The question requires monitoring both the data submitted to the web service and the predictions generated, with minimal administrative effort for a real-time inference service. Option B (Enable Azure Application Insights) is optimal because it provides built-in integration with Azure ML endpoints, automatically capturing request/response data including inputs and predictions, and requires minimal setup (just enabling it during deployment). It offers real-time monitoring, analytics, and alerting capabilities suitable for business-critical applications. While option D (MLflow tracking) can log predictions, it requires manual instrumentation and ongoing management, increasing administrative overhead. Options A and C do not provide real-time monitoring of endpoint traffic and predictions. The community discussion shows B as the consensus (63% votes) with upvoted comments emphasizing Application Insights' ease of setup and real-time capabilities for endpoint monitoring.