zappa | Manipulate audio with Ruby | Data Migration library

You have an exception being thrown in your code. I have found NoneType is a generic error when using AWS Lambda & Zappa that is masking the true issue.

Some debugging steps:

1. Ensure your code works locally when you run python manage.py runserver
2. Output console messages in various places in your code and run zappa tail to identify the section of code that is having troubles
3. Repeat above option until you have narrowed the location of the problem.

With some extra precautions for security and to prevent inadvertent string extrapolation, you can combine Invoke-Expression with Write-Output, though note that Invoke-Expression should generally be avoided:

I got around this by adding the following permissions to the group my user belongs to:

Have you tried pushing them into an array?

the most direct way to overcome the issue is by adding

in config/deploy.rb ensure that

append :linked_dirs, node_modules is included
then run yarn install --check-filesfrom within the latest repository.

1. API Gateway is a service that allows you to create a RESTful APIs. I assume that's exactly what you need if you like to deploy some APIs as you mentioned. EventBridge is a serverless event bus where you can publish events and configure your lambdas to consume those. That's what you use for decoupled communication. E.g. if a POST to your API Gateway creates a new user to your app then your Lambda could dispatch an event "USER_CREATED" into EventBridge event bus. An other Lambda can then subscribe to event "USER_CREATED" and send a welcome email. CloudWatch Events are just timer based EventBridge events that are published to event bus. In that case you could e.g. create a rule that notifies your Lambdas every morning to run some background task. Sending a daily marketing email to your customers could be one such use case.

2. I don't think there is a sigle best practise. It can be more simple to start with one Lambda serving multiple API endpoints. You can also think what kind of permissions and resources/databases your Lambdas need. One example is to divide Lambdas to the command and query Lambdas. That way POST, PATCH, PUT and DELETE could call one Lambda that has write permissions to your database. Then GET endpoints are handled with another Lambda that has only read permissions to your database. This read lambda could use in the future some different kind of database that is optimized for queries. These are just some things to consider when your application grows.

When the documentation talks about "Flask's built-in server", it's talking about the server that you get when you run the command flask run (or in older applications running a command like python my_application.py with a line in the main function like app.run()).

When you run flask on Lambda (using Zappa or another solution like aws-wsgi or serverless-wsgi), you're not using Flask's built-in server or any server at all; the wrapper code (in Zappa or anything else) is translating the lambda event to a call to your WSGI application.

Since there is no actual WSGI server, it's not possible to use Gunicorn, uWGSI, etc (well, it may be possible, but it would be very convoluted).

It's best practice not to use AWS Secret & Access Keys inside code if you are using Lambda Function. You should modify your Lambda Function's Execution Role and add the required permissions for accessing S3 and DynamoDB.

But if you choose not to use Lambda Function's Execution Role, you have many options to store your AWS Secret & Access Keys:

1. Store them in Lambda Function's Environment Variables. (not recommended)
2. Store them in AWS SSM Parameter Store as a Secure String.
3. Store them in AWS Secrets Manager.

But I recommend you to modify your Lambda Function's Execution Role and add the required permissions for accessing any AWS service in your case S3 and DynamoDB.