Skip to main content

Monitoring Costs for Azure AI Services

To effectively monitor and manage your Azure OpenAI costs, you should focus on the following key areas using Azure Cost Management tools:

  1. Cost Analysis:
    • Service Name: Filter by "Cognitive Services" and "Azure OpenAI" to view costs specific to Azure OpenAI.
    • Resource Group: Group costs by resource groups to see which projects or departments are incurring the most expenses.
    • Meter Subcategory: Look at costs grouped by meter subcategory to differentiate between token-based deployments and Provisioned Throughput Units (PTUs).
  2. Budgets and Alerts:
    • Set Budgets: Create budgets for your Azure OpenAI services and set thresholds (e.g., 50%, 75%, 90%) to receive alerts when spending approaches these limits.
    • Email Alerts: Subscribe to automated email updates for your cost views to stay informed about spending trends and anomalies.
  3. Usage Metrics:
    • Token Usage: Monitor the number of tokens used for both input and output to understand how much you're spending on API calls.
    • Provisioned Throughput Units (PTUs): Track PTU usage if you have reserved throughput to ensure you're utilizing your allocation efficiently.
  4. Forecasted Costs:
    • Cost Forecasting: Use the forecasting feature to predict future costs based on current usage patterns. This helps in planning and adjusting budgets proactively.
  5. Cost Optimization:
    • Identify Trends: Regularly review cost trends to identify any unusual spikes or patterns that may indicate inefficiencies or unexpected usage.
    • Optimize Resources: Consolidate workloads, minimize unnecessary API calls, and use the most cost-effective models to optimize your spending.

 

Resources for Each of the Suggestions