Background to the issue
AI services typically involve the use of multiple resources such as GPU time and storage space, and traditional billing methods make it difficult to accurately track these complex metrics.
prescription
Flexprice improves billing accuracy in the following ways:
- Custom Event Definitions: Specialized units of measurement such as GPU seconds, storage GB-hours, etc. can be created
- Real-time data processing: Kafka and ClickHouse based architecture can handle high concurrent usage data.
- credit management: Setting of resource quotas and automatic alert mechanisms
carry out in practice
- Embedding the SDK in the application to send resource usage events (e.g. one event for every 1 second of GPU usage)
- Configuration of measurement rules and price lists
- Setting the usage alarm threshold (e.g., notify the user when the limit 80% is reached)
- Integration with Stripe and other payment tools for automatic chargebacks
Optimization Recommendations
For computationally intensive applications, batch reporting mode is recommended to reduce system load.
This answer comes from the articleFlexprice: an open source billing tool that supports usage billing and subscriptionsThe
May not be reproduced without permission:AI productivity tools " How to improve the accuracy of resource usage billing in AI services?
