I'm trying to deploy an AWS Lambda app that I was handed, But I'm not sure whether I should connect to it using a function URL or an API gateway, it's my fist time working with Lambdas so I don't even know how to tell. Do apps work with both or is there something in the serverless.yml file that could tell me which one to use?
When I try the API gateway, I don't know whether to use HTTP or REST, or whether to use cors, and whichever one I choose I don't know how to expose the X-CSRF-Token header. When I try using the Function URL, I can do that, but I get a 502 bad gateway error and a KeyError: 'path' in the logs.
Related
I created my Lambda Functions and their routes in the API Gateway within the AWS Console. The functions all work within the Testing Tab in Lambda on the console. My React app is very standard and will be pushed to AWS Amplify.
I cannot find any resources on how to correctly invoke the deployed link of my API Gateway from my frontend. Before when working with a local backend, I was able to invoke my backend from my frontend easily with Axios. I tried using axios in my ReactJS frontend with the URL for my API Gateway, but this led to several errors as well such as (No Authentication Token) and (No Access-control-allow-origin header). I've spent hours looking and trying different things to resolve those but every time I always come back to where I started.
Looking for some direction, thank you in advance.
No Authentication Token will come if on you are not passing required auth token.
Access-control-allow-origin will be there if you have not enabled CORS on api gateway resource and also you need to pass cors headers in response from your lambda if you are using LAMBDA_PROXY integration. For more details refer this.
I'm developing several AWS serverless applications using Lambda and API gateway.
At one point, I tried to execute an API request on one application (using requests python lib) from code running inside a Lambda function in another application. I get 500 server error. From the logs it appears that the Lambda function behind the API gateway is not starting at all. I don't find any logs that can tell me what happened.
Additional details:
The API gateway is protected by IAM auth.
The calling lambda has permission to "execute_api"
The request is signed according to Signature V4 - I followed the example here: https://docs.aws.amazon.com/general/latest/gr/sigv4-signed-request-examples.html#sig-v4-examples-post .
The issue was that the calling lambda needed permission to execute the second lambda behind the API gateway. I don't know why that is. I also still don't know how I should have debugged this - where are the logs that should tell me what was the issue. Eventually it was a lucky guess on my side.
I am very new to AWS Lambda and am struggling to understand its functionalities based on many examples I found online (+reading endless documentations). I understand the primary goal of using such service is to implement a serverless architecture that is cost and probably effort-efficient by allowing Lambda and the API Gateway to take on the role of managing your server (so serverless does not mean you don't use a server, but the architecture takes care of things for you). I organized my research into two general approaches taken by developers to deploy a Flask web application to Lambda:
Deploy the entire application to Lambda using zappa-and zappa configurations (json file) will be the API Gateway authentication.
Deploy only the function, the parsing blackbox that transforms user input to a form the backend endpoint is expecting (and backwards as well) -> Grab a proxy url from the API Gateway that configures Lambda proxy -> Have a separate application program that uses the url
(and then there's 3, which does not use the API Gateway and invokes the Lambda function in the application itself-but I really want to get a hands on experience using the API Gateway)
Here are the questions I have for each of the above two approaches:
For 1, I don't understand how Lambda is calling the functions in the Flask application. According to my understanding, Lambda only calls functions that have the parameters event and context-or are the url calls (url formulated by the API Gateway) actually the events calling the separate functions in the Flask application, thus enabling Lambda to function as a 'serverless' environment-this doesn't make sense to me because event, in most of the examples I analyzed, is the user input data. That means some of the functions in the application have no event and some do, which means Lambda somehow magically figures out what to do with different function calls?
I also know that Lambda does have limited capacity, so is this the best way? It seems to be the standard way of deploying a web application on Lambda.
