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HPE0-S59 Exam Questions
- HPE ASE Certifications
- HPE ASE - Compute Solutions V1 Certifications
- Topic 1: Understand Fundamental AI Concepts: This section of the exam measures the skills of the AI Solutions Architect and covers the ability to assess a customer's AI maturity level, understand specific workloads and use cases, and position HPE AI solutions accordingly. It focuses on aligning the right AI infrastructure and services with customer needs based on where they are in their AI journey.
- Topic 2: Describe the Infrastructure Components of HPE Private Cloud AI with NVIDIA: This section evaluates the knowledge of the Enterprise Infrastructure Engineer and includes understanding the benefits and features of the infrastructure provided by HPE and NVIDIA. It addresses how the combined solution meets demanding AI workload requirements and supports high-performance computing.
- Topic 3: Describe the Software Components of HPE Private Cloud AI with NVIDIA: In this part, the AI Solutions Architect is tested on their understanding of HPE and NVIDIA’s software offerings within the Private Cloud AI platform. The section emphasizes how these components integrate to support AI development and deployment while offering operational advantages.
- Topic 4: Size HPE Private Cloud AI with NVIDIA Solutions: This section targets the Enterprise Infrastructure Engineer and involves sizing the solution based on customer data, performance goals, and workload characteristics. It also includes knowledge of using HPE tools to determine the optimal configuration that aligns with both cost-efficiency and technical requirements.
- Topic 5: Configure and Quote HPE Private Cloud AI Solutions: The AI Solutions Architect is expected to demonstrate the ability to configure AI solutions using HPE tools, recommend appropriate services, and understand the division of responsibilities between HPE, customers, and partners. The section also includes knowledge of Customer Intent Documents and managing evolving needs such as updates or expansions.
- Topic 6: Identify and Use HPE GreenLake Cloud Services: This section examines the capabilities of the Enterprise Infrastructure Engineer in applying the right HPE GreenLake cloud services to support customer requirements such as improving performance, updating firmware, or expanding capabilities. It also involves using HPE Private Cloud AI to demonstrate a basic AI use case in a real-world setting.
- Topic 7: Design an Edge Inferencing Solution: This part of the exam evaluates the skills of the AI Solutions Architect in designing edge inferencing systems by selecting suitable servers, GPUs, and networking components. It includes best practices for deploying HPE ProLiant servers and integrating them into AI-focused environments.
- Topic 8: Manage HPE Compute Solutions: Here, the Enterprise Infrastructure Engineer is assessed on their ability to onboard servers into HPE Compute Ops Management and utilize the platform to manage systems, apply updates, and fulfill customer requests. This includes managing compute resources efficiently across various deployment scenarios.
- Topic 9: Design and Deploy Storage for HPE Compute Solutions: The AI Solutions Architect is responsible in this section for designing storage systems that complement HPE compute environments. It covers selecting suitable storage architectures and ensuring alignment with performance and scalability expectations.
- Topic 10: Describe and Deploy HPE VM Essentials: This domain measures the knowledge of the Enterprise Infrastructure Engineer in understanding the benefits of HPE VM Essentials, and their ability to design and implement it in a production environment, ensuring cost-effective virtualization for AI and general computing workloads.
- Topic 11: Optimize and Troubleshoot HPE Compute and AI Solutions: This section tests the expertise of the AI Solutions Architect in fine-tuning system performance and resolving common issues in compute and AI environments. It focuses on applying optimization techniques and diagnosing problems to ensure efficient, stable, and high-performing operations.
Free HP HPE0-S59 Exam Actual Questions
Note: Premium Questions for HPE0-S59 were last updated On Aug. 12, 2025 (see below)
Your customer has an HPE Synergy platform deployed and managed using HPE OneView. The customer also has HPE Superdome Flex with RMC deployed They plan to deploy a second nPar and HPE Superdome Flex 280 They plan to manage new components using HPE OneView
What must be done to achieve this goal?
To manage HPE Superdome Flex systems, including the new Superdome Flex 280, using HPE OneView, the customer should deploy a dedicated HPE OneView appliance specifically for HPE Superdome Flex management. This approach ensures that the Superdome Flex systems are properly integrated and managed within the HPE OneView environment, allowing for consistent and centralized management alongside other HPE infrastructure.
Refer to the exhibit.
Which statement about this logical interconnect group is true?
In the HPE Synergy setup shown in the exhibit, the interconnect type is Virtual Connect SE 32Gb FC Module for Synergy with an enclosure count of 1 and interconnect bay set 1. Typically, in such configurations, the interconnect modules are installed in bays 1 and 4 for redundancy. This placement ensures high availability and failover capabilities.
Your customer plans to deploy VMware ESXi 7.0 U2, and they are looking for a hardware platform that will allow them to use up to 24 TB of physical memory.
Which HPE compute system meets the customer's requirements?
Your customer experienced some problems caused by outdated HPE Superdome Flex firmware. Which update method should they use to avoid these issues in the future?
HPE System Update Manager (SUM) is the recommended method for updating firmware on HPE Superdome Flex systems, especially when HPE Persistent Memory firmware needs to be updated. HPE SUM ensures that all firmware components are updated correctly and consistently, reducing the risk of compatibility issues.
One of the administrators added some connections within a server profile that was created using a template. This server profile did not report inconsistency.
What is the most likely reason for this behavior?
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