Monitoring¶

SnerdMQ provides multiple monitoring surfaces — from the built-in dashboard to programmatic APIs — so you can observe queue health in production.

Built-in Dashboard¶

Every SDK ships with a React dashboard that provides real-time visibility:

// Node.js
queue.startDashboard(9090);

# Python
queue.start_dashboard(9090)

// Go
queue.StartDashboard(9090)

Open http://localhost:9090 to see:

Live stats: total enqueued, processed, and failed jobs
Recent Jobs table: per-task status (queued, active, completed, failed, dead_letter), retry counts, and feature badges
Real-time Progress Stream: live output from yieldProgress calls

JSON API¶

The dashboard exposes REST endpoints for programmatic access:

`GET /api/stats`¶

Returns aggregate queue statistics.

{
  "total_enqueued": 1542,
  "total_processed": 1498,
  "total_failed": 12,
  "total_active": 32,
  "total_dead_letter": 4,
  "queue_depth": 44
}

`GET /api/tasks`¶

Returns the list of recent tasks with their status.

{
  "tasks": [
    {
      "id": "email-123",
      "type": "send_email",
      "status": "completed",
      "retries": 0,
      "created_at": "2026-08-17T10:00:00Z",
      "features": ["rate_limit", "dedupe"]
    }
  ]
}

`GET /api/progress`¶

Returns the latest progress events.

{
  "progress": [
    {
      "task_id": "report-456",
      "message": "Step 7/10 complete",
      "timestamp": "2026-08-17T10:05:30Z"
    }
  ]
}

Prometheus Metrics¶

You can expose queue stats to Prometheus by polling /api/stats with the Prometheus Node Exporter's textfile collector, or by writing a simple bridge:

# Example: Prometheus bridge (Python)
import time
import requests
from prometheus_client import Gauge, start_http_server

queued = Gauge('snerdmq_queue_depth', 'Current queue depth')
processed = Gauge('snerdmq_total_processed', 'Total processed tasks')
failed = Gauge('snerdmq_total_failed', 'Total failed tasks')
dlq = Gauge('snerdmq_dead_letter_count', 'Dead letter queue count')

start_http_server(9100)

while True:
    stats = requests.get('http://localhost:9090/api/stats').json()
    queued.set(stats['queue_depth'])
    processed.set(stats['total_processed'])
    failed.set(stats['total_failed'])
    dlq.set(stats['total_dead_letter'])
    time.sleep(15)

Health Checks¶

Add a health check endpoint to your application:

app.get('/health', (req, res) => {
    try {
        const stats = queue.getStats();  // SDK-specific method
        res.json({
            status: 'healthy',
            queue_depth: stats.queue_depth,
            daemon_alive: true,
        });
    } catch (err) {
        res.status(503).json({
            status: 'unhealthy',
            error: err.message,
        });
    }
});

Alerting Recommendations¶

Set up alerts for these conditions:

Condition	Severity	Action
`queue_depth > 1000`	Warning	Scale up workers or investigate bottleneck
`total_dead_letter > 0`	Critical	Inspect DLQ entries, fix failing tasks
`total_failed / total_processed > 0.1`	Warning	High failure rate, check handler logs
`daemon process not running`	Critical	Restart application, check binary path
`queue file size > 1GB`	Warning	Investigate backlog, consider cleanup

Log Monitoring¶

SnerdMQ daemon logs to stderr. Capture it in your logging pipeline:

# Docker: logs are captured automatically
docker logs my-app-container

# Systemd: logs go to journalctl
journalctl -u my-app -f

# Kubernetes: logs go to stdout/stderr
kubectl logs -f deployment/my-app

Dashboard in Production¶

Warning

The built-in dashboard is intended for development and debugging. For production monitoring, use the /api/stats endpoint with your existing monitoring stack (Prometheus, Grafana, Datadog, etc.).

If you want to expose the dashboard in production:

Put it behind authentication
Restrict access to internal networks
Or use the API endpoints directly with Grafana