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Comment by abd12 | Hacker News Reader

True! I'm not a huge fan of Aurora Serverless and the Data API. The scaling for Aurora Serverless is slow enough that it's not really serverless, IMO. And the Data API adds a good bit of latency and has a non-standard request & response format, so it's hard to use with existing libraries. But it's definitely an option for those that want Lambda + RDBMS.

The RDS Proxy is _hopefully_ a better option in this regard but still early.

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Differing opinion - I think RDS Proxy is the wrong approach. Adding an additional fixed cost service to enable lambda seems like an indicator of a bad architecture. In this case the better approach would likely be to just use a Fargate container which would have a similar cost and fewer moving parts.

By the time you pay a fixed cost for the proxy on top of what you already pay for the RDS server, it'd be a far simpler architecture with less moving parts to just run a Fargate container (or better yet, AWS would offer a Google Cloud Run competitor)

The Data API, while still rough around the edges, at least keeps the solution more "serverless-y". Over time it should get easier to work with as tooling improves. At the very least, it won't be more difficult to work with than DynamoDB was initially with it's different paradigm.

For services that truly require consistently low latency, lambda shouldn't be used anyway, so the added latency of the data api shouldn't be a big deal IMO.

For those reasons, I view the RDS Proxy as an ugly stopgap that enables poor architecture, whereas the Data API actually enables something new, and potentially better. So I'd much rather AWS double down on it and quickly add some improvements.

I agree completely. We have APIs that are both used by our website and our external customers (we sell our API for our customers to integrate with their websites and mobile apps) and for batch loads for internal use.

We deploy our APIs to Fargate for low, predictable latency for our customers and to Lambda [1] which handles scaling up like crazy and scaling down to 0 for internal use but where latency isn’t a concern.

Our pipeline deploys to both.

[1] As far as being “locked into lambda”, that’s not a concern. With API Gateway “proxy integration” you just add three or four lines of code to your Node/Express, C#/WebAPI, Python/Flask code and you can deploy your code as is to lambda. It’s just a separate entry point.

https://github.com/awslabs/aws-serverless-express

https://aws.amazon.com/blogs/developer/deploy-an-existing-as...

Yup, that's exactly how I recommend clients to write lambdas for API purposes... Such a great balance of getting per request pricing while retaining all existing tooling for building APIs

For an internal API with one or two endpoints, I‘ll do things the native Lambda way. Your standard frameworks are heavy when all you need to do is respond to one or two events and you can do your own routing, use APIGW and API Key for authorization, etc.

There is also a threshold between “A group of developers will be developing this API and type safety would be nice so let’s use C#” and “I can write and debug this entire 20-50 line thing in the web console in Python, configure it using the GUI, and export a SAM CloudFormation template for our deployment pipeline.”

> By the time you pay a fixed cost for the proxy on top of what you already pay for the RDS server, it'd be a far simpler architecture with less moving parts to just run a Fargate container

A lot of people want to use lambda (or serverless) even so. So AWS is just accommodating their wishes.

We can’t use Aurora Serverless even in our non Prod environments because we have workflows that involving importing and exporting data to and from S3. But really, our Aurora servers in those environments are so small that most of our costs are storage.

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