properly tuned to ingest new video feeds.

Adding mixed resolutions on a single VMS server

Newer cameras mean higher frame rates and resolutions, which require more storage capacity. One approach is to simply add another VMS server for the higher resolution cameras, but that can lead to siloed management.

However, with a smart and modern storage system, it’s easy to incorporate new cameras with higher resolution. Just as we mentioned above, you can look at how much throughput each camera in the system requires. With that information, mixing different resolution cameras on a single VMS server is easy to manage because you can see the impact of adding newer cameras.

Using insights from storage data can also help organizations look at the longer-term effects of the new cameras over days, weeks and months. Administrators will be able to build an internal sizing calculator for each VMS server, based on the number of cameras of each resolution/frame rate.

Changing retention time requirements in video surveillance

Another challenge to scaling the storage for video surveillance is changing retention requirements for assets. In many cases, storage solutions are set up to keep assets for a certain period of time. But if you want to extend that period, there isn’t enough storage capacity to handle the extra data. Modern storage solves that problem with a better way for scalability. With a scale-out approach to storage, organizations can simply add additional capacity without any provisioning or migration of data.

The right storage for video surveillance

Storage is only one piece of video surveillance. But the right storage solution can make all the difference. Using a storage filesystem with a scale-out architecture allows organizations to easily account for the additional resources that come with growing surveillance. But for the most value from video surveillance, look for storage that has real-time analytics. With storage analytics, organizations can easily determine what impact any changes to the system will have. So when it is time to scale your video surveillance, you know you have the necessary infrastructure in place.

video surveillance storage solutions from Qumulo

Keith is building highly successful teams that architect and build universal-scale storage systems for media & entertainment, life sciences, oil & gas, high performance computing and general purpose workloads.

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