Amazon Forecast is used for what specific function?

Amazon Forecast is specifically designed for generating time-series forecasts. This service leverages machine learning techniques to predict future values based on historical data, making it invaluable for businesses that need to forecast demand, resource utilization, or other metrics that can be expressed in a time-sequenced format.

The strength of Amazon Forecast lies in its ability to automatically select the best algorithms and configurations that fit your unique dataset, providing accurate forecasts without requiring extensive machine learning expertise from the user. Companies can input their historical time-series data along with related data (such as items, prices, promotions, or seasonality) to generate predictions that help in decision-making processes.

While the other options might seem relevant in a broader sense, they do not align with the core functionality of Amazon Forecast. For instance, monitoring application performance relates to services like Amazon CloudWatch, whereas creating machine learning models is a broader task that can be done with Amazon SageMaker. Analyzing customer feedback typically falls under the domain of workflows powered by natural language processing and customer analytics tools, which do not specifically focus on time-series forecasting.