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| Section | Weight | Objectives |
|---|---|---|
| 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 |
| Solution Design for Enterprise Workloads | 30% | - Scalability, availability and performance optimization - Requirements analysis and environment assessment - Design for AI, HPC and mission-critical workloads |
| HPE Compute Architecture and Technologies | 25% | - HPE ProLiant, Apollo and Superdome Flex platforms - Virtualization and container integration - Compute component selection: processors, memory, storage, accelerators |
1. A customer wants to deploy an AI-powered chatbot using HPE Private Cloud AI but needs help putting together all the components.
What should you recommend the customer use?
A) A Ray Serve deployment
B) An Airflow DAG
C) An NVIDIA AI blueprint
D) A Kubeflow pipeline
2. How does NVIDIA Spectrum-X address congestion?
A) It prevents congestion proactively by using ECMP to distribute traffic across multiple links.
B) It exclusively uses open standard technologies such as PFC and IP ECN to ensure compatibility for heterogeneous networks.
C) It allocates a dedicated buffer to each port to prevent traffic loss during congestion.
D) It uses flow metering based on information gathered from control packets to target congestion at the source.
3. You are setting up a demonstration of HPE Private Cloud AI. You will show how easy it is to deploy a NIM with HPE Machine Learning Inference Software. As part of the demonstration, you worked with a developer to create a simple web application that sends queries to this NIM.
What is one important thing to keep in mind about your plan?
A) You must set up a storageclass that references HPE GreenLake for File Storage in advance to ensure that the deployment proceeds correctly.
B) You will need to set up the application to include an API token, associated with the deployment, in the headers of requests.
C) You must establish a private NGC registry and collect its credentials to prepare for defining the source in HPE Machine Learning Inference Software.
D) You must develop an API that understands the application's queries and incorporates those in the NIM as a custom image.
4. A customer with 30 rack-mount ProLiant servers wants to view aggregated health status and perform group power operations without deploying any management software.
What should you recommend?
A) Agentless Management Service (AMS)
B) HPE Compute Ops Management Enhanced
C) iLO Federation
D) HPE OneView Standard
5. 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.)
A) Kyverno mutating admission policies
B) HPE AI Essentials scheduler priorities
C) Autoscaling for KServe
D) Canary roll outs for KServe
Solutions:
| Question # 1 Answer: C | Question # 2 Answer: D | Question # 3 Answer: B | Question # 4 Answer: C | Question # 5 Answer: B,C |
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