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| Section | Objectives |
|---|---|
| Topic 1: Exam Objective | - Design and architect advanced HPE solutions across Edge-to-Cloud environments - Translate business requirements into complex, multi-site solutions - Consider all consumption models and hosting locations |
| Topic 2: Core Knowledge Areas | - Compute, storage, and networking solution design - HPE GreenLake and cloud service models - Edge-to-Cloud workloads integration and architecture - Scenario-based problem solving and application - Solution planning and positioning HPE products and services |
>> HPE7-V01 Sample Questions <<
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NEW QUESTION # 30
Your customer wants to implement a disaster recovery solution for their virtualization workload. They also want to implement a protection method that will protect the workload in case of a site failure.
Their existing environment includes the following configurations:
* All ESXi systems are located in the same datacenter
* Virtual machines are protected by an HA cluster
* Some of the VMs are protected with Fault Tolerance
* HPE Synergy 480 Gen11 is the compute platform
* HPE Alletra Storage MP B10000 array for storage
* Orchestrated failover for all VMs using VMware tools
The customer plans to replicate the same setup at the second site. The total number of virtual machines that must be protected is 200. Your customer also expects an RPO of 0.
Which component or configuration is a necessary part of a solution that will meet all customer requirements?
Answer: A
Explanation:
The correct answer is C. RPO 0 is the decisive requirement. A zero recovery point objective means the customer cannot lose acknowledged writes if a site fails. That requirement cannot be satisfied by asynchronous replication because asynchronous copy always introduces replication lag. The storage volumes backing the VMware datastores must be synchronously replicated between the two sites so that committed data exists at both locations before the write is considered protected. HPE Alletra Storage MP B10000 is designed for mission-critical block workloads and supports high-availability replication models, including synchronous Remote Copy / Peer Persistence designs for VMware environments. HPE documentation for Active Peer Persistence describes synchronous Remote Copy as the mechanism used for high-availability protection across arrays. Option A is incorrect because stretching or joining HPE Synergy frames across sites is not the mechanism that provides RPO 0.
Option B can help with VMware policy-driven placement, but SPBM alone does not replicate data.
Option D fails the RPO requirement. Reference/topics: DR architecture, RPO 0, synchronous replication, B10000 Remote Copy, VMware datastore protection.
NEW QUESTION # 31
Your customer is in the early stages of an AI project. They are requesting a POC demonstrating how they can utilize on-prem data with a limited amount of rack space, in an air-cooled environment.
Performance with the AI use case of Retrieval-Augmented Generation (RAG) will be the primary factor in their decision making.
Which HPE Compute offering would be suitable in this scenario?
Answer: A
Explanation:
The correct answer is C because the customer's requirement is for an early-stage AI proof of concept, on-prem data usage, limited rack space, and an air-cooled environment. HPE ProLiant DL320 Gen11 with NVIDIA L4 GPUs is a compact, rack-efficient platform suitable for AI inference and edge-style workloads. HPE describes the DL320 Gen11 as a compact 1U platform that can support up to four NVIDIA L4 Tensor Core GPUs, making it appropriate for space-constrained AI inferencing and near- real-time insight use cases. RAG workloads often need strong inference performance and local data access, but a POC does not automatically justify large-scale H200, GH200, or Cray-class infrastructure.
Options A and D are much larger, higher-power configurations suited to more demanding AI training or large-scale accelerated-compute requirements. Option B is also excessive for the stated limited-rack, air-cooled POC profile. The right design is not the most powerful system; it is the platform that matches the workload maturity, thermal limits, footprint, and business validation stage. Reference
/topics: AI workload sizing, RAG inferencing, HPE ProLiant DL320 Gen11, NVIDIA L4, POC platform selection.
NEW QUESTION # 32
A customer wants to extend on-premises Kubernetes clusters to burst workloads into a public cloud during peak demand while maintaining consistent policy and security controls. Which capability is most relevant?
Answer: C
Explanation:
HPE GreenLake for containers provides centralized, consistent Kubernetes cluster lifecycle management across on-premises, edge, and public cloud environments, enabling workload portability and unified policy enforcement for burst or hybrid scenarios.
NEW QUESTION # 33
During a technical discovery session, a customer states their primary concern is avoiding vendor lock-in for future storage expansion while still wanting a single support relationship. Which HPE positioning point is most relevant to address this concern?
Answer: D
Explanation:
HPE Alletra Storage MP's modular, disaggregated architecture is explicitly positioned to reduce long-term lock-in risk by supporting industry-standard connectivity/protocols and allowing independent scaling of compute and capacity nodes over time, all while HPE (via GreenLake and standard support contracts) remains the customer's single point of support and accountability.
NEW QUESTION # 34
Your customer is in the early stages of an AI project. They are requesting a POC demonstrating how they can utilize on-prem data with a limited amount of rack space, in an air-cooled environment.
Performance with the AI use case of Retrieval-Augmented Generation (RAG) will be the primary factor in their decision making.
Which HPE Compute offering would be suitable in this scenario?
Answer: B
Explanation:
The correct answer is B. The customer is not asking for the lowest-cost AI inference server; the scenario explicitly states that RAG performance is the primary decision factor, while also requiring limited rack space and air cooling. HPE ProLiant Compute DL384 Gen12 with NVIDIA GH200 NVL2 is the strongest fit because it is designed for high-performance enterprise AI and provides coherent CPU/GPU memory architecture with very high memory bandwidth, which is especially valuable for RAG and larger language-model workflows. HPE product information describes the DL384 Gen12 as a 2U air-cooled 19-inch rack server with NVIDIA GH200 NVL2, and HPE states that the platform provides outstanding coherent memory and memory bandwidth to run larger models faster and more cost-effectively.
NEW QUESTION # 35
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