Description
Is this related to an existing feature request or issue?
Which AWS Lambda Powertools utility does this relate to?
Logger
Summary
This RFC is the first of three that will detail how the Logger, Metrics, and Tracer utilities can be extended to support a bring-your-own-observability-provider format for customers who want to use platforms other than AWS CloudWatch.
This RFC will be specifically for the Logger. Currently, in the Logger for Python (and Typescript), customers can bring their own Logging Formatter and have the option to provide a configuration option to define the output format when they're setting up their Logger in order to allow for better integration with observability solutions other than CloudWatch.
Since this is already quite powerful, we are seeking to improve the existing mechanism by offering out of the box support for Datadog and a few other providers (TBD) for the Logger Formatter.
Metrics RFC: #2015
Tracer RFC: #2030
Use case
The primary use case for this utility would be for developers who want a simplified way to integrate the Logger Formatter with the most popular third party observability providers (ie. DataDog).
Proposal
Current Logger Formatter experience
Below is a simple snippet of how the Logger Formatter currently works:
from aws_lambda_powertools import Logger
from aws_lambda_powertools.logging.formatter import LambdaPowertoolsFormatter
class CustomFormatter(LambdaPowertoolsFormatter):
def serialize(self, log: dict) -> str:
"""Serialize final structured log dict to JSON str"""
log["event"] = log.pop("message") # rename message key to event
return self.json_serializer(log) # use configured json serializer
logger = Logger(service="payment", logger_formatter=CustomFormatter())logger.info("hello")
logger = Logger(service="payment", logger_formatter=CustomFormatter())
logger.info("hello")
Output
{
"level": "INFO",
"location": "hello_name:8",
"event": "Request from Alice received",
"timestamp": "2023-03-21 13:25:36,129+0100",
"service": "service_undefined"
}
Logger Formatter proposal
For this new utility, we propose a new parameter to the existing logger that developers can use to specify which observability provider they would like to receive their logs. The below code snippet is a rudimentary look at how this utility can be used and how it will function. Out of the box, we will support DataDog and a few other providers (TBD).
from aws_lambda_powertools import Logger
from aws_lambda_powertools.logging.providers import DatadogLogFormatter
logger = Logger(service="payment", logger_formatter=DatadogLogFormatter())
logger.info("hello")
Output
{
"datetime": "2021-11-22 15:32:02,145",
"level": "INFO",
"message": "Request from Alice received",
"requestId": "9b1deb4d-3b7d-4bad"
}
Custom logger usage
If the customer would like to use another observability provider, or define their own logger functions, we will define an interface that the customer can implement and pass in to the Logger class.
Out of scope
Sending logs from Powertools to the customer's desired observability platform will not be in the scope of this project. The implementation should only support modifying the output of the Logger so that the customer can push them to their platform of choice using the Lambda Handler.
Potential challenges
We need to determine which platforms we want to support out-of-the-box (apart from Datadog).
Dependencies and Integrations
We will have to integrate with (and thus, have a dependency on) Datadog and any other platforms we decide to support out-of-the-box.
Alternative solutions
Acknowledgment
- This feature request meets Lambda Powertools TenetsShould this be considered in other Lambda Powertools languages? i.e. Java, TypeScript
Activity
heitorlessa commentedon Mar 21, 2023
reading!
heitorlessa commentedon Mar 21, 2023
Thanks a lot @seshubaws for taking the time in creating this! I'm so excited we're kicking the observability provider discussion.
As I was reading, one thing struck me: only Python and TypeScript already provide this capability. This means we might not need an actual Provider capability but more of an improvement to the ergonomics for customers to bring their own output.
In Python, we use the standard logging library which is absurdly flexible yet why it's so complex to configure it. For Powertools Logger, customers tend to migrate from standard logging library or another loggers. Since we build atop of the standard logging library, we expose the same mechanisms for customers to override and bring their company standards, for example:
In this case,
logger_formatter
would receive an instance ofLambdaPowertoolsFormatter
. Upon a new log that Logger already validated it has the correct logging levels, filters, fields like correlation ID, X-Ray ID, Lambda context and custom keys resolved, etc., it'd callserialize
last and return. What I like about thelogger_formatter
is that it's explicit enough, customers can have additional logic in it, and we do the heavy lifting without them having to worry about logging levels, logging filters, and whatnot - if they do want the trouble, they can useBaseLambdaPowertoolsFormatter
.What I think we could do better here but didn't before is to either think of a simpler way since is already powerful enough, OR improve the existing mechanism by typing the
log
parameter withTypedDict
for example.What do you think?
Answering some comments and questions
Minor correction, Logger sends logs to standard output (stdout). That's why some customers even use it locally for scripts, or in platforms like Fargate/AppRunner/Beanstalk, despite not having access to all features. That's also true for all other languages. The reason we did this is to make it easier for customers to take control over stdout and transform/do as they please, with say sidecar containers... or in case of Lambda... Lambda Extensions Logs API.
We can ask the community. Turns out a customer shared that Logger output is recognized by Datadog out of the box when used with
Logger(use_rfc3339=True)
. I had asked for a docs issue so make this more visible in a FAQ but customer lacked bandwidth (so did we :/).That's an interesting idea - would you mind expanding the RFC to cover an initial take? We heard some ideas in the past of having a central configuration.
Minor edits
python
)Current logger experience
seshubaws commentedon Mar 24, 2023
Thank you for your comments @heitorlessa, it really clarifies a lot! I have revised the original RFC to integrate most of your comments, though I should call out some points:
In the revised RFC, I have proposed supporting Datadog and any other providers we want out of the box to make the current Logger Formatter simpler. We could add the TypedDict in addition to that, or do that as a fast follow, up to you.
I guess if we support Datadog formatting for logs out of the box like
we can just do that behind the scenes.
Also, to determine the other providers we want to support out of the box, is this RFC the place where we are asking? Or is there some other forum for that kind of poll specifically?
Of course! Should we have that in a separate RFC though, since this one is just about the Logger and that would involve Logger, Tracer, and Metrics?
heitorlessa commentedon Mar 31, 2023
awesome, I somehow missed your message @seshubaws (sorry!!). I'm finishing a documentation issue and going through all RFCs today
heitorlessa commentedon Mar 31, 2023
Loved it! Gotta re-read the updated RFC now. As for your questions:
We can use the Poll feature in GitHub Discussions, then drive customers there from our docs, board, Discord, and social media :)
It'll also be good to find out which ones don't work outside the box (only DataDog didn't work out as far as I remember).
Good idea! A new RFC would be better. I did learn from another customer interview last week that they tend to use one Logging provider (e.g., CloudWatch), and use another for Metrics and Traces primarily to optimize costs.
heitorlessa commentedon Mar 31, 2023
That's it! That's exactly the simple developer experience customers love about Powertools - you're awesome @seshubaws!
Feel free to start the implementation (or let us know if you want us to!). Given how related it is, we could also address the
TypedDict
to make the authoring experience even better.I've pinged a Serverless Partner SA for guidance on how to best ensure a fair chance for AWS Partners (whether to support a few out of the box, or do it based on customer demand and Partner's contribution). For now, assume Datadog as an example, as we can revert that easily if we need to.
Thanks
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