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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Integration with Third-Party Platforms | 15% | - Red Hat OpenShift and Kubernetes integration - VMware integration |
| Topic 2: AI Workshops and HPE AI Essentials Platform | 15% | - Platform capabilities and deployment - Customer engagement and assessment |
| Topic 3: High Performance Computing (HPC) Design and Management | 10% | - Architecture and scaling - Management and monitoring |
| Topic 4: NVIDIA AI Enterprise and Model Serving | 10% | - Model serving architecture and optimization - Software deployment and management |
| Topic 5: Troubleshooting HPE Private Cloud AI | 10% | - Performance tuning and optimization - Issue diagnosis and resolution |
| Topic 6: HPE AI Essentials: Data Analytics and Data Science | 15% | - Analytics and machine learning tools - Data pipelines and processing |
| Topic 7: Solution Optimization and Security | 5% | - Efficiency and resilience - Security best practices |
| Topic 8: HPE ProLiant Gen12 for AI | 20% | - Server architecture and components - AI-optimized compute design - GPU integration and configuration |
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NEW QUESTION # 54
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: A
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The original wording "SUSE Rancher Operators catalog" is outdated/inexact; current Rancher releases expose this through Apps & Marketplace/Partner repositories.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 # 55
What is one action that an HPE Private Cloud AI Administrator can perform from the Alerts view in HPE AI Essentials?
Answer: C
Explanation:
C is correct. The Alerts view in HPE AI Essentials is designed to move an administrator from a detected condition to the evidence needed for diagnosis. From an alert, the administrator can open the logs for the pod associated with that alert. That is materially different from taking a remediation action such as restarting a pod: the Alerts interface provides observability and troubleshooting context, while restart or recovery actions are performed through the appropriate Kubernetes or platform-management workflow. Alert forwarding is separately configured in the platform's observability settings rather than as a per-alert action, and HPE GreenLake does not provide an alert-correlation function from this local Alerts view.
This is an important operational distinction for the exam. HPE Private Cloud AI troubleshooting follows an evidence-first workflow: identify the alert, inspect the affected workload and its logs, and then determine the corrective action. Pod logs can expose image-pull failures, scheduling problems, resource exhaustion, application exceptions, or service communication errors without immediately changing system state.
References/topics: Advanced HPE Compute Solutions, Rev. 26.21, Module 7 "Troubleshooting HPE Private Cloud AI," especially alerts and solution-provided tools; HPE AI Essentials Software documentation,
"Viewing Alerts and Notifications."
NEW QUESTION # 56
Which HPE offering allows an integrator to model, size, and validate a proposed HPE compute and storage solution against a customer's workload requirements before purchase?
Answer: A
Explanation:
HPE Sizer tools let partners and integrators model workload requirements (compute, storage, networking) and generate validated bill-of-materials recommendations. HPE Power Advisor specifically estimates power/cooling requirements for a given configuration, SPOCK validates compatibility rather than sizing, and Smart Update Manager handles firmware/driver updates post-purchase.
NEW QUESTION # 57
An HPE Private Cloud AI customer has a model deployed with HPE Machine Learning Inference Software (MLIS). You have helped the customer further fine-tune that model. Now the customer would like to test the new model by directing 10% of traffic to it.
What should you do?
Answer: B
Explanation:
A is correct. HPE Machine Learning Inference Software supports canary rollout behavior for a deployment when a new model version is introduced. A canary allows the current production version and the candidate version to run concurrently while a defined percentage of inference traffic is directed to each. Setting the new version to 10% gives the customer a controlled production test while retaining 90% of traffic on the established version.
Option B invents a "Canal" routing service and unnecessarily creates a separate deployment. Option C confuses autoscaling with traffic splitting; autoscaling changes replica capacity, not the percentage of requests routed to different model versions. Option D also misstates the model: traffic distribution is part of the versioned canary rollout rather than an arbitrary routing rule between two independently configured model versions in the existing deployment.
The canary mechanism reduces change risk because model quality, latency, error rate, and resource consumption can be compared before full promotion. If the candidate is satisfactory, its traffic share can be increased; if not, the rollout can be stopped or rolled back.
References/topics: Advanced HPE Compute Solutions, Rev. 26.21, Module 5 "Serving models with HPE Machine Learning Inference Software"; HPE AI Essentials MLIS documentation, "Initiate Canary Rollout."
NEW QUESTION # 58
A customer has HPE Cray XD systems, an HPE Slingshot network that includes HPE Slingshot Fabric Manager, HPE Performance Cluster Manager (HPCM), HPE Slingshot AIOps Software, and SchedMD Slurm. Which tool provides heatmaps and interactive topologies that help you find trouble spots in the network performance?
Answer: C
Explanation:
HPE Slingshot AIOps provides network utilization heatmaps, topology views, and congestion/bottleneck analysis to help identify network performance trouble spots. Slingshot Fabric Manager manages the fabric, while HPCM and Slurm manage the cluster and jobs.
NEW QUESTION # 59
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