A network team is configuring quality of service (QoS) for RoCEv2 traffic on a VXLAN fabric. The team must ensure that congestion notification packets (CNP) generated by storage targets are never dropped in the network, as these packets are critical for congestion control feedback.
How must CNP packets be handled in the QoS configuration to ensure reliable delivery?
Which result is provided through image recognition using AI?
A corporate network administrator manages a HyperFabric AI environment and wants to receive email notifications about assertions in the fabric. The administrator sets up a recipient email endpoint under the notification endpoints in the controller, but notifications are not received.
Which two configurations cause the issue? (Choose two.)
For email notifications in a HyperFabric AI environment to work properly, two critical configurations must be in place:
If either of these is missing, notifications will not be delivered despite the endpoint being configured.
A global enterprise is deploying a new AI-driven analytics platform that requires high-performance GPU acceleration, large memory capacity, and robust virtualization support. The current compute environment must co-exist with the newly purposed GPU-enabled workload. This environment will continue to grow, so the customer wants to scale out the resources as needed.
Which Cisco product meets the requirements?
Which components are part of the HyperFabric AI solution?
A national law firm is deploying a RAG solution for their legal research team to more efficiently use their 50 TB of confidential data and documents when preparing new contracts and briefs. They decided on a UCS X-Series chassis equipped with four GPUs and six X210c servers.
Which storage solution fits this deployment?
A company is building a network fabric for an AI training cluster that will train large language models. The cluster includes 256 GPUs distributed across 32 servers. Security requirements mandate isolation between different training projects and allowing shared access to a central storage system.
Which approach provides the required security isolation and maintains optimal performance for GPU-to-GPU communication?
A medium-sized breadmaking operation must deploy a fleet of GPU servers that meet these requirements for their flagship application: policy managed through cloud-based interface low latency between specific pairs of GPUs at least 2 GPUs per server all GPUs should be same model Intel CPU - well suited for Inferencing customer is power conscious
Which server meets the requirements?
When considering a rail-only network design, when would adding spine switches make sense?
An engineer is deploying a Cisco AI POD environment to support large-scale AI workloads. The solution must provide a software-defined storage platform with a Disaggregated Shared-Everything architecture, allow compute nodes to run on Cisco UCS C225 M8 servers managed through Cisco Intersight, and deliver exabyte-scale, all-flash performance with integrated high-speed RDMA and GPU Direct Storage capabilities.
Which solution meets the requirements?
