A data science team runs a real-time SageMaker endpoint serving a credit-scoring model. Compliance requires that a sample of incoming requests and the model's predictions be persistently stored so the team can later analyze production traffic and build monitoring baselines. The team wants to enable this with minimal custom code and without modifying the inference container. What is the most appropriate approach?