Question

A machine learning engineer manages a real-time SageMaker endpoint serving a recommendation model. Business stakeholders complain that during peak hours the recommendations feel slow, but the endpoint's average latency in CloudWatch looks acceptable. The engineer needs to detect and alert on the tail-latency experienced by the slowest requests so the team can react before customers are affected. Which CloudWatch approach best addresses this requirement?

Accepted Answer

Create a CloudWatch alarm on the p99 percentile statistic of the ModelLatency metric emitted by the endpoint.

Answer

Create a CloudWatch alarm on the Average statistic of the OverheadLatency metric emitted by the endpoint.

Answer

Create a CloudWatch alarm on the SampleCount statistic of the Invocations metric emitted by the endpoint.

Answer

Enable SageMaker Model Monitor data quality baselines to capture latency drift over time.