Cyxtera compute-as-a-service ‘speeds up AI innovation cycle’

Data centre colocation and interconnection specialist Cyxtera has introduced its Artificial Intelligence/Machine Learning (AI/ML) compute-as-a-service offering.


Based on the NVIDIA DGX A100 system, the new service aims to provide enterprises with greater agility and faster deployment with a flexible OpEx model.


Cyxtera has said the solution combines the simplicity and ease of the cloud with the deterministic performance of dedicated infrastructure, leveraging its data centre services exchange. Customers, it added, will also have direct access to an ecosystem of service providers and technology solutions, including storage-as-a-service (StaaS), interconnectivity, and security, among other managed services.


“Launching our DGX-based AI/ML compute as a service offering reinforces our continued focus on providing enterprise customers with a rich variety of leading-edge infrastructure options across our global footprint,” said Russell Cozart, Senior Vice President of Marketing and Product Strategy for Cyxtera. “As a certified NVIDIA DGX-Ready Program partner, we’re offering accelerated solutions ideally suited to our enterprise customer base.”


Enterprises will be able to provision NVIDIA DGX A100 systems via Cyxtera’s service exchange, providing the security and control provided by single tenant, dedicated infrastructure combined with the flexibility and agility of cloud. The NVIDIA DGX A100 offering also allows managed service providers to focus on service delivery by eliminating large, upfront capital investments in data center infrastructure while providing access to customers via the Cyxtera exchange.


“Many organizations want to speed up their AI innovation cycle, but lack the infrastructure to support it,” said Charlie Boyle, Vice President, General Manager of DGX Systems at NVIDIA. “Cyxtera’s AI/ML compute-as-a-service offering makes it easy to leverage the performance, flexibility and efficiency of DGX A100 in a cost-effective model, enabling more businesses to succeed in the race to deploy AI.”


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