NVIDIA Triton Inference Server with Kubernetes is the most suitable approach for deploying and managing a real-time fraud detection system on NVIDIA A100 GPUs. Triton provides a scalable, low-latency inference platform with features like dynamic batching and model management, ideal for processing thousands of transactions per second. Integration with Kubernetes (via NVIDIA GPU Operator) ensures high availability, scalability, and orchestration in a cluster, as outlined in NVIDIA's "Triton Inference Server Documentation" and "DeepOps" resources. This meets the financial institution's needs for real-time, high-throughput inference.
TensorRT standalone (A) optimizes models but lacks deployment scalability. Kafka with GPUs (C) is a messaging system, not an inference solution. CUDA with Docker (D) is a development tool, not a production deployment platform. Triton with Kubernetes is NVIDIA's recommended approach.