Testing: Azure Container Instances (ACI) is the officially recommended compute target for development and testing environments. It is a serverless, managed service that requires minimal deployment effort and is highly cost-effective for low-volume testing as it eliminates the need to manage complex cluster infrastructure.

Production: Azure Kubernetes Service (AKS) is designed for high-scale production workloads. It fulfills the requirements for fast response times and low latency through robust resource management. Crucially, AKS provides autoscaling of the deployed pods to handle traffic spikes and natively supports real-time inferencing at scale.

Official Vendor Documentation:

Microsoft Learn. (2025, October). What are compute targets in Azure Machine Learning? Section: "Compute targets for inference". URL: https://learn.microsoft.com/en-us/azure/machine-learning/concept-compute-target

Microsoft Learn. (2025, April). Deploy machine learning models to online endpoints. Section: "Managed online endpoints vs Kubernetes online endpoints". URL: https://learn.microsoft.com/en-us/azure/machine-learning/how-to-deploy-online-endpoints

Architectural Guidance:

Azure Architecture Center. (2025, January). Overview of Microsoft Machine Learning Products and Technologies. Subsection: "Azure Machine Learning - Deployment". URL: https://learn.microsoft.com/en-us/azure/architecture/ai-ml/guide/data-science-and-machine-learning