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| Section | Weight | Objectives |
|---|---|---|
| AI Infrastructure Deployment and Data Management | 30% | - Implement data management and lifecycle for AI workloads - Configure high-performance networks for AI: Cisco Nexus, NDFC, lossless fabrics - Deploy and manage AI infrastructure with orchestration tools - Integrate AI frameworks and applications with Cisco infrastructure - Configure compute and storage using Cisco UCS: profiles, policies, Intersight |
| AI Infrastructure Fundamentals | 20% | - Explain Cisco AI infrastructure solutions and portfolio - Describe AI use cases in data center environments - Describe AI and machine learning concepts - Describe types of AI infrastructure: on-premises, cloud, hybrid, edge - Describe core components of AI infrastructure: network, compute, storage, orchestration, monitoring |
| AI Infrastructure Operations and Troubleshooting | 20% | - Manage health, logs, and events - Optimize performance, security, and reliability - Implement performance benchmarking and validation - Troubleshoot network, compute, storage, and orchestration issues - Monitor infrastructure: Nexus Dashboard, Intersight, telemetry, alerts |
| AI Infrastructure Components and Architecture | 30% | - Evaluate hybrid and multi-cloud AI integration - Evaluate compute requirements: CPU, GPU, NVLink, virtualization, containerization, scalability - Evaluate network requirements for AI workloads: bandwidth, latency, congestion control, RoCEv2, QoS - Evaluate storage requirements: capacity, performance, data pipelines, distributed architectures - Evaluate power, cooling, and efficiency requirements |
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NEW QUESTION # 53
A network architect designs connectivity for a new Cisco AI POD operating in Intersight Managed Mode. To ensure high availability and aggregate bandwidth for external network traffic, a port channel must be established using multiple 100 GbE uplink ports on the fabric interconnects to connect to the upstream core switch infrastructure. Which specific policy, applied through the domain profile, must be modified to define and configure this port channel on the fabric interconnects for the desired uplink connectivity?
Answer: D
Explanation:
In Cisco Intersight Managed Mode, fabric interconnect port roles and uplink port channels are defined in the port policy associated with the UCS domain profile. Modifying the port policy allows the engineer to configure multiple 100 GbE uplink ports as a port channel for aggregated bandwidth and high availability toward the upstream network.
NEW QUESTION # 54
What does workload distribution offer in an AI infrastructure with local and external resources?
Answer: B
Explanation:
Workload distribution in AI infrastructure enables computational tasks to be spread across local and external resources, improving scalability, resource utilization, and execution flexibility across multiple processing locations.
NEW QUESTION # 55
Which function is provided through natural language processing?
Answer: D
Explanation:
Natural language processing enables systems to interpret, process, and transform human language from spoken or written inputs into structured data that applications can analyze, search, classify, or use for automation.
NEW QUESTION # 56
A data center administrator for a medium-sized manufacturing facility uses Intersight to perform unattended operating system installation on already discovered X-Series servers with server profiles assigned. Which set of prerequisites must be met for installing an operating system on a server in Cisco Mode?
Answer: A
Explanation:
In Cisco Intersight, unattended operating system installation requires the OS installation image and the operating system configuration file to be available in the software repository. These files allow Intersight to boot the installer and apply the required unattended installation parameters to the assigned server profile.
NEW QUESTION # 57
Which aspect of rapid provisioning supports a scalable workload execution in an AI infrastructure?
Answer: A
Explanation:
Rapid provisioning supports scalable AI workload execution by enabling computational platforms to be launched quickly and consistently as workload demand grows. This allows AI infrastructure to add or prepare compute resources efficiently for training, inference, or data-processing tasks.
NEW QUESTION # 58
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