As cloud-based solutions continue to proliferate, it’s clear that the virtualized video revolution has already begun.
How much of your video infrastructure still relies on dedicated appliances? Today, a growing number of pay TV providers are taking a different approach. By virtualizing key functions – transcoding, content management, content delivery network (CDN), and others – they can cut their video delivery costs by up to 33 percent, according to Cisco forecasts.
Can you really cut a third of your costs through virtualization? Absolutely. Here’s how.
1. Scale with demand
For the first source of savings, consider how video networks are designed today. Not only are the custom appliances used for each video processing function expensive individually; you have to deploy enough of them to handle peak usage. That means, for example, building out a dedicated video on demand (VoD) infrastructure to handle peak Friday night viewing times, even if most of those resources sit idle the rest of the week.
When you virtualize the VoD platform and associated video functions, your need for custom hardware disappears. You can use a shared pool of compute and storage resources and dynamically reallocate resources according to demand. Need more transcoding? Spin up more resources from the shared pool. Want to burst VoD resources on Friday nights, and then reallocate them to other applications the rest of the week? No problem. In effect, you’re replacing expensive and under-utilized custom appliances with a smaller hardware footprint that does the same things more efficiently.
2. Lower operating costs
Operational expenses play a big role in that 33 percent saving. After all, when you’re using custom appliances for diverse video processing functions, you need a data center to house them. Multiple dedicated infrastructures built for peak transcoding, content management systems (CMS), and other functions take up a lot of square footage. They require a lot of cooling. They consume an enormous amount of power.
By virtualizing those functions and delivering them from a smaller footprint, you eliminate a huge amount of redundancy and unused capacity. Your video cloud can now accommodate the same scale from a facility a fraction of the size, which costs much less to maintain.
3. Optimize architecture
Virtualization also allows for a more distributed video architecture, which lowers the overall cost of your network. When CDN, transcoding, and more are virtualized functions running on standard x86 platforms, you can easily distribute them out into the network. So you’re reducing core and edge bandwidth even as you’re lowering costs in your video data center/cloud. You can also push gateway, caching and video optimization functions closer to subscribers, reducing traffic in access networks.
Add it all up, and it equals major capital and operational savings, lower long-term access investments and lower total cost of ownership (TCO) [see Figure 1].
We’re just getting started
It’s worth remembering that the 33 percent savings projection only addresses the first stages of the virtualized video revolution. Within the next few years, you can also expect substantially lower software licensing costs as video providers shift from proprietary virtualization frameworks to open-source solutions, like OpenStack.
Many pay TV providers are also now looking at hosted cloud solutions – whether private or public – for their virtualized resources. These offer even more flexibility to scale with demand, and often better economics than building out capacity in house. Even more importantly, they reduce time-to-market because you can deploy, test and scale new video services much faster.
Plug in your own parameters in our Monetization and Optimization Index and create a customized model of what virtualization can mean for your video infrastructure.
For more examples of how other providers are using virtualization to lower costs and optimize video infrastructures, visit www.cisco.com/go/v2p.