Logging for Lambda

Based on Structlog.

Structured and enriched logging for AWS Lambda functions.

TL;DR:

• Decorate handler with logging_wrapper
• Encrich logs with key/value pairs using log_add
• Time functions with log_duration
• Log exceptions with log_exception

Usage

Wrap your lambda handler with logging_wrapper. Badabing badabom, you're good to go!

You can set the service name using the logging.init method, or configure it using the SERVICE_NAME environment variable.

from dataplatform.awslambda import logging
from dataplatform.awslambda.logging import logging_wrapper

logging.init("my_fantastic_lambda")

@logging_wrapper
def handler(event, context):
    if error:
        return {
            "statusCode": 500,
            "body": "Automatically logs bodies from error responses even!",
        }

Encriching logs

By automagic logs will be enriched with git revisions, cold start y/n call duration and much more, but to add even more magic you can use log_add and log_duration.

from dataplatform.awslambda.logging import logging_wrapper, log_add, log_duration

@logging_wrapper
def handler(event, context):
    log_add(dataset=event["dataset"], foo=context["foo"])
    log_duration(
        lambda: slow_thinger(event["dataset"]),
        "my_slow_thinger"
    )
    ... and so on

def slow_thinger():
    sleep(9999999999999999)

Exceptions

Struct log can extract exception info if we log the exception to the special exc_info key.

For convenience we catch and log uncaught exceptions using this already.

If you need to process an exception you can use log_exception to log it to the exc_info key.

from dataplatform.awslambda.logging import logging_wrapper, log_exception

@logging_wrapper
def handler(event, context):
    try:
        thing()
    except MyException as e:
        log_exception(e)
        return { ... }