The ask from the business
Cisco IT needed to build an AI cluster to support model training and inferencing for multiple teams across the business.
Challenge
Cisco product teams needed a way to run AI workloads that would be used to develop and test new AI capabilities in Cisco products. But, existing data center facilities weren’t built to power modern AI.
- Critical business need with tight timelines: Product teams were under pressure to deliver innovations to customers and needed the environment in 3 months.
- Extensive technical requirements: Needed to ensure security, reliability, and performance within the AI infrastructure.
- Hurdles to overcome: There were several challenges to figure out along the way related to power limitations, structured cabling limitations, and the location of data.
- Designing for the future: Needed to design to scale with the business, including automated operations.
- Building from scratch with a full data center refresh would take 18-24 months—we needed it done much faster.
Solution
Cisco IT designed an AI infrastructure with Cisco compute, best-in-class GPUs from NVIDIA, and Cisco networking. They built a front-end ethernet network and a backend lossless ethernet network — ensuring a reliable, high performing, scalable network.
Speed of deployment
The backend of the AI network fabric was deployed in under 3 hours and the entire AI infrastructure was designed and deployed in 3 months, 80% faster than the alternative rebuild.
Enhanced AI capabilities
The new infrastructure now supports more than 25 use cases across the business, with more added every week.
Future-proofed infrastructure
Cisco IT maximized agility to power any workload, traditional or AI, at massive scale, no matter where the data lives.
Hear from the team
Jon Woolwine, Technical Systems Engineering and Jag Kahlon, Principal IT Engineer, explain how this new infrastructure was launched in only 3 months and expanded to support dozens of use cases.
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