Kyle McChesney
10/03/2024, 7:39 PMMarvin
10/03/2024, 7:39 PMPREFECT_LOGGING_[PATH]_[TO]_[KEY]
, allowing you to customize logging paths and levels. For example, setting PREFECT_LOGGING_LEVEL="DEBUG"
changes the default logging to DEBUG level.
2. AWS CloudWatch Setup:
To integrate with AWS CloudWatch, you can use a custom Python logging handler that pushes logs to CloudWatch. You'll need to install the AWS SDK for Python (Boto3) and set up a CloudWatch log handler. Here's a basic example:
- Install Boto3:
shell
pip install boto3
- Create a CloudWatch log handler:
python
import logging
from watchtower import CloudWatchLogHandler
# Define the CloudWatch log handler
cloudwatch_handler = CloudWatchLogHandler(log_group="your-log-group-name")
cloudwatch_handler.setLevel(<http://logging.INFO|logging.INFO>)
3. Combine Handlers:
You can now set up a logger that logs to both the Prefect API and CloudWatch:
python
logger = logging.getLogger('prefect')
logger.setLevel(<http://logging.INFO|logging.INFO>)
# Add the CloudWatch handler
logger.addHandler(cloudwatch_handler)
# Prefect logger already configured, or configure another handler as required
By setting up the above configuration in your application or flow, logs will be sent to both endpoints.
References:
- Prefect 2.x Logging Documentation: https://docs-2.prefect.io/latest/guides/logs/
- Prefect 3.x Logging Documentation: https://docs-3.prefect.io/3.0/develop/logging
You'll need to ensure that your AWS credentials and permissions for CloudWatch are appropriately configured for the environment you are running the Prefect flows in.Bring your towel and join one of the fastest growing data communities. Welcome to our second-generation open source orchestration platform, a completely rethought approach to dataflow automation.
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