Scaling local resources with hyperconverged infrastructure for video surveillance
One of the factors that limits the overall performance of any IP video surveillance solution is how effectively software can utilize hardware resources. Traditionally, an application such as video management software or access control requires a dedicated server, which typically does not use more than 20 percent of available hardware resources. This leads to an investment in hardware that won’t be utilized throughout the life of a deployment, and it also increases the total cost of ownership.
One method to scale local resources and use hardware more efficiently is to create a virtual resource pool by utilizing a hypervisor software. A virtual environment allows for multiple virtual machines, each of which represents its own server, to exist on one appliance. This introduces a variety of benefits to any deployment. By virtualizing, the exact amount of resources needed for an application can be properly allocated and distributed to the virtual appliance.
With each server being allocated the exact amount of compute, memory and storage resources, multiple rack units of space can be condensed into a single 1U or 2U server. Not only does this reduce the hardware footprint and the operational expenses of power and cooling, but it also better leverages the existing hardware.
BCDVideo’s Hyperconverged Infrastructure for Video Surveillance (HCI-VS) offers a highly available, easy-to-deploy and operate, purpose-built platform for video-optimized virtualization in the physical security space. HCI-VS enables integrators to successfully deploy various software including video management, access control, and building management, to name a few.
Each of these kinds of software would traditionally require its own appliance, but with a high-efficiency virtualized platform, HCI-VS enables all of these to be run within one single cluster, thereby drastically improving the usage of hardware, ensuring high availability, improving performance, and significantly lowering the total cost of ownership for any deployment.