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You are a data engineer responsible for monitoring the performance of machine learning models used for fraud detection, recommendation systems, and sales forecasting at a financial services company. These models are deployed in production and are critical to business operations. The company requires a monitoring solution that can aggregate performance metrics such as prediction latency, model accuracy, and resource utilization. The solution must provide real-time visualizations and allow non-technical stakeholders to drill down into specific metrics for insights. Which approach would best meet these requirements?