Intermediate• 20 minutes

Monitoring and Alerting

Set up comprehensive monitoring and alerting for your automations to ensure reliability and performance.

What You'll Build

In this tutorial, you'll learn how to:

Monitor automation performance and health
Create alerts based on metrics and thresholds
Configure notification channels (email, webhooks, Slack)
Set up dashboards for real-time monitoring
Track key performance indicators

Prerequisites

Before You Start

✅ A Sematryx account with active automations
✅ Understanding of monitoring concepts
✅ Access to notification channels (email, webhooks)

Step 1: Create Monitoring Alerts

Set up alerts to be notified when metrics exceed thresholds:

Create monitoring alert

curl -X POST https://api.sematryx.com/v1/alerts \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "high-error-rate",
    "condition": {
      "metric": "error_rate",
      "operator": ">",
      "threshold": 0.05
    },
    "notifications": [
      {
        "type": "email",
        "config": {
          "recipients": ["team@example.com"]
        }
      },
      {
        "type": "webhook",
        "config": {
          "url": "https://your-app.com/alerts"
        }
      }
    ]
  }'

Available Metrics

error_rate: Percentage of failed executions
execution_time: Average execution duration
throughput: Executions per time period
cost: API usage costs
queue_depth: Number of pending executions

Step 2: Using the Python SDK

Create alerts programmatically:

Create alert with Python SDK

from sematryx import SematryxClient

client = SematryxClient(api_key='your-api-key')

# Create monitoring alert
alert = client.alerts.create(
    name='high-error-rate',
    condition={
        'metric': 'error_rate',
        'operator': '>',
        'threshold': 0.05
    },
    notifications=[
        {
            'type': 'email',
            'config': {'recipients': ['team@example.com']}
        }
    ]
)

Step 3: Monitor Metrics

Retrieve real-time metrics and analytics:

Get monitoring metrics

# Get real-time metrics
metrics = client.analytics.get_metrics(
    start_date='2024-01-01',
    end_date='2024-01-31'
)

print(f"Total executions: {metrics.total_executions}")
print(f"Success rate: {metrics.success_rate}")
print(f"Average execution time: {metrics.avg_execution_time}")

Notification Channels

Email Notifications

Receive email alerts when conditions are met. Configure recipients and email templates.

Webhook Notifications

Send alerts to your own systems via HTTP webhooks for custom integrations.

Slack Integration

Send alerts directly to Slack channels for team visibility.

SMS Notifications

Receive SMS alerts for critical issues that require immediate attention.

Best Practices

Monitoring Best Practices

Set up alerts for critical metrics (error rate, execution time)
Use appropriate thresholds to avoid alert fatigue
Configure multiple notification channels for redundancy
Review and adjust alert thresholds regularly
Monitor trends over time, not just point-in-time values
Set up dashboards for visual monitoring

🎉 Next Steps

You've learned how to set up monitoring and alerts! Continue learning:

→ Learn enterprise workflow patterns → Explore analytics API documentation