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HP HPE7-S02 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Troubleshooting HPE Private Cloud AI | 10% | - Issue diagnosis and resolution - Performance tuning and optimization |
| High Performance Computing (HPC) Design and Management | 10% | - Architecture and scaling - Management and monitoring |
| Solution Optimization and Security | 5% | - Security best practices - Efficiency and resilience |
| NVIDIA AI Enterprise and Model Serving | 10% | - Software deployment and management - Model serving architecture and optimization |
| AI Workshops and HPE AI Essentials Platform | 15% | - Platform capabilities and deployment - Customer engagement and assessment |
| HPE AI Essentials: Data Analytics and Data Science | 15% | - Data pipelines and processing - Analytics and machine learning tools |
| HPE ProLiant Gen12 for AI | 20% | - Server architecture and components - GPU integration and configuration - AI-optimized compute design |
| Integration with Third-Party Platforms | 15% | - Red Hat OpenShift and Kubernetes integration - VMware integration |
HP Advanced HPE Compute Integrator Solutions Written Sample Questions:
1. 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?
A) Migrate the deployment to KServe and use autoscaling to set the 10% value for the new model.
B) Edit the existing deployment and use the advanced options to set up routing rules to the two model versions.
C) Add a new version of the model to the existing deployment as a canary rollout, setting the desired percentages per version.
D) Create a second deployment with the new model in MLIS. Use HPE Private Cloud AI's Canal service to set up routing rules to each deployment.
2. What is one role played by the retriever reranking NIM in the NVIDIA NeMo Retriever pipeline?
A) Generating responses to queries submitted by users
B) Determining which vectors retrieved from the RAG database best match a query
C) Submitting queries to an unstructured database
D) Receiving ingested data and preparing it for storage in a RAG database
3. A customer needs to deploy a NIM LLM with HPE Machine Learning Inference Software running on HPE Private Cloud AI (AI Essentials 1.6.1).
What is one option for the image for serving the model?
A) A BentoML image provided by HPE Machine Learning Inference Software
B) A custom image stored in the customer's choice of registry
C) An image stored in the HPE Private Cloud AI registry
D) An image available in the public NGC registry
4. What is one benefit of HPE Slingshot for HPC workloads?
A) It provides advanced congestion management based on DiffServ.
B) It uses InfiniBand NDR to reduce the average end-to-end latency for MPI communications.
C) It uses bandwidth efficiently with packet-by-packet adaptive routing for MPI and Lustre.
D) It provides the end-to-end non-blocking architecture required for typical HPC applications.
5. An HPE Private Cloud AI customer wants to import a custom framework. The customer wants to ensure that only authorized users access that framework's endpoint URL. You have created an authorization policy for this purpose.
In which namespace should you add the policy?
A) ezapp-system
B) the namespace in which you will import the framework
C) the namespace associated with your user account
D) istio-system
Solutions:
| Question # 1 Answer: C | Question # 2 Answer: B | Question # 3 Answer: C | Question # 4 Answer: C | Question # 5 Answer: D |




