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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: HPE ProLiant Gen12 for AI | 20% | - AI-optimized compute design - Server architecture and components - GPU integration and configuration |
| Topic 2: AI Workshops and HPE AI Essentials Platform | 15% | - Customer engagement and assessment - Platform capabilities and deployment |
| Topic 3: HPE AI Essentials: Data Analytics and Data Science | 15% | - Analytics and machine learning tools - Data pipelines and processing |
| Topic 4: NVIDIA AI Enterprise and Model Serving | 10% | - Software deployment and management - Model serving architecture and optimization |
| Topic 5: Troubleshooting HPE Private Cloud AI | 10% | - Performance tuning and optimization - Issue diagnosis and resolution |
| Topic 6: High Performance Computing (HPC) Design and Management | 10% | - Management and monitoring - Architecture and scaling |
| Topic 7: Solution Optimization and Security | 5% | - Security best practices - Efficiency and resilience |
| Topic 8: Integration with Third-Party Platforms | 15% | - VMware integration - Red Hat OpenShift and Kubernetes integration |
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NEW QUESTION # 34
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: C
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 # 35
An organization running a mixed fleet of HPE ProLiant, Synergy, and Alletra storage systems wants predictive analytics and AI-driven recommendations to prevent infrastructure issues before they occur. Which HPE offering should be proposed?
Answer: B
Explanation:
HPE InfoSight provides AI-driven predictive analytics across compute and storage (extended from Nimble/Alletra into ProLiant and other infrastructure) to identify and often auto-resolve problems before they impact operations. OneView Global Dashboard aggregates OneView instances, Insight Remote Support automates support-case creation, and iLO Amplifier Pack is a firmware/health scanning tool for large ProLiant fleets.
NEW QUESTION # 36
An AI team is using Spark Applications to analyze and format data for AI fine-tuning. The team would like to automate running the applications in a series.
Which component of HPE AI Essentials can help?
Answer: D
Explanation:
B is correct. Airflow is the workflow-orchestration component in HPE AI Essentials. It is designed to define directed acyclic graphs (DAGs) whose tasks execute in a controlled sequence based on dependencies. If a team has several Spark applications that prepare, transform, and validate data before model fine-tuning, Airflow can schedule those applications as stages in a repeatable pipeline and coordinate retries, dependencies, and execution order.
Katib and Ray Tune are focused on hyperparameter optimization rather than general-purpose workflow orchestration. MLflow tracks experiments, runs, artifacts, and model lifecycle information; it is not the scheduler that executes an ordered series of Spark jobs. Airflow complements these components rather than replacing them.
The key exam distinction is between orchestration and execution engines. Spark performs distributed data processing. Airflow controls when the Spark applications run and how one stage depends on another. That separation permits the data-preparation pipeline to be automated without embedding orchestration logic inside each Spark application.
References/topics: Advanced HPE Compute Solutions, Rev. 26.21, Module 4 "Using Spark" and "Airflow"; HPE AI Essentials Software Airflow documentation.
NEW QUESTION # 37
An organization has an HPE Cray Storage Systems C500 solution. IT is interested in scripting management of these systems.
Which API can they use?
Answer: A
Explanation:
B is correct. HPE Cray Supercomputing Storage Systems C500 exposes management through the Redfish
/Swordfish REST API model. Redfish provides a standardized, HTTP-based management interface, and Swordfish extends the model for storage resources. This makes it suitable for scripted inventory, configuration, health, and lifecycle operations without requiring an administrator to automate an interactive management console.
HPE GreenLake is not the device-level scripting API for the C500. HPE OneView is a composable- infrastructure and server-management platform and is not the native C500 storage-management API. Slurm is a workload manager and scheduler for HPC jobs; it allocates compute resources and schedules work but does not replace the storage system's management API.
The spelling is also significant: the standard is "Redfish," not "RedFish." In an HPC environment, administrators commonly combine specialized tools rather than expecting one product to perform every management function. HPE Performance Cluster Manager or Slurm can participate in cluster operations, while the storage platform remains manageable through its supported Redfish/Swordfish interface.
References/topics: Advanced HPE Compute Solutions, Rev. 26.21, Modules 9 and 10, HPE Cray management and HPC storage; HPE Cray Supercomputing Storage Systems C500 Redfish/Swordfish REST API documentation.
NEW QUESTION # 38
You have imported a VMware vSphere ESXi cluster into HPE OneView for vCenter (0V4VC). You now want to grow the cluster, adding an HPE ProLiant DL server as a host. What is one requirement?
Answer: C
Explanation:
For OV4VC cluster growth/deployment, NIC0 in the server profile must be connected to a network that can reach the HPE OneView for VMware vCenter provisioning/deployment server.
NEW QUESTION # 39
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