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Adaline enforces rate limits to ensure fair usage and platform stability. Limits apply per workspace.

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Default Limits

ResourceLimitWindow
Log Trace APIs60,000per minute
Log Span APIs150,000per minute
Deployment APIs60,000per minute
All other APIs6000per minute
These are default limits. If you need higher limits for your use case, contact support@adaline.ai.

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Handling Rate Limits

When you exceed the rate limit, the API returns a 429 Too Many Requests response: 
{
  "error": {
    "code": "RATE_LIMIT_EXCEEDED",
    "message": "Rate limit exceeded. Please try again later."
  }
}

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Payload Limits

ResourceMax Size
Request body32 MB
Response body32 MB
Span content1 MB
Span content attachment (image)10 MB
Span content attachment (pdf)10 MB
Requests exceeding payload limits receive a 413 Payload Too Large response.

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SDK Retry Behavior

TypeScript SDK (@adaline/client)
  • The Monitor class buffers logs and flushes in batches
  • Failed flushes are automatically retried with exponential backoff
  • Configure flushInterval and maxBufferSize to control batching
const monitor = adaline.initMonitor({
  projectId: "your-project-id",
  flushInterval: 5,    // seconds between flushes
  maxBufferSize: 100,  // max items before forced flush
});
Gateway SDK (@adaline/gateway)
  • Built-in configurable queue with automatic retry
  • Exponential backoff on transient failures (429, 5xx)
  • Pluggable queue backend for custom retry logic
const gateway = new Gateway({
  // Custom queue options are configured per-request or via plugins
});

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Best Practices

Use the SDK’s built-in batching (Monitor class) rather than sending individual API calls for each trace or span. This significantly reduces the number of requests.
Use initLatestDeployment() with a refreshInterval to cache prompt deployments locally and reduce deployment fetch requests.
If making direct API calls, implement exponential backoff when you receive 429 responses. Start with a 1-second delay and double it on each retry, up to a maximum of 60 seconds.
Track your API usage in the Adaline Dashboard under Settings > API Usage to stay within your limits. See View API Usage.