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| Section | Weight | Objectives |
|---|---|---|
| Solution Design for Enterprise Workloads | 30% | - Scalability, availability and performance optimization - Design for AI, HPC and mission-critical workloads - Requirements analysis and environment assessment |
| Customer Success and Solution Optimization | 10% | - Solution demonstration and value justification - Troubleshooting and continuous improvement |
| Implementation and Lifecycle Management | 15% | - Upgrade, maintenance and monitoring - Deployment planning and validation |
| Integration with Data Center Infrastructure | 20% | - Networking and storage integration - HPE OneView management and automation - Security, compliance and data protection |
| HPE Compute Architecture and Technologies | 25% | - Compute component selection: processors, memory, storage, accelerators - Virtualization and container integration - HPE ProLiant, Apollo and Superdome Flex platforms |
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NEW QUESTION # 73
You are proposing 32 HPE Cray XD670 systems with HPE Performance Cluster Manager (HPCM) to a customer.
What is one benefit of HPCM that you should emphasize?
Answer: B
Explanation:
HPE Performance Cluster Manager provides bare-metal provisioning, image management, software updates, monitoring, and cluster health management for large HPC clusters. Scheduling is handled by tools such as Slurm, not HPCM.
Reference: https://www.hpe.com/us/en/collaterals/collateral.a00044858enw.html
NEW QUESTION # 74
You want to demonstrate HPE Private Cloud AI running a complex AI application, such as a video search app, to a customer.
What is one good resource for putting together this demonstration more quickly?
Answer: B
NEW QUESTION # 75
An automotive engineering team is running inference workloads for traffic simulation and computer vision models using KServe on HPE Private Cloud AI.
The team also uses GPU-enabled notebooks running on HPE Private Cloud AI to experiment with new models. They want to automatically adjust GPU usage for the different models based on current demand, as well as ensure that the notebooks never prevent the inferencing workloads from receiving the GPUs they need.
Which two features support this functionality? (Choose two.)
Answer: A,C
Explanation:
KServe autoscaling adjusts inference deployment capacity based on demand. HPE AI Essentials scheduler priorities ensure higher-priority inference workloads can get GPUs ahead of lower- priority notebook workloads.
Reference: https://kserve.github.io/website/docs/model-serving/predictive- inference/autoscaling/hpa-autoscaler
https://support.hpe.com/hpesc/public/docDisplay?docId=a00aie17hen_us&docLocale=en_US&pa ge=pcai%2FGenAI%2Fdeploying-knowledge-base.html
NEW QUESTION # 76
A global customer operates five HPE OneView appliances in different regions and asks for a single view of all managed resources.
What should you recommend?
Answer: D
Explanation:
HPE OneView Global Dashboard aggregates inventory, health, and alerts from multiple OneView appliances into a single searchable view, with drill-down launch into the individual appliance for management actions. OneView appliances cannot be clustered for this purpose.
NEW QUESTION # 77
A customer needs to mount an ISO image remotely and use full graphical remote console with multiple simultaneous administrators on ProLiant Gen11 servers.
What is required?
Answer: B
Explanation:
Integrated Remote Console with virtual media, shared/multi-user console, and directory integration require an iLO Advanced (or higher) license. iLO Standard provides basic health monitoring and text-based access only.
NEW QUESTION # 78
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