How should you collect telemetry for your Azure Cognitive Services resource for analysis later?

To effectively collect telemetry for an Azure Cognitive Services resource, configuring diagnostic settings is the optimal approach. Diagnostic settings allow you to route logs and metrics from your Cognitive Services to various destinations for analysis, such as Azure Monitor, Azure Storage, or even third-party tools. This enables you to gather detailed performance and usage statistics for your resource, which can be invaluable for monitoring and optimizing your AI solutions.

By using diagnostic settings, you enable comprehensive telemetry collection, including insights into operation data and errors, which can be critical for troubleshooting and ensuring the health of the service over time. This proactive data collection method ensures that you have the necessary information available when you need to analyze the performance or diagnose issues.

Creating alerts could notify you of specific events or thresholds being met, but it does not by itself collect the telemetry data for later analysis. Similarly, creating a dashboard is useful for visualizing data, but it requires that data to first be collected and stored, which is accomplished through diagnostic settings. Aggregating logs manually is not only time-consuming but also prone to errors, and it lacks the automation and integration that diagnostic settings provide. Hence, configuring diagnostic settings is the most effective and comprehensive method for long-term telemetry collection in Azure Cognitive Services.