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| Section | Objectives |
|---|---|
| Topic 1: HPE Compute Architecture and Solutions | - HPE ProLiant server families overview - Compute solution positioning and use cases |
| Topic 2: Server Deployment and Configuration | - Firmware and system configuration tools (iLO, SPP) - Initial setup and provisioning |
| Topic 3: Troubleshooting and Support | - Hardware and firmware troubleshooting - Performance monitoring and diagnostics |
| Topic 4: Storage and Networking Integration | - Networking configuration and connectivity options - SAN and direct-attached storage integration |
| Topic 5: Solution Design and Implementation | - High availability and redundancy design - Workload sizing and architecture planning |
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NEW QUESTION # 15
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: D
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 # 16
An HPE Private Cloud AI customer wants to prevent Airflow from consuming too many resources on the cluster.
What is one approach you can take to fulfill this request?
Answer: B
Explanation:
D is correct. Airflow pools provide a direct mechanism for controlling task concurrency. Each pool has a defined number of slots, and tasks assigned to that pool consume slots while they execute. Reducing the number of slots in the default pool therefore limits the number of tasks that can run simultaneously and places an upper bound on how aggressively Airflow can consume cluster resources across concurrent DAG activity.
Option A is not the supported control in this scenario; the Airflow UI does not serve as the general editor for executor-pod CPU and memory sizing. Option B is the opposite of the stated objective because enabling autoscaling can increase executor capacity in response to demand. Option C suggests changing framework values for executor resources, but HPE's Airflow integration historically constrains those settings and the exam-tested method for limiting aggregate workload pressure is pool concurrency.
This is a scheduling-level safeguard rather than a Kubernetes quota. In a production environment, pool slots can be combined with platform quotas and workload resource requests to create layered control over resource consumption.
References/topics: Advanced HPE Compute Solutions, Rev. 26.21, Module 4 "Airflow" and Module 7 resource troubleshooting; HPE AI Essentials Airflow documentation, pool slots and maximum simultaneous jobs.
NEW QUESTION # 17
A hospital wants to fine-tune an LLM on their own dataset. However, the data needs to have sensitive information redacted. Duplicate records also need to be cleaned up. What can help the customer use to achieve this goal?
Answer: B
Explanation:
NeMo Curator is used to prepare datasets for LLM training and fine-tuning, including data cleaning, filtering, sensitive data redaction, and deduplication. MLflow tracks experiments, NeMo Customizer fine-tunes models, and Katib handles hyperparameter tuning.
NEW QUESTION # 18
In an HPE Synergy environment, what is the role of the Synergy Composer?
Answer: C
Explanation:
Synergy Composer is the embedded management appliance running HPE OneView that provides the software-defined control plane for composing and managing Synergy resources into logical servers, storage volumes, and fabric connectivity. It is not a physical cooling component, a licensing key, or a switch module (that role belongs to Virtual Connect/Synergy interconnect modules).
NEW QUESTION # 19
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 # 20
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