You are a machine learning engineer at a financial aws video
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You are a machine learning engineer at a financial services company responsible for maintaining a fraud detection model deployed on Amazon SageMaker. The model processes a high volume of real-time transactions and must respond with low latency to ensure a seamless customer experience. Recently, the model has experienced increased latency during peak traffic times, and there have been instances where requests were dropped due to insufficient capacity. Which approach is the MOST EFFECTIVE for monitoring and resolving these latency and scaling issues in your ML solution?