Klayers VS Zappa

Use public layers maintained by others. For example Klayers which are produced with CI in GitHub Actions. This way you don't have any layers lying around in your Lambda UI. You can point to new layer versions whenever you wish. You can interact with the layer data via an API : https://github.com/keithrozario/Klayers/#api

If I want to do something more data heavy or complex, I'll sometimes instead go for Python. Having a mixture of languages is one of the big advantages of micro services. Packaging dependencies is a bit tricker for Python, for simple packages I'll usually include in my build script something to copy the relevant directories from my venv's site-packages. However one neat alternative is to use a publicly available precompiled lambda layer from Klayers. These slot neatly in one line of code into my terraform config and enable me to use popular Python packages like numpy and pandas without troubling myself about C extensions, build environment or having to mess with Amazon Linux.

Before anything, Huge shoutout to Keith Rozario for providing us with this awesome Repo. where he defined layers for lambda functions to add libraries that doesn't exist by default in the lambda runtime without you having to create them yourself. I used his repo to add the requests, pandas and psycopg2 libraries to the project.

I like to use this guy’s layers as an arn: https://github.com/keithrozario/Klayers

Another alternative is Zappa which is built-in Python Serverless Framework and it serves only that runtime on AWS.

Also, Zappa core team is looking for contributors to manage the project. I don't know why someone would leave a project like this. It had nearly 12k stars on original repo here https://github.com/Miserlou/Zappa and has around 1.7k on the new one.

I used to work for a startup that quickly grew to become one of the biggest Lambda users in my country (according to AWS). The entire business was serverless, not just Lambda but backend DynamoDB, APIGW, Cloudfront, etc. There was maybe 2 EC2 instances in the whole company.

Having seen what that model of development can do from an operational/security/agility/scalability/efficiency perspective, I think the comments on HN about serverless saying "it's just CGI" or that they could do something similar without vendor lockin are honestly laughably ignorant. If you haven't messed with Zappa (https://github.com/Miserlou/Zappa) or Serverless Framework (https://www.serverless.com/) at least a little you are missing out.

I'm using the Zappa framework https://github.com/Miserlou/Zappa with Python and Flask on AWS Lambda. When it raises an exception it appears in the CloudWatch log but is illegible to me. I do get a normal Flask stack trace returned from a HTTP GET in debug builds however.

I have a Python 3.6 - Flask application deployed onto AWS Lambda using Zappa, in which I have an asynchronous task execution function defined using @Task as discussed here

The only similar issue I can find in my Google searches is this page, but I don't know if it's the same issue and the discussion there is going over my head.

Hi u/appliku I think Zappa has been moved from https://github.com/Miserlou/Zappa repo to its own repo and account https://github.com/zappa/Zappa Also, they released version 0.54.0 (Minor version) on Oct 14.

I like deploying on AWS Fargate or AWS Lambda using zappa for very low-cost deployments. Because Lambda has a (always) free tier usage, you can get away with hosting many sites for next-to-nothing with Zappa.

Depending on what you need zappa (https://github.com/Miserlou/Zappa) allows you to run Django in aws lambda which is very cheap (read practically free).