Apache Airflow

Logging in Apache Airflow

Effective logging is crucial for understanding the execution of your data pipelines, debugging issues, and monitoring the health of your Airflow environment. Airflow provides a robust and flexible logging system that can be configured to suit various needs.

How Airflow Logs Work

Airflow logs are generated at different levels: the scheduler, the webserver, individual task instances, and various internal components. Each log message typically includes information about the timestamp, log level, the component generating the log, and the message content.

Configuring Logging

The primary configuration for logging is done through the airflow.cfg file or environment variables. Key parameters include:

• logging_config_class: Specifies a custom Python module for logging configuration.
• base_log_folder: The base directory where Airflow logs are stored locally.
• remote_logging: A boolean to enable or disable remote logging.
• remote_log_conn_id: The connection ID for the remote logging backend.
• remote_log_url: The URL for the remote logging backend.

For example, to configure logging to use Amazon S3 as a backend, you would set:

[logging]
remote_logging = True
remote_log_conn_id = aws_default
remote_log_url = s3://your-airflow-logs-bucket/{{ dag_id }}/{{ task_id }}/{{ execution_date }}/{{ try_number }}.log
            

Logging Backends

Airflow supports various logging backends:

• Local File System: The default and simplest option, logs are stored on the machine running the Airflow components.
• Remote Logging: Allows logs to be sent to external systems for better scalability, durability, and centralized access. Supported backends include:
  • Amazon S3
  • Google Cloud Storage (GCS)
  • Azure Blob Storage
  • Elasticsearch
  • HTTP/HTTPS endpoints

Accessing Logs

You can access logs through several methods:

• Airflow UI: The Airflow web UI provides a dedicated interface to view logs for individual task instances. You can navigate to a DAG run, click on a task, and then select "View Log".
• Command Line Interface (CLI): The Airflow CLI can be used to fetch logs for specific tasks or DAG runs. For example:

  airflow tasks logs my_dag_id my_task_id 2023-10-27T00:00:00+00:00

• Direct Access: If using local logging, you can navigate to the base_log_folder on the filesystem. For remote logging, you access them via the specific service's interface (e.g., S3 console, GCS browser).

Log Rotation and Retention

It's essential to manage log file sizes and storage. Airflow can be configured to rotate logs periodically and to retain logs for a specific duration to prevent disk space exhaustion.

Configuring log rotation and retention policies is vital for long-term operational efficiency and cost management, especially in production environments.

Best Practices

• Be Descriptive: Write clear and informative log messages. Include relevant context like task IDs, execution dates, and any unique identifiers.
• Use Appropriate Log Levels: Differentiate between informational messages, warnings, and errors using standard log levels (e.g., INFO, WARNING, ERROR).
• Centralize Logs: For production deployments, always configure remote logging to ensure logs are safe, accessible, and easily searchable.
• Monitor Logs Regularly: Set up alerts for critical errors and periodically review logs for unusual patterns or performance issues.
• Consider Structured Logging: For advanced analysis, explore using structured logging formats (like JSON) which can be easily parsed by log aggregation tools.

Customizing Log Formatting

You can customize the format of your log messages by defining a custom logging configuration class. This allows you to include specific metadata or structure your logs in a way that integrates well with your monitoring tools.

Refer to the official Airflow Configuration Reference for detailed logging parameters.