The correct option is Azure Anomaly Detector.

The service applies machine learning specifically to time series data to identify unusual activity and repeating patterns. It offers a ready made REST API and SDKs for real time and batch anomaly detection which makes it a direct fit for the retail analytics team requirements.

Azure Stream Analytics is a real time stream processing and query service for event data and it is not an out of the box machine learning anomaly detection API. It can integrate with external models but it does not itself provide the turnkey time series anomaly detection capability.

Azure Machine Learning is a comprehensive platform for building training and deploying custom machine learning models and it requires you to design and manage models rather than giving a simple, dedicated time series anomaly detection endpoint.

Google Cloud Monitoring is a monitoring and observability service for Google Cloud resources and applications and it is not the Azure offering. It focuses on metrics, logs, and alerts and is therefore not the Azure service that directly provides the described anomaly detection feature.

None of the listed services are deprecated or retired so the current Azure naming and capabilities apply.

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