For 2, I understand the steps leading to incorporating the API Gateway urls in the Flask application. The Flask application therefore will use the url to access the Lambda function and have HTTP endpoints for user access. HOWEVER, that means, if I have the Flask application on my local computer, the application will only be hosted when I run the application on my computer-I would like it to have persistent public access (hopefully). I read about AWS Cloud9-would this be a good solution? Where should I deploy the application itself to optimize this architecture-without using services that take away the architecture's severless-ness (like an EC2 instance maybe OR on S3, where I would be putting my frontend html files, and host a website)? Also, going back to 1 (sorry I am trying to organize my ideas in a coherent way, and it's not working too well), will the application run consistently as long as I leave the API Gateway endpoint open?
I don't know what's the best practice for deploying a Flask application using AWS Lambda and the API Gateway but based on my findings, the above two are most frequently used. It would be really helpful if you could answer my questions so I could actually start playing with AWS Lambda! Thank you! (+I did read all the Amazon documentations, and these are the final-remaining questions I have before I start experimenting:))
Zappa has its own code to handle requests and make them compatible with the "Flask" format. Keep in mind that you aren't really using Flask as intended in either cases when using Lambda. Lambdas are invoked only when calls are made, flask usually keeps running looking for requests. But the continuously running part is handled by the API Gateway here. Zappa essentially creates a single ANY request on API gateway, this request is passed to your lambda handler which interprets it and uses it to invoke your flask function.
If you you are building API Gateway + Lambda you don't need to use Flask. It would be much easier to simply make a function that is invoked by the parameters passed to lambda handler by the API Gateway. The front end application you can host on S3 (if it is static or Angular).
I would say the best practice here would be to not use Flask and go with the API Gateway + Lambda option. This lets you put custom security and checks on your APIs as well as making the application a lot more stable as every request has its own lambda.
I get an error while invoking the AWS SageMaker endpoint API from a Lambda function. When I call this using Postman, I am getting an error like:
{
"errorMessage": "module initialization error"
}
Just to make it clear, you can't call SageMaker endpoints directly using PostMan (even if it is, it would not be straightforward).
You may need to use AWS SDK (i.e. boto) for that.
Ref : https://aws.amazon.com/blogs/machine-learning/call-an-amazon-sagemaker-model-endpoint-using-amazon-api-gateway-and-aws-lambda/
What I would suggest is to create a small HTTP server with Flask and use the AWS SDK (Boto) to call the endpoint. Then you can call your Flask endpoint using PostMan.
We recommend using AWS SDK to invoke your endpoint. AWS SDK clients handle the serialization for you as well as request signing, etc. It would be really hard to get it right manually with postman.
We have the SDK client available in many languages, including Java, Python, JS, etc.
https://docs.aws.amazon.com/sagemaker/latest/dg/API_runtime_InvokeEndpoint.html#API_runtime_InvokeEndpoint_SeeAlso
Next time please include more details in your question. eg. POST request data, Headers etc.
Anyways, to help you out in calling Sagemaker endpoint using Postman -
In 'Authorization' tab, select type as 'AWS Signature'.
Enter your Access and Secret key of the IAM user which has permission to Sagemaker resources.
Enter the AWS region. eg.us-east-1
Enter 'Service Name' as 'sagemaker'
Select the right content type. Some ML algorithms only accept 'text/csv'.
Select request type as 'POST'
Enter the Sagemaker Invocation url. eg:'https://runtime.sagemaker.us-east-1.amazonaws.com/endpoints/xgboost-xxxx-xx-xx-xx-xx-xx-xxx/invocations'
Try it out and let me know if you have any issues.
Here is how your Postman should look -
I am using VPC link in API GATEWAY to connect to rest service in EC2 instance. However, octet stream responses are not getting correctly passed through. Error getting at client side is "Make sure you are passing in a Gzip Stream". Do I need to make any changes in API gateway or in Spring REST service headers? REST service returns the correct response if invoked directly.
Hurray! Resolved it.
Added "Accept-encoding" : "identity" header in client side.
in API Gateway setting, enabled "content encoding".
worked like a charm :)
PS: Make sure you deploy the API even though it is just settings!!