AI Service Operations Monitoring Implementation Guide
AIRouter's health monitoring system provides the operations team with the following key capabilities:
| functionality | implementation method | Monitoring Indicators |
|---|---|---|
| API Survival Detection | Regular visits to the /check_healthy endpoint | HTTP status code, response time |
| Smart Fuse | Automatically block consecutive timeout APIs | Error rate, number of timeouts |
| Resource Alert | Analyzing the api_key_usage table | Token consumption rate |
Implementation Steps:
1. Start the health check service: python CheckHealthy.py (or docker-compose up)
2. Configure alert thresholds: modify parameters such as MAX_RESPONSE_TIME in health_check_config.py
3. Integration of monitoring systems: push alerts to Slack/Enterprise WeChat through webhooks
BEST PRACTICE: It is recommended to set health check intervals to 5-10 minutes to avoid triggering provider rate limits.
This answer comes from the articleAIRouter: Intelligent Routing Tool for Calling Multiple Models with Unified API InterfaceThe
May not be reproduced without permission:AI productivity tools " How to apply AIRouter's health monitoring feature in an automated ops scenario?
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