FlexPod Solutions Target AI Challenges
NetApp and Cisco have introduced new FlexPod solutions aimed at improving security, scalability, and simplicity in AI infrastructure. This announcement was made on June 3rd 2026, in San Jose, California.
The newly launched solutions focus on addressing the unique challenges posed by AI workloads to compute, network, and storage systems. They offer enterprises a reliable pathway to enhance their AI capabilities effectively.
NetApp’s Chief Commercial Officer, Dallas Olson, said, “NetApp and Cisco’s longstanding partnership on FlexPod has already proven effective, saving customers up to 20 per cent of their time in infrastructure management and maintenance.”
Enhancing AI Infrastructure
The expanded FlexPod solutions are tailored for organisations of different sizes and maturity levels. They support enterprise AI deployments, including retrieval-augmented generation and semantic search, with integrated, end-to-end security features.
Jeremy Foster, General Manager and Senior Vice President at Cisco, noted, “Starting with security is essential. In collaboration with NetApp, Cisco aims to tackle AI-specific risks such as data exposure and governance gaps.”
FlexPod’s architecture incorporates disaggregated storage, which allows for independent scaling of performance and capacity. Future functionalities will include data discovery, preparation, and governance capabilities from the NetApp AI Data Engine.
These developments aim to facilitate AI adoption while minimising risk. Field trials and practical applications are expected to roll out in the coming months.
The collaboration between NetApp and Cisco integrates NVIDIA’s AI Data Platform reference design, providing a consistent foundation for AI deployments. This integration aims to maximise XPU utilisation and reduce job completion times.
Targeting full-stack enterprise AI use cases, the companies have worked with NVIDIA to build FlexPod Solutions based on NVIDIA Enterprise Reference Architectures. This enables organisations to design, deploy, and scale high-performance AI factories efficiently.
AI inferencing and RAG workflows are further streamlined by this simplified, pre-integrated solution. It lowers the cost, complexity, and specialised skill requirements for deploying AI infrastructure, making AI benefits more accessible to teams and departments.
Last updated: 4 June 2026, 1:48 pm
