Cisco is taking a collaborative approach to helping enterprise customers build AI-based infrastructures.
The vendor recently used its Partner Summit to talk about its AI infrastructure strategy and a variety of new partnerships and programs aimed at helping enterprises get their core infrastructure ready for AI workloads and applications.
“While AI is driving a lot of changes in technology, we believe that it should not require a wholesale rethink of customer data centre operations,” said Todd Brannon. senior director of cloud infrastructure marketing with Cisco’s Cloud Infrastructure and Software Group.
As AI projects move from actual science projects in some organisations backroom to mission-critical applications, enterprise infrastructure and operations teams are being challenged because they are dealing with new workloads running on familiar infrastructure but with new requirements, Brannon said.
“The idea is that we want to help our customers deploy and manage AI workloads efficiently, find that right mix of acceleration and not over provision or leave stranded resources or create new islands of operations,” added Sean McGee, cloud data centre technology strategist with Cisco.
One of the ways Cisco intends to help customers is by offering a suite of validated designs they can easily deploy as their enterprise AI needs to evolve.
The company recently announced four new Cisco Validated Designs for AI blueprints from Red Hat, NVIDIA, OpenAI, and Cloudera to focus on virtualised and containerised environments as well as converged and hyper-converged infrastructure options. Cisco already had other validated AI models on its menu from AMD, Intel, Nutanix, Flashstack and Flexpod.
The Validated Designs let customers use these models and inject their data into them to fit their needs and fine-tune what they want to do for their business needs, McGee said.
On top of these models, McGee said Cisco is building Ansible-based automation playbooks customers can use with Cisco’s Intersight cloud-based management and orchestration system to bring down the models and automatically inject their own data and build out repositories that can be used in their infrastructure be it at the edge of the network or in the data centre, McGee said.
Cisco’s Intersight package manages a variety of systems from Kubernetes containers to applications, servers, and hyperconverged environments from a single location.
“Utilising Intersight and our systems stack customers can deploy and manage AI validated workloads,” Brannon said. “The message is that we don't want our customers and partners having to completely rethink the operation side even though they're having to rethink some things on the GPU provisioning side for AI, for example,” Brannon said.
In addition, as Cisco gets feedback from our customers on AI-specific features or additional validated designs or things like that, it will augment Intersight with new features, Brannon said.
Also over time, these models will evolve as more data is used to tune them and customers can easily adjust them to fit the needs of their enterprise infrastructure, McGee said. “Our partners too can utilise these models to significantly expand their services because they really give them a head start and relieve a lot of the engineering expense and time that they need to put these services together for customers.”
Cisco recently unveiled Data Center Networking Blueprint for AI/ML Applications that defines how organisations can use existing data centre Ethernet networks to support AI workloads now.
A core component of the data centre AI blueprint is Cisco’s Nexus 9000 data centre switches, which support up to 25.6Tbps of bandwidth per ASIC and “have the hardware and software capabilities available today to provide the right latency, congestion management mechanisms, and telemetry to meet the requirements of AI/ML applications,” the vendor stated. “Coupled with tools such as Cisco Nexus Dashboard Insights for visibility and Nexus Dashboard Fabric Controller for automation, Cisco Nexus 9000 switches become ideal platforms to build a high-performance AI/ML network fabric,” Cisco stated.
Cisco has also published scripts so customers can automate specific settings across the network to set up this network fabric and simplify configurations, Cisco stated.
