Worker Configuration

AIMQ workers can be configured through both environment variables and programmatic settings. This guide covers all available configuration options and best practices.

Environment Variables

The following environment variables control worker behavior:

Variable	Description	Default
WORKER_NAME	Name of the worker instance	'peon'
WORKER_LOG_LEVEL	Logging level (debug, info, warning, error)	'info'
WORKER_IDLE_WAIT	Time to wait between queue checks (seconds)	10.0

Programmatic Configuration

You can configure workers programmatically when creating a Worker instance:

from aimq import Worker

worker = Worker(
    name="custom-worker",      # Override worker name
    log_level="debug",        # Set logging level
    idle_wait=5.0            # Set idle wait time
)

Configuration Precedence

Configuration values are determined in the following order (highest to lowest priority): 1. Programmatic configuration 2. Environment variables 3. Default values

Worker Settings

Name

The worker name is used to identify the worker instance in logs and monitoring:

# Via environment
WORKER_NAME=analytics-worker

# Via code
worker = Worker(name="analytics-worker")

Log Level

Control the verbosity of worker logs:

# Via environment
WORKER_LOG_LEVEL=debug

# Via code
worker = Worker(log_level="debug")

Available log levels: - debug: Detailed debugging information - info: General operational information - warning: Warning messages for potential issues - error: Error messages for actual problems

Idle Wait

Configure how long the worker waits between checking for new tasks:

# Via environment
WORKER_IDLE_WAIT=5.0

# Via code
worker = Worker(idle_wait=5.0)

Best Practices

1. Worker Names
2. Use descriptive names that indicate the worker's purpose
3. Include environment or region in the name if relevant

4. Example: prod-us-east-analytics-worker

5. Log Levels

6. Use debug during development
7. Use info in production

8. Use warning or error for minimal logging

9. Idle Wait

10. Lower values (1-5s) for time-sensitive tasks
11. Higher values (10-30s) for background tasks
12. Consider queue volume when setting this value

Example Configurations

Development Environment

# .env
WORKER_NAME=dev-worker
WORKER_LOG_LEVEL=debug
WORKER_IDLE_WAIT=5.0

Production Environment

# .env
WORKER_NAME=prod-analytics
WORKER_LOG_LEVEL=info
WORKER_IDLE_WAIT=10.0

Mixed Configuration

# .env
WORKER_NAME=prod-worker
WORKER_LOG_LEVEL=info

# code
worker = Worker(
    name=os.getenv("WORKER_NAME"),
    log_level=os.getenv("WORKER_LOG_LEVEL"),
    idle_wait=5.0  # Override default and env
)

Monitoring and Debugging

1. Log Output
2. All worker operations are logged according to log_level

3. Logs include worker name, timestamp, and operation details

4. Performance Tuning

5. Monitor worker performance with different idle_wait values

6. Adjust based on queue volume and task processing time

7. Multiple Workers

8. Use different names for each worker instance
9. Configure log levels independently for focused debugging