Cisco launches Cloud Control to unify infrastructure

Cisco introduced Cloud Control at its Cisco Live event as a single management platform that consolidates Catalyst Center, Meraki Dashboard, Nexus One and Cisco Security Cloud. The company says the platform gives administrators a unified interface to monitor, manage and orchestrate infrastructure as AI workloads grow.

Rob Lay, Cisco UK&I chief technology officer, explained the platform combines cross-domain telemetry, purpose-built models, trusted agents, a Cloud Control Studio and a Cisco AI Canvas. He said the aim is to reduce the need for administrators to switch between multiple consoles.

Cisco described Cloud Control as a foundation for what it calls AgenticOps, an operating model where automated agents and people work together. The platform includes an Agent Builder for creating custom agents that follow company policies and workflows and an App Builder for designing and publishing applications and workflows using natural language prompts.

Agent Builder can connect to more than 50 third-party platforms through native connectors or the Model Context Protocol (MCP). The App Builder uses elements based on OpenAI’s Codex to translate prompts into actions, according to Cisco. Trusted agents and purpose-built models are intended to support policy enforcement and reduce operational overhead from managing multiple consoles and scripts.

Lay highlighted network performance as a key requirement for agent-driven AI. He pointed to use cases that need continuous connections to GPU resources and sustained bandwidth and low latency across data centers, cloud services and network edges. He contrasted the sustained demands of always-on agents with the short traffic bursts common in earlier chatbot deployments and said networks must be planned and provisioned to meet steady, higher traffic levels.

The company linked Cloud Control to current customer efforts to refresh network hardware. Lay recounted discussions with customers operating switches for more than a decade and noted such equipment may not meet the throughput or latency demands of modern AI workloads. Cisco said customers are increasingly planning upgrades with a two- to three-year view of future network needs.

Cisco positioned Cloud Control as a response to customers managing a growing number of overlapping tools. The company highlighted use cases including connecting distributed data centers, linking to GPU resources for model training and inference, and coordinating agents across security, collaboration and network management domains. The rollout continues Cisco’s multi-year work to consolidate platform management and add AI-focused capabilities.