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Customer Name: Cisco
Location: San Jose, CA
Number of Employees: 79,500
● Deploy a completely new cloud service infrastructure
● Ensure high performance and reliability for calling, meetings, and messaging
● Simplify management of globally distributed infrastructure
● Established foundational platform for cloud-delivered unified communications
● Significantly reduced storage costs via hyperconverged infrastructure
● Improved infrastructure flexibility, scalability, and manageability
With customers wanting greater choice and flexibility for technology consumption and orchestration, Cisco sought to extend its unified communications portfolio and make it available from the cloud.
“A lot of customers don’t want to purchase and maintain servers for calling and collaboration,” says Andrew Brugh, systems architect at Cisco. “They’d rather save some time and rack space by adopting a fully hosted, cloud-delivered service.”
Before Dedicated Instance for Webex Calling could be made widely available, however, Cisco needed to determine the platform on which the new service would be hosted.
“We had a lot of requirements,” explains James Arias, product manager at Cisco. “We wanted a platform that could be deployed globally and managed centrally. It needed to be space- and cost-efficient. And it had to have sufficiently high performance and resiliency to support voice and video, which tend to be more sensitive than other workloads.”
After evaluating a number of blade and rackmount server options, the team selected Cisco HyperFlex.
“Most of the options we considered require third-party storage, which takes up a lot of space, demands additional power and cooling, and increases both technical and operational complexity,” Brugh says. “Because it has shared storage, HyperFlex eliminated those concerns.”
It also provides a level of performance the team wasn’t expecting.
“We did a bunch of testing and validation, and HyperFlex performed very, very well,” Arias says. “The innovation that’s been built into the platform and the operational integrity it provides were immediately apparent.”
According to Brugh and Arias, Cisco HyperFlex offers a number of advantages in addition to exceptional performance. The platform provides tight alignment with the company’s Cisco ACI network, which can be segmented for specific workloads and customers. Cisco HyperFlex clusters can be stretched across multiple sites for full redundancy and seamless failover. And the globally distributed environment can be managed centrally using Cisco Intersight.
“We apply driver and firmware updates to all of the components collectively,” Brugh says. “Pressing a button on Intersight is way faster than managing and updating each node individually.”
Cisco can also right-size each cluster—and associated costs—based on the workloads they’re running. And as the service grows, they can scale CPU, hard drives, storage, and memory independently.
“HyperFlex gives us a bunch of what I call ‘flex knobs,’” Brugh notes. “We were able to start small with a minimal loadout and expand over time instead of overprovisioning and wasting budget in the initial stages of rollout.”
“Unified communications workloads don’t use a lot of storage, but they require a ton of CPU and RAM,” Arias adds. “The other solutions we considered would have required separate arrays with an excessive amount of storage. With HyperFlex, we are scaling memory and CPU as needed and saving a ton of money on storage.”
Dedicated Instance for Webex Calling is now available around the world, thanks to 21 active/active Cisco HyperFlex clusters in seven countries.
“Choosing a foundational platform for a global cloud service is anything but trivial,” Brugh says. “Based on a number of factors—including performance, reliability, scalability, operational simplicity, and cost—HyperFlex was clearly the best decision.”
“Unified communications workloads don’t use a lot of storage, but they require a ton of CPU and RAM. The other solutions we considered would have required separate arrays with an excessive amount of storage. With HyperFlex, we are scaling memory and CPU as needed and saving a ton of money on storage.”
Product Manager, Cisco