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| Section | Weight | Objectives |
|---|---|---|
| Solution Design for Enterprise Workloads | 30% | - Requirements analysis and environment assessment - Scalability, availability and performance optimization - Design for AI, HPC and mission-critical workloads |
| Implementation and Lifecycle Management | 15% | - Deployment planning and validation - Upgrade, maintenance and monitoring |
| Integration with Data Center Infrastructure | 20% | - Networking and storage integration - Security, compliance and data protection - HPE OneView management and automation |
| HPE Compute Architecture and Technologies | 25% | - HPE ProLiant, Apollo and Superdome Flex platforms - Virtualization and container integration - Compute component selection: processors, memory, storage, accelerators |
| Customer Success and Solution Optimization | 10% | - Solution demonstration and value justification - Troubleshooting and continuous improvement |
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NEW QUESTION # 17
What is a benefit of the storage component of HPE Private Cloud AI (small, medium, and large configurations)?
Answer: D
Explanation:
Small, medium, and large HPE Private Cloud AI configurations use GreenLake for File with Object Storage / Alletra X10000 File and Object Storage, not local node drives. This provides shared, high-performance AI storage for the platform.
Reference: https://www.hpe.com/us/en/collaterals/collateral.a50009216enw.html
NEW QUESTION # 18
A customer runs a transactional database with a write-intensive I/O profile on twelve SAS SSDs attached to an HPE MR controller and requires fault tolerance with minimal write penalty.
Which RAID level should you recommend?
Answer: B
Explanation:
RAID 10 mirrors and stripes, incurring a write penalty of 2 compared with 4 for RAID 5 and 6 for RAID 6. For write-heavy transactional workloads where usable capacity is secondary to write performance, RAID 10 is the appropriate choice.
NEW QUESTION # 19
You are demonstrating HPE Private Cloud AI. The customer asks how the system handles multiple users running concurrent workloads with different priorities.
Which feature would you highlight to explain how this is managed?
Answer: C
Explanation:
The HPE AI Essentials scheduler plug-in manages GPU/resource allocation for concurrent workloads and supports workload priority handling, which is the feature relevant to multiple users competing for shared AI resources.
NEW QUESTION # 20
Company TXXX is working on autonomous vehicle simulation and needs a system optimized for high-throughput training of generative AI models. The customer already uses HPE iLO to manage other servers and would like to continue with that option.
Which HPE server model aligns with these goals?
Answer: C
Explanation:
The HPE ProLiant Compute XD685 is optimized for high-throughput AI/model training workloads and uses HPE iLO management, matching the customer's need to continue managing systems through iLO.
NEW QUESTION # 21
A customer runs latency-sensitive network functions in virtual machines and reports that the hypervisor virtual switch adds unacceptable overhead.
What should you recommend?
Answer: C
Explanation:
SR-IOV allows a physical adapter to present virtual functions that are passed directly to guest VMs, bypassing the hypervisor networking stack and reducing latency and CPU overhead. Note that SR-IOV can restrict features such as live migration in some configurations.
NEW QUESTION # 22
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