Platform for AI (PAI) - Release dynamic parameters for an EAS service
Apr 17 2026
Platform for AI (PAI)Content
Dynamic parameters are a runtime configuration capability provided by EAS. They allow you to modify parameter settings in real time while a service is running and take effect immediately without restarting the service. Differences from environment variables: Environment variables: Injected at service startup. After modification, you usually need to restart the service for changes to take effect. Dynamic parameters: Can be modified at runtime. Changes take effect immediately without a restart. Core benefits: The configuration takes effect in real time and can be quickly synchronized to all container instances. Does not affect service running and avoids service interruption caused by Restart. Suitable for frequently adjusted configuration items, such as Rate Limiting thresholds and model inference parameters. Scenarios: Dynamic parameters apply to the following scenarios: Dynamically adjust Rate Limiting configuration: For example, update Rate Limiting parameters such as rate_limit in real-time based on service traffic. Modify model inference parameters in real-time: Adjust parameters such as temperature, top_p, and max_tokens to optimize the Effect or Cost. Adjust the log level: Temporarily increase the log Outputs level when troubleshooting issues, and recover it after completion. Grayscale Release Switch control: Control the Switch Status of New Features through dynamic parameters to implement batch publishing. A/B Test configuration: Quickly switch between different configuration policies to facilitate Effect comparison and authentication.