AWS Cost Anomaly Detection primarily monitors spending and cost increases by analyzing your AWS usage patterns and identifying any deviations from your typical spending behavior. This service utilizes machine learning to establish a baseline of your spending and alerts you to any unexpected increases that could indicate potential issues, such as unexpected usage spikes, potential billing errors, or the consumption of resources that might not have been accounted for in your forecasts.
By focusing on spending patterns, it helps organizations manage their AWS costs more effectively, allowing them to take proactive measures if their spending exceeds expected values. This is crucial for effective budgeting and financial management within an organization using AWS services.
The other options, while relevant to AWS environments or cloud management in general, do not directly relate to the core functionality of Cost Anomaly Detection. For instance, monitoring API call usage, network traffic patterns, or service uptime falls under different AWS services and use-cases, which focus on operational metrics rather than cost management.