Step 5: Orchestration Basics

Step 5: Orchestration Basics

Orchestration is the process of coordinating and managing automated tasks. You need a way to run your scripts on a schedule and handle failures.

---

🛠️ Code Example: Simple Scheduling

For beginners, you can use the schedule library to run tasks without needing a complex server.

import schedule
import time

def my_etl_job():
    print("ETL Job Started...")
    # Your ETL logic here
    print("ETL Job Finished Successfully.")

# Run every hour
schedule.every().hour.do(my_etl_job)

# Run every day at 10:30 AM
schedule.every().day.at("10:30").do(my_etl_job)

while True:
    schedule.run_pending()
    time.sleep(1)

---

🏗️ Orchestration Concepts

1. Retries: If an API is down, the system should wait and try again.
2. Alerting: If a job fails after 3 tries, send an email or Slack message.
3. DAGs: (Directed Acyclic Graphs) – A fancy name for a sequence of tasks (e.g., Task A must finish before Task B starts).

---

🥅 Your Goal

• Research Apache Airflow (The industry standard).
• Understand why a simple “Cron Job” is sometimes not enough for complex pipelines.