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| Section | Objectives |
|---|---|
| HPC and High-Performance Infrastructure | - HPC Networking
|
| Operations, Security, and Troubleshooting | - Identity and Access Management
|
| Design and Implement HPE Private Cloud AI Solutions | - AI Infrastructure Integration
|
| Compute and Virtualization Solutions | - VMware and vSphere Integration
|
| Kubernetes and MLOps Platforms | - Kubernetes Infrastructure
|
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NEW QUESTION # 17
You are proposing HPE Private Cloud AI to a financial institution and want to demo the solution running a complex AI-enabled security application.
What can help you to accelerate the development of the demo?
Answer: B
Explanation:
B is correct. NVIDIA AI Blueprints are packaged reference workflows that combine models, NIM microservices, retrieval components, guardrails, and application logic for specific generative-AI use cases.
Selecting a suitable blueprint from the NVIDIA catalog can shorten a proof-of-concept cycle because the team starts from a validated architecture and deployable workflow instead of assembling every component from scratch. That is particularly useful when demonstrating a complex security-oriented AI application to a regulated customer.
Sample Kubeflow pipelines can accelerate individual machine-learning workflow steps, but they do not provide the same end-to-end application blueprint. NVIDIA Base Command Manager is an infrastructure and cluster-management product; it is not the development accelerator being asked for. HPE AI Essentials tutorials are useful instructional resources, but a blueprint is explicitly intended to speed implementation of a working use case.
Current Rev. 26.21 training has a dedicated module on using NVIDIA Blueprints and updates the recommended installation process for validated blueprints, reinforcing their role in demonstrations and PoCs.
References/topics: Advanced HPE Compute Solutions, Rev. 26.21, Module 6 "Using an NVIDIA Blueprint to demo an AI Chatbot"; NVIDIA AI Blueprints catalog and deployment documentation.
NEW QUESTION # 18
At the request of an HPE Private Cloud AI customer, you have added an AWS S3 object store to HPE AI Essentials. Several AI Users should be able to access that source when running notebooks and Spark Applications. Other users should have no access. What should you do?
Answer: D
Explanation:
HPE AI Essentials manages user access to data sources through the Identity & Access Management page; for object stores, the admin grants privileges under the Object Store Data tab.
This allows only selected AI Users to access the S3 source.
NEW QUESTION # 19
You are deploying several HPE ProLiant DL Gen12 servers to act as ESXi hosts.
How can you help to ensure the servers pass TPM attestation?
Answer: D
Explanation:
A is correct. VMware ESXi host TPM attestation depends on a trusted measured boot chain. Enabling UEFI Secure Boot helps establish that chain by allowing the platform to verify signed boot components and by aligning the host with VMware's secure-boot and TPM attestation requirements. With a supported TPM 2.0 configuration, vCenter can evaluate host attestation status and detect changes that compromise the expected boot measurements.
Encrypting self-encrypting drives is a storage-data protection control and does not determine whether the host passes TPM boot attestation. TAA compliance concerns procurement and manufacturing requirements, not the trusted boot state. The iLO Service Port provides a local management interface and has no role in establishing the ESXi TPM measurement chain.
The configuration must be treated as a platform-security dependency, not a post-installation checkbox. UEFI mode, Secure Boot, supported TPM settings, and compatible ESXi configuration should be established before hosts are placed into the production cluster.
References/topics: Advanced HPE Compute Solutions, Rev. 26.21, Module 8 "Designing HPE compute for VMware vSphere"; HPE ProLiant Gen12 security/UEFI documentation; VMware vSphere TPM and Secure Boot attestation guidance.
NEW QUESTION # 20
You are planning to demonstrate how you can use KServe to run NIMs on HPE Private Cloud AI. You have downloaded the CodeLlama-70B-Instruct model to a volume in your namespace named demo-model.
The objects that you are planning to deploy are shown below:
What change should you make to the objects?
Answer: B
Explanation:
D is correct after correcting the YAML location to spec.predictor.model.storageUri. The ServingRuntime describes the runtime container capable of serving the model; the InferenceService describes the particular model instance to deploy. Because the CodeLlama model files already reside on a persistent volume claim named demo-model, the InferenceService must tell KServe where those model artifacts are stored. A PVC URI is therefore supplied through the model's storageUri field, for example pvc://demo-model.
Option A is structurally wrong because modelFormat.name identifies the model format understood by the ServingRuntime; it is not a storage location. Option B incorrectly assigns model storage to the ServingRuntime specification. Option C changes the NIM cache directory inside the container but does not tell KServe to mount and initialize the requested model from the PVC. KServe's v1beta1 schema places storageUri alongside modelFormat and runtime under the predictor's model block.
This distinction is fundamental to reusable KServe design: a runtime can serve multiple compatible models, while each InferenceService supplies the model-specific location and deployment parameters.
References/topics: Advanced HPE Compute Solutions, Rev. 26.21, Module 5 "Other options for serving models on HPE Private Cloud AI"; HPE AI Essentials KServe documentation; KServe InferenceService v1beta1 schema.
NEW QUESTION # 21
A customer is concerned about counterfeit or tampered components entering their supply chain before servers reach their data center. Which HPE program directly addresses this concern?
Answer: D
Explanation:
HPE Trusted Supply Chain provides manufacturing and supply-chain security controls (including
U.S.-based secure manufacturing options and firmware provenance validation) to reduce the risk of tampering or counterfeit components before delivery. Pointnext Complete Care is a support/services offering, Factory Express provides factory-integration/configuration services (not specifically supply-chain security), and GreenLake for Private Cloud is a consumption/management platform.
NEW QUESTION # 22
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