Câu 27: NCP-AAI: Agentic AI

A financial services company is deploying a multi-agent customer service system consisting of three specialized agents: a reasoning LLM for complex queries, an embedding agent for document retrieval, and a re-ranking agent for result optimization. The system experiences significant traffic variations, with peak loads during business hours (10x normal traffic) and minimal usage overnight. The company needs a deployment solution that can handle these fluctuations cost-effectively while maintaining sub-second response times during peak periods. Which NVIDIA infrastructure approach would provide the MOST cost-effective and scalable deployment solution for this variable-load multi-agent system?

1. A. Deploy agents directly on individual NVIDIA RTX workstations without containerization or orchestration, relying on load balancers with round-robin for traffic distribution.
2. B. Deploy each agent on dedicated NVIDIA DGX systems with manual scaling based on previous days traffic predictions and static resource allocation for peak loads.
3. C. Deploy NVIDIA NIM microservices on Kubernetes with auto-scaling capabilities, utilizing NVIDIA NIM Operator for lifecycle management and horizontal pod autoscaling based on custom metrics. — đáp án hiện tại
4. D. Deploy all agents on a single large GPU instance without containerization, scaling compute by upgrading to larger GPU instances when needed.