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| Section | Weight | Objectives |
|---|---|---|
| High Performance Computing (HPC) Design and Management | 10% | - Management and monitoring - Architecture and scaling |
| Troubleshooting HPE Private Cloud AI | 10% | - Issue diagnosis and resolution - Performance tuning and optimization |
| Integration with Third-Party Platforms | 15% | - VMware integration - Red Hat OpenShift and Kubernetes integration |
| HPE ProLiant Gen12 for AI | 20% | - Server architecture and components - AI-optimized compute design - GPU integration and configuration |
| AI Workshops and HPE AI Essentials Platform | 15% | - Platform capabilities and deployment - Customer engagement and assessment |
| NVIDIA AI Enterprise and Model Serving | 10% | - Software deployment and management - Model serving architecture and optimization |
| Solution Optimization and Security | 5% | - Efficiency and resilience - Security best practices |
| HPE AI Essentials: Data Analytics and Data Science | 15% | - Data pipelines and processing - Analytics and machine learning tools |
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NEW QUESTION # 57
A customer has fine-tuned a model and wants to find out whether the model is producing any toxic content.
Which NVIDIA microservice best meets this need?
Answer: B
Explanation:
D is correct. NVIDIA NeMo Evaluator is designed to measure model and application quality against defined evaluation criteria, including safety-related dimensions. Current NeMo evaluation tooling includes safety evaluations for harmful-content generation, toxicity, bias, hate speech, and related robustness concerns. A customer who has fine-tuned a model and wants to determine whether it produces toxic output needs an evaluation service rather than a data-preparation or runtime-policy component.
NeMo Customizer is used to adapt or fine-tune models. NeMo Curator prepares training data through curation, filtering, and deduplication. NeMo Guardrails is used to apply runtime controls to conversational AI applications, such as restricting unsafe topics or validating inputs and outputs. Guardrails can help prevent unacceptable responses in production, but the question asks which microservice is used to evaluate whether the fine-tuned model is producing toxic content.
A sound AI lifecycle therefore separates customization, evaluation, and enforcement: customize the model, evaluate its behavior, and then apply appropriate guardrails and deployment controls.
References/topics: Advanced HPE Compute Solutions, Rev. 26.21, Module 5 "NVIDIA NeMo deep dive"; NVIDIA NeMo Evaluator documentation, safety and security evaluation capabilities.
NEW QUESTION # 58
When designing high availability for an HPE OneView managed environment, what is the purpose of deploying OneView in a multi-appliance (HA) configuration?
Answer: D
Explanation:
HPE OneView HA (clustered appliances) protects the management plane itself, ensuring continued management, monitoring, and orchestration capability if one appliance instance becomes unavailable. It does not affect VLAN counts, compute capacity, or replace Synergy Composer, which is the management appliance specific to Synergy frames.
NEW QUESTION # 59
A customer's compliance team requires that all server firmware and drivers be baselined and rolled back if drift is detected. Which HPE OneView feature addresses this?
Answer: B
Explanation:
HPE OneView lets administrators assign a Service Pack for ProLiant (SPP) baseline to server profiles; OneView monitors for drift from that baseline and can remediate it. Server Profile Templates standardize configuration but the compliance/drift function specifically is the firmware baseline feature. Scopes/Permissions control access, and the Activity Feed is an audit log.
NEW QUESTION # 60
How do workloads running within HPE AI Essentials authenticate each other?
Answer: D
Explanation:
HPE AI Essentials uses service-mesh workload identity: workloads authenticate with SPIFFE/SPIRE-issued SVIDs, used through Istio proxies for secure service-to-service communication. It is not based on ingress-gateway certificates or static self-signed certificates.
NEW QUESTION # 61
A customer is running SUSE Rancher on HPE ProLiant DL servers and HPE Alletra arrays.
How should you install the HPE CSI Driver for Kubernetes?
Answer: B
Explanation:
C is correct after updating the terminology to the current SUSE Rancher interface: use Rancher Apps & Marketplace and the official Partner repository/catalog entry to install the HPE CSI Driver for Kubernetes.
HPE publishes the CSI integration so that Rancher administrators can deploy it through the native application- management workflow, which handles the Helm-based installation and ongoing configuration in a form consistent with Rancher operations.
Option A is technically possible in generic Kubernetes environments because HPE provides Helm deployment methods, but the scenario specifically asks how to install the driver in SUSE Rancher. The integrated Rancher catalog workflow is the preferred answer. Option B is incorrect because an Ansible playbook is not the standard driver installation path. Option D references a Data Ops Manager plug-in that is not required to deploy the CSI driver.
The original wording "SUSE Rancher Operators catalog" is outdated/inexact; current Rancher releases expose this through Apps & Marketplace/Partner repositories. The underlying concept remains the same: use the supported Rancher-integrated package rather than building a separate deployment mechanism.
References/topics: Advanced HPE Compute Solutions, Rev. 26.21, Module 8 "HPE integrations with third- party container platforms"; HPE Storage Container Orchestrator documentation, SUSE Rancher deployment of the HPE CSI Driver.
NEW QUESTION # 62
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