HPE Private Cloud AI Solutions: HPE2-B08 Exam

"HPE Private Cloud AI Solutions", also known as HPE2-B08 exam, is a HP Certification. With the complete collection of questions and answers, PrepPDF has assembled to take you through 87 Q&As to your HPE2-B08 Exam preparation. In the HPE2-B08 exam resources, you will cover every field and category in Hybrid Cloud Certification helping to ready you for your successful HP Certification.

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  • Exam Code: HPE2-B08
  • Exam Name: HPE Private Cloud AI Solutions
  • Certification Provider: HP
  • Corresponding Certification: Hybrid Cloud
  • Updated: Aug 28, 2026
  • No. of Questions: 87 Questions & Answers with Testing Engine
  • Download Limit: Unlimited

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HP HPE2-B08 Exam Syllabus Topics:

SectionObjectives
Deployment and Operations- Monitoring and optimization
- Lifecycle management of AI infrastructure
- Deployment models for AI solutions
Data Management and Governance- Data lifecycle management
- Data governance and compliance
HPE Private Cloud AI Fundamentals- Overview of private cloud AI concepts
- Core AI workload characteristics
AI Infrastructure Design- Storage and data pipeline design
- Networking for AI workloads
- Compute and GPU considerations
HPE GreenLake for AI Solutions- GreenLake architecture and services
- Consumption-based IT model for AI
Security in Private Cloud AI- Identity and access management
- Workload and data protection

HPE Private Cloud AI Solutions Sample Questions:

Question 1

An architect is presenting to a customer who is an 'Early AI User'. The customer is unsure about the differences between their two main project ideas.
Project 1: Create an internal chatbot that can answer HR policy questions by accessing the live employee handbook stored on a shared drive.
Project 2: Teach a general-purpose chatbot to adopt the company's formal communication style and tone for drafting official press releases.
How should the architect categorize the primary AI task for each project? (Choose 2.)

A. Project 2 is a classic inferencing workload with no model customization.
B. Project 1 is a model training workload.
C. Project 1 is a RAG (Retrieval-Augmented Generation) workload.
D. Project 2 is a fine-tuning workload.


Question 2

A data analytics team is running workloads on an HPE Private Cloud AI solution. They observe that a data ingestion job is not meeting performance expectations, suspecting a CPU bottleneck. They believe the application is not correctly leveraging GPUDirect Storage (GDS), forcing data to be copied through the server's main memory before reaching the GPU.
Which are valid reasons why GDS might not be functioning correctly? (Choose 3.)

A. The NVIDIA peer memory driver has not been installed on the guest VM.
B. The NVIDIA GPUs have been configured with Multi-Instance GPU (MIG), which enhances GDS performance.
C. The application is using a standard TCP/IP socket for data transfer instead of an RDMA-based library.
D. The HPE GreenLake for File Storage array is using SATA SSDs instead of NVMe SSDs.
E. The network switches are not configured for lossless operation (e.g., PFC is disabled).


Question 3

A customer's distributed AI training job is experiencing poor performance. An analysis reveals high network latency. The architect suspects a misconfiguration in the NVIDIA Spectrum switches that form the RoCE-based AI fabric.
They review the following configuration snippet from one of the switch ports connected to a compute node:
```
interface ethernet 1/1
description "Connection to PCAI-Node-1"
speed 200G
mtu 9216
switchport mode trunk
## Priority Flow Control (PFC) is disabled on this port
```
What is the most likely cause of the performance issue?

A. Priority Flow Control (PFC) is disabled, which is mandatory for a lossless RoCE fabric.
B. The MTU size is too small for AI workloads.
C. The port is incorrectly configured in trunk mode instead of access mode.
D. The port speed is not sufficient for the connected H100 GPU.


Question 4

A retail customer wants to implement an AI-powered recommender system to personalize product suggestions on their e-commerce website. They are an 'Early AI user' and need a full-stack solution that simplifies deployment and management.
Which HPE AI solution is most appropriate for this use case?

A. AI-optimized HPE ProLiant DL servers deployed individually
B. HPE Cray systems
C. HPE AI Services - Transformation Workshop
D. HPE Private Cloud AI with NVIDIA


Question 5

Match the stakeholder in an AI project to their most likely primary concern.
Stakeholders:
1. Data Scientist
2. AI Decision Maker (CIO)
3. Data Engineer
Concerns:
a. "How can I easily build, manage, and automate data pipelines to feed our models?" b. "What is the total cost of ownership (TCO) and return on investment (ROI) for this AI initiative?" c. "Which hyperparameter tuning method will give my model the highest accuracy?"

A. 1-b, 2-a, 3-c
B. 1-c, 2-a, 3-b
C. 1-a, 2-c, 3-b
D. 1-c, 2-b, 3-a


Solutions:

Question 1
Answer: C,D
Question 2
Answer: A,C,E
Question 3
Answer: A
Question 4
Answer: D
Question 5
Answer: D

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