300-640 aktueller Test, Test VCE-Dumps für Implementing Cisco Data Center AI Infrastructure

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Cisco 300-640 Exam Syllabus Topics:

Section	Objectives
Topic 1: Compute and Storage for AI Infrastructure	- Storage systems 1. Distributed storage concepts 2. High-throughput storage for AI training data - Compute architecture 1. HPC-style scaling considerations 2. GPU-based compute nodes
Topic 2: AI Infrastructure Deployment and Operations	- Deployment models 1. Hybrid AI infrastructure integration 2. On-premises AI clusters - Operations and lifecycle management 1. Monitoring and observability 2. Performance tuning and optimization
Topic 3: Security and Governance in AI Data Centers	- Infrastructure security 1. Secure access to AI workloads 2. Network segmentation and policy enforcement
Topic 4: Data Center AI Infrastructure Fundamentals	- AI/ML workload requirements in data centers 1. Compute, GPU, and acceleration concepts 2. Data pipeline and workload characteristics
Topic 5: Data Center Networking for AI Workloads	- Cisco Data Center networking technologies 1. Cisco Nexus platform concepts 2. Cisco ACI integration concepts - High-performance fabric design 1. Low-latency switching and routing considerations 2. Leaf-spine architecture in AI environments

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Cisco Implementing Cisco Data Center AI Infrastructure 300-640 Prüfungsfragen mit Lösungen (Q43-Q48):

43. Frage
A data center operator configures telemetry streaming on Cisco Nexus switches. What is the primary operational advantage over traditional SNMP polling?

A. Elimination of routing tables
B. Increased packet fragmentation
C. Mandatory hardware replacement
D. Real-time visibility with lower overhead

Antwort: D

Begründung:
Streaming telemetry continuously exports operational data in near real time, improving visibility and reducing polling overhead compared to SNMP. AI infrastructures require rapid monitoring of congestion and latency conditions. Telemetry does not remove routing tables or require hardware replacement.

44. Frage
An engineer made changes to the corporate DNS, which caused a Cisco UCS X-Series domain to lose connectivity to Intersight. To restore connectivity, the management interface DNS and NTP settings must be updated using the device console UI. Which configuration change must be made in Intersight to allow the updated DNS configuration to persist?

A. Edit the IMC access policy associated to the fabric interconnects.
B. Create a network connectivity policy and apply it to the blade chassis.
C. Edit the domain profile deployed to the fabric interconnect.
D. Create a device connector policy and apply it to the blade chassis.

Antwort: C

Begründung:
In Cisco Intersight Managed Mode, the fabric interconnect management DNS and NTP settings are controlled through the UCS domain profile. If the settings are changed locally from the device console UI, the deployed domain profile must also be updated in Intersight so the corrected configuration is not overwritten during the next policy deployment or compliance remediation.

45. Frage
A network engineer analyzes RoCEv2 traffic flows in an AI training cluster and notices that all RoCEv2 packets have the Don't Fragment bit set in the IP header. Why must RoCEv2 set the DF bit in all packets?

A. to prevent IP fragmentation that would break the InfiniBand sequence numbering and ordering guarantees
B. to enable Path MTU Discovery so that the optimal packet size can be negotiated
C. to ensure that packets always take the same path through ECMP routing for consistent latency
D. to indicate to intermediate switches that the packet contains RDMA traffic requiring special handling

Antwort: A

Begründung:
RoCEv2 carries InfiniBand transport semantics over UDP/IP, and IP fragmentation would disrupt the expected packet sequencing and ordering behavior required by RDMA. Setting the Don't Fragment bit prevents intermediate devices from fragmenting RoCEv2 packets, preserving reliable RDMA transport behavior across the AI training fabric.

46. Frage
What describes inference traffic patterns in AI deployments?

A. provides real-time decision making
B. simplifies complex neural network architectures
C. optimizes data storage solutions for data lakes
D. eliminates the need for data preparation

Antwort: A

Begründung:
Inference traffic is associated with using a trained model to generate predictions or responses from new input data. In AI deployments, this commonly supports real-time or near-real-time decision making, such as classification, recommendations, detection, or automated responses.

47. Frage
A data center is deploying an AI infrastructure for LLM training and model inference. This infrastructure requires high GPU density, low-latency interconnects, and the ability to scale compute resources. When considering the Cisco UCS C885A M8 Rack Server for the deployment, which design aspect is the most critical for achieving optimal performance and scalability in this environment?

A. configuring the server with the minimum amount of RAM to reduce initial costs
B. using the maximum number of CPU cores to support the virtualization overhead
C. selecting the appropriate Nexus Fabric and its configuration to minimize latency
D. implementing a redundant power supply configuration to ensure high availability

Antwort: C

Begründung:
For UCS C885A M8 servers running LLM training and inference workloads, the surrounding Nexus fabric design is critical because GPU-dense systems depend on low-latency, high- bandwidth, lossless network connectivity for scale-out performance. Selecting and configuring the correct Nexus fabric minimizes communication delays between compute nodes and enables the AI infrastructure to scale efficiently.

48. Frage
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