Cron Expression: Every Day at 8:30 AM (30 8 * * *)

The cron expression 30 8 * * * executes a task every day at 8:30 AM, making it ideal for tasks that should run after initial morning operations complete, such as follow-up reports or secondary data processing.

Expression Breakdown

30 8 * * *
│  │ │ │ │
│  │ │ │ └─── Day of week: * (every day)
│  │ │ └───── Month: * (every month)
│  │ └─────── Day of month: * (every day)
│  └───────── Hour: 8 (at hour 8, 8:00 AM)
└──────────── Minute: 30 (at minute 30)

Field Values

Execution Time

This expression runs once per day at:

• 08:30 (8:30 AM)

Common Use Cases

1. Follow-Up Reports

30 8 * * * /usr/bin/python3 /scripts/generate-follow-up-report.py

Generate follow-up reports after initial morning operations complete.

2. Secondary Data Processing

30 8 * * * /usr/bin/python3 /scripts/secondary-data-processing.py

Process data that depends on 8 AM jobs completing first.

3. Cache Refresh

30 8 * * * /usr/bin/python3 /scripts/refresh-cache.py

Refresh cached data after initial morning data loads.

4. Email Notifications

30 8 * * * /usr/bin/node /app/send-morning-updates.js

Send morning update emails or notifications.

Example Implementations

Follow-Up Report Script

# generate-follow-up-report.py
import json
from datetime import datetime
import sqlite3

def generate_follow_up_report():
    conn = sqlite3.connect('/var/data/app.db')
    cursor = conn.cursor()
    
    # Check if morning data is ready
    cursor.execute('''
        SELECT COUNT(*) FROM morning_data
        WHERE DATE(processed_at) = DATE('now')
    ''')
    
    count = cursor.fetchone()[0]
    
    if count > 0:
        # Generate follow-up report
        report = {
            'date': datetime.now().strftime('%Y-%m-%d'),
            'time': '8:30 AM',
            'status': 'morning_data_processed',
            'records': count
        }
        
        with open(f'/var/reports/followup_{datetime.now().strftime("%Y%m%d")}.json', 'w') as f:
            json.dump(report, f, indent=2)
        
        print(f"{datetime.now()}: Follow-up report generated")
    else:
        print(f"{datetime.now()}: Morning data not ready yet")
    
    conn.close()

if __name__ == '__main__':
    generate_follow_up_report()

Best Practices

1. Dependency Management: Ensure 8 AM jobs complete before 8:30 AM jobs start
2. Error Handling: Implement comprehensive error handling and logging
3. Locking: Use file locks to prevent concurrent execution
4. Monitoring: Set up alerts for failed jobs
5. Timing: 30 minutes after 8 AM allows time for initial operations

When to Use

✅ Good for:

• Follow-up reports
• Secondary data processing
• Cache refresh
• Email notifications
• Tasks dependent on 8 AM jobs

❌ Avoid for:

• Real-time critical operations
• Tasks requiring immediate execution

Related Patterns

Conclusion

The 30 8 * * * expression is perfect for tasks that need to run after initial morning operations complete. It's commonly used for follow-up reports, secondary data processing, and tasks that depend on 8 AM jobs finishing first, providing a 30-minute buffer for initial operations.