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06 Automations

06 Automations

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Automations & Scheduled Notebooks

Open in Alph

Alph can run notebook cells on a schedule — no cron server, no Airflow, no infrastructure. Set it up in a few clicks and your notebooks run themselves. This requires a running project that can run the notebook!

How It Works

  1. Write your code in a notebook cell as usual
  2. Click the clock icon on the cell toolbar (or right-click → "Schedule")
  3. Pick a schedule — every hour, daily, weekly, or custom cron expression
  4. Done. Alph runs the cell on schedule using your project's cloud compute

Each run is logged with its output, execution time, and status. You can view the full history in the cell's run log.

Note: Scheduled runs execute code inside your project — they can read/write files, call APIs, update databases, and modify state within your project environment. The notebook itself isn't changed; you'd still publish any notebook content updates separately.

Example: Daily Data Report

Schedule the cell below to run every morning at 8am. It fetches data and generates a summary.

[1]
šŸ“Š Daily Report — 2026-03-19
   New users:         77
   Active notebooks:  454
   Compute hours:     320.0h
   API calls:         18,401

Example: Data Refresh Pipeline

Keep a dataset up to date by scheduling a refresh. This pattern works for any API or database.

[2]
Exchange rates as of 2026-03-19 12:22
  USD → EUR: 0.8713
  USD → GBP: 0.7529
  USD → JPY: 159.25
  USD → CAD: 1.3725

Example: Health Check / Monitoring

Use a scheduled cell as a lightweight uptime monitor.

[3]
Service Health Check
==================================================
  [OK] https://httpbin.org/status/200 — 200 (671ms)
  [OK] https://httpbin.org/delay/1 — 200 (1287ms)
  [OK] https://httpbin.org/status/200 — 200 (264ms)

Cron Expressions

For custom schedules, use standard cron syntax:

ExpressionSchedule
0 8 * * *Every day at 8:00 AM
0 */6 * * *Every 6 hours
*/15 * * * *Every 15 minutes
0 9 * * 1Every Monday at 9:00 AM
0 0 1 * *First day of every month
ā”Œā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ minute (0-59)
│ ā”Œā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ hour (0-23)
│ │ ā”Œā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ day of month (1-31)
│ │ │ ā”Œā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ month (1-12)
│ │ │ │ ā”Œā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ day of week (0-6, Sun=0)
│ │ │ │ │
* * * * *

Run History & Logs

Every scheduled run is recorded. Click the clock icon on a scheduled cell to see:

  • Run history — timestamp, duration, status (success/failure)
  • Output — the full output from each run
  • Errors — stack traces if something went wrong

You can also pause and resume schedules without deleting them.

Common Patterns

PatternScheduleExample
Daily report0 8 * * *Fetch metrics, generate summary
Data refresh0 */6 * * *Pull latest data from API/DB
Health check*/15 * * * *Ping endpoints, alert on failure
Weekly digest0 9 * * 1Aggregate weekly stats
Model retrain0 2 * * 0Retrain ML model on new data
Cleanup0 3 1 * *Archive old files, rotate logs

No infrastructure to manage. No Docker. No Airflow. Just write a cell and schedule it.