# ADR-053: Worker Health Checks and Stalled Job Monitoring

**Date**: 2026-01-11

**Status**: Proposed

## Context

Our application relies heavily on background workers (BullMQ) for flyer processing, analytics, and emails. If a worker process crashes (e.g., Out of Memory) or hangs, jobs may remain in the 'active' state indefinitely ("stalled") until BullMQ's fail-safe triggers.

Currently, we lack:

1. Visibility into queue depths and worker status via HTTP endpoints (for uptime monitors).
2. A mechanism to detect if the worker process itself is alive, beyond just queue statistics.
3. Explicit configuration to ensure stalled jobs are recovered quickly.

## Decision

We will implement a multi-layered health check strategy for background workers:

1. **Queue Metrics Endpoint**: Expose a protected endpoint `GET /health/queues` that returns the counts (waiting, active, failed) for all critical queues.
2. **Stalled Job Configuration**: Explicitly configure BullMQ workers with aggressive stall detection settings to recover quickly from crashes.
3. **Worker Heartbeats**: Workers will periodically update a "heartbeat" key in Redis. The health endpoint will check if this timestamp is recent.

## Implementation

### 1. BullMQ Worker Settings

Workers must be initialized with specific options to handle stalls:

```typescript
const workerOptions = {
  // Check for stalled jobs every 30 seconds
  stalledInterval: 30000,
  // Fail job after 3 stalls (prevents infinite loops causing infinite retries)
  maxStalledCount: 3,
  // Duration of the lock for the job in milliseconds.
  // If the worker doesn't renew this (e.g. crash), the job stalls.
  lockDuration: 30000,
};
```

### 2. Health Endpoint Logic

The `/health/queues` endpoint will:

1. Iterate through all defined queues (`flyerQueue`, `emailQueue`, etc.).
2. Fetch job counts (`waiting`, `active`, `failed`, `delayed`).
3. Return a 200 OK if queues are accessible, or 503 if Redis is unreachable.
4. (Future) Return 500 if the `waiting` count exceeds a critical threshold for too long.

## Consequences

**Positive**:

- Early detection of stuck processing pipelines.
- Automatic recovery of stalled jobs via BullMQ configuration.
- Metrics available for external monitoring tools (e.g., UptimeRobot, Datadog).

**Negative**:

- Requires configuring external monitoring to poll the new endpoint.
