issue_comments

Oh, and the container image can be up to 10GB, so the EFS step might not be needed except for pretty big stuff.

Now that Lambda supports Docker, this probably is a bit easier and may be able to build on top of the existing package command.

There are weirdnesses in how the command actually gets invoked; the aws-lambda-python image shows a bit of that. So Datasette would probably need some sort of Lambda-specific entry point to make this work.

I made a repo at https://github.com/code402/datasette-lambda to demonstrate the idea, and scratch my personal itch for this.

The demo relies on some central authority having already published a public, reusable Lambda layer with Datasette & its dependencies. I think that differs from the other publish plugins which seem to mainly publish Dockerfiles that the host will interpret to install deps from a requirements.txt file.

I chose that approach because uvloop appears to be a dependency with native code that needs to be compiled for the target runtime environment. In this case, that's Amazon Linux 2. I'm not 100% clear on whether that's still required, because:

• maybe uvloop is only needed for uvicorn, which the demo doesn't actually use since HTTP routing is handled by API Gateway
• it seems like uvloop may be an optional, drop-in optimization for asyncio in any case (but I may be misreading this; I'm very much a Python noob)

If it's the case that uvloop is truly optional, then I think the publish plugin could do the packaging on the user's machine, regardless of what flavour of operating system they're on. That'd be a bit slower for the user, but would provide the most long-term flexibility in terms of supporting plugins.

Hi Simon,

I'm thinking of attempting this. Can you clarify some questions I have?

1) I assume the goal is to have a CORS-friendly HTTPS endpoint that hosts the datasette service + user's db.

2) If that's the goal, I think Lambda alone is insufficient. Lambda provides the compute fabric, but not the HTTP routing. You'd also need to add Application Load Balancer or API Gateway to provide an HTTP endpoint that routes to the lambda function.

Do you have a preference between ALB or API GW? ALB has better economics at scale, but has a minimum monthly cost. API GW has worse per-request economics, but scales to zero when no requests are happening.

3) Does Datasette have any native components, or is it all pure python? If it has native bits, they'll likely need to be recompiled to work on Amazon Linux 2.

4) There are a few disparate services that need to be wired together to expose a Python service securely to the web. If I was doing this outside of the datasette publish system, I'd use an AWS CloudFormation template. Even within datasette, I think it still makes sense to use a CloudFormation template and just have the publish plugin invoke it (via the standard aws cli) with user-specified parameters. Does that sound reasonable to you?

Thanks for your help!