okdata-aws 0.3.1

Collection of helpers for working with AWS

okdata-aws

Collection of helpers for working with AWS.

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 okdata.aws import logging
from okdata.aws.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 okdata.aws.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 okdata.aws.logging import logging_wrapper, log_exception

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

Status wrapper

The status wrapper logs details about a Lambda function execution and sends it to the status API.

The first component that touches the data (typically on upload) sets a "trace ID", which is then inherited by the following processing steps. This allows the status API to track what has happened to the data, from upload through the various processing steps until the data is ready for consumption.

For pipeline components, the status wrapper picks up the trace ID from the Lambda event automatically.

The status wrapper expects the SERVICE_NAME of the Lambda component to be set in an environment variable, along with GIT_REV and GIT_BRANCH.

Usage

Tag the Lambda handler function with @status_wrapper.

The handler function should set the domain and domain_id values using the status_add method:

from okdata.aws.status import status_wrapper, status_add

@status_wrapper
def my_lambda_handler(event, context):
    status_add(domain="dataset", domain_id=f"{dataset_id}/{version}")

    # Regular handler logic here ...

    # The handler can also add a body object containing component-specific information
    status_body = {
        "input": "/tmp/file.txt",
        "output": "/tmp/file.csv",
        "transformation": "text-to-csv",
    }
    status_add(status_body=status_body)

By default, this will send a status event with event status OK and trace status CONTINUE, meaning that the data pipeline is still running. If the handler function fails, e.g. throws an exception, it will send event status FAILED and trace status FINISHED, in addition to the failure details (exception).