Execution Logs
Every workflow execution produces a complete, immutable audit trail — allowing you to debug failures, analyze performance, and understand agent behavior at every step.
Why Execution Logs Matter
In AI automation, failures are inevitable — models hallucinate, APIs timeout, tools misbehave. This platform treats observability as a first-class feature. Logs are not an afterthought; they are the foundation for trust, safety, and reproducibility.
Observability Stack
Run History
Every workflow trigger creates a permanent execution record.
Step-Level Status
Track success, failure, retries, and timing for each step.
Payload Inspection
Full visibility into inputs, outputs, and intermediate results.
Log Structure
Logs are stored per task execution and indexed by workflow, step, and timestamp. This enables efficient querying, debugging, and replay.
| Field | Description |
|---|---|
| message | Human-readable log message |
| level | Log severity: debug, info, success, warn, error |
| workerId | Identifier of the worker that emitted the log |
| workflowId | ID of the workflow being executed |
| taskId | ID of the task execution |
| createdAt | ISO timestamp of the log entry |
| traceId | Trace ID for correlating logs across steps |
Log Levels
Filtering Logs
The Logs page supports filtering by level, workflow ID, task ID, search text, and date range. Use structured view for detailed inspection or raw terminal view for quick scanning.
Log API
/api/logsList logs with filtering by level, workflowId, taskId, search, and date range. Supports pagination.