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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: AI Infrastructure Deployment and Data Management | 30% | - Integrate AI frameworks and applications with Cisco infrastructure - Configure compute and storage using Cisco UCS: profiles, policies, Intersight - Deploy and manage AI infrastructure with orchestration tools - Implement data management and lifecycle for AI workloads - Configure high-performance networks for AI: Cisco Nexus, NDFC, lossless fabrics |
| Topic 2: AI Infrastructure Fundamentals | 20% | - Describe AI use cases in data center environments - Describe AI and machine learning concepts - Explain Cisco AI infrastructure solutions and portfolio - Describe core components of AI infrastructure: network, compute, storage, orchestration, monitoring - Describe types of AI infrastructure: on-premises, cloud, hybrid, edge |
| Topic 3: AI Infrastructure Components and Architecture | 30% | - Evaluate power, cooling, and efficiency requirements - Evaluate hybrid and multi-cloud AI integration - Evaluate storage requirements: capacity, performance, data pipelines, distributed architectures - Evaluate network requirements for AI workloads: bandwidth, latency, congestion control, RoCEv2, QoS - Evaluate compute requirements: CPU, GPU, NVLink, virtualization, containerization, scalability |
| Topic 4: AI Infrastructure Operations and Troubleshooting | 20% | - Monitor infrastructure: Nexus Dashboard, Intersight, telemetry, alerts - Troubleshoot network, compute, storage, and orchestration issues - Implement performance benchmarking and validation - Optimize performance, security, and reliability - Manage health, logs, and events |
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NEW QUESTION # 72
A network engineer logs into Nexus Dashboard and sees an anomaly showing that a BGP peer connection has gone down. Next to the anomaly, a yellow bubble displays "Correlated." What does Nexus Dashboard indicate by "Correlated" in this case?
Answer: C
Explanation:
In Nexus Dashboard, a correlated anomaly means the displayed issue is associated with a higher-level root anomaly. The BGP peer-down event is being treated as a resulting or related symptom rather than the primary root cause, helping operators focus troubleshooting on the upstream issue first.
NEW QUESTION # 73
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?
Answer: A
Explanation:
VAST Data Universal Storage provides a software-defined, disaggregated shared-everything storage architecture designed for AI-scale workloads. It supports Cisco UCS-based deployments managed through Intersight and delivers high-performance all-flash storage with RDMA and GPU Direct Storage capabilities for large-scale AI training, fine-tuning, and inference environments.
NEW QUESTION # 74
An end customer plans to deploy an AI fabric in a new data center. Their engineers are more familiar with CLI-based networks and require the capability to automate standardized configuration templates and monitor flows for the fabric. Which data center automation tool meets the requirements?
Answer: D
Explanation:
Nexus Dashboard is the Cisco data center automation and operations platform used with Nexus fabrics. It supports standardized fabric configuration through automation templates and provides visibility features such as flow monitoring, making it the appropriate tool for engineers who need CLI-oriented data center fabric operations with automation and telemetry.
NEW QUESTION # 75
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 compute and GPU resources selected must provide direct GPU to GPU access leveraging NVLink technology.
Which set of products meets the requirements?
Answer: B
Explanation:
Cisco UCS C885A M8 with NVIDIA H200 GPUs is designed for high-performance AI workloads that require dense GPU acceleration, large memory capacity, and direct GPU-to-GPU communication through NVIDIA NVLink. This combination supports demanding analytics, training, and inference workloads where high-bandwidth GPU interconnect is required.
NEW QUESTION # 76
When considering a rail-only network design, when would adding spine switches make sense?
Answer: B
Explanation:
In a rail-only design, each scalable unit provides optimized east-west GPU communication within that unit. Spine switches are added when the design must scale beyond a single scalable unit and support traffic between multiple scalable units while preserving predictable performance for larger AI training environments.
NEW QUESTION # 77
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