# ADR-051: Asynchronous Context Propagation

**Date**: 2026-01-11

**Status**: Accepted (Implemented)

## Context

Debugging asynchronous workflows is difficult because the `request_id` generated at the API layer is lost when a task is handed off to a background queue (BullMQ). Logs from the worker appear disconnected from the user action that triggered them.

## Decision

We will implement a context propagation pattern for all background jobs:

1. **Job Data Payload**: All job data interfaces MUST include a `meta` object containing `requestId`, `userId`, and `origin`.
2. **Worker Logger Initialization**: All BullMQ workers MUST initialize a child logger immediately upon processing a job, using the metadata passed in the payload.
3. **Correlation**: The worker's logger must use the _same_ `request_id` as the initiating API request.

## Implementation

```typescript
// 1. Enqueueing (API Layer)
await queue.add('process-flyer', {
  ...data,
  meta: {
    requestId: req.log.bindings().request_id, // Propagate ID
    userId: req.user.id,
  },
});

// 2. Processing (Worker Layer)
const worker = new Worker('queue', async (job) => {
  const { requestId, userId } = job.data.meta || {};

  // Create context-aware logger for this specific job execution
  const jobLogger = logger.child({
    request_id: requestId || uuidv4(), // Use propagated ID or generate new
    user_id: userId,
    job_id: job.id,
    service: 'worker',
  });

  try {
    await processJob(job.data, jobLogger); // Pass logger down
  } catch (err) {
    jobLogger.error({ err }, 'Job failed');
    throw err;
  }
});
```

## Consequences

**Positive**: Complete traceability from API request -> Queue -> Worker execution. Drastically reduces time to find "what happened" to a specific user request.
