Data Center & Hybrid Cloud
Data Center and Cloud as One Connected Architecture.
Driven designs the network, compute, storage, virtualization, cloud connectivity, and automation that let workloads live where they make sense — including the infrastructure now being used for private and cloud AI inference.
3
HYPERSCALERS: AWS / AZURE / GCP
EVPN
STANDARDS-BASED FABRICS
IaC
AUTOMATION FROM DESIGN TO OPERATIONS
HYBRID
ON-PREM + CLOUD AS ONE ARCHITECTURE
Most enterprise workloads now span data center and cloud environments.
Cloud & data center, connected
Workloads Across Cloud & Data Center
A workload may sit on-premises today, move to public cloud tomorrow, call services in another cloud, and still depend on data or identity back in the data center. The architecture has to account for routing, segmentation, DNS, address space, performance, observability, security controls, and operations across all of it. AI adds another workload class, but the same fundamentals still apply: data location, accelerated compute, east-west traffic, storage throughput and private connectivity all have to be designed together.
Data Center Network Fabrics
Modern data centers need a network that can scale east-west traffic, support segmentation and move workloads without requiring a redesign every time the environment changes. Routed leaf-spine, VXLAN EVPN, controller-based fabrics, multi-tenancy, anycast gateway, route leaking, external connectivity, DCI and brownfield migration. Cisco Cloud Control/AI Canvas and Arista AVA add AI-assisted correlation to the operational layer; in AI fabrics, Arista CV UNO can add job-centric visibility into network behavior.
AI-Assisted Operations
AI-Ready Infrastructure & Operations
The data-center operating model is also changing. Cisco Cloud Control can combine Nexus and Intersight context in AI Canvas so agents and engineers investigate network and compute issues together. Arista AVA uses CloudVision and NetDL, for AI-assisted event correlation and troubleshooting. In public cloud, the same idea is appearing in infrastructure planning and operations — for example, Google exposes Gemini-assisted AI-cluster design guidance. We design telemetry, inventory, naming, policy and automation so these tools have trustworthy context to work with.
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