@Anna Geller I’m still working on implementing the aws-lambda-serverless-flow template example. On a closer look at the repo, I can see that you didn’t build deployment with prefect(no deployment scripts). Was this intentional or an omission? My attempt to build and apply deployment led to this error:`File "/home/ec2-user/.servy/lib/python3.9/site-packages/botocore/handlers.py", line 278, in validate_bucket_name` raise ParamValidationError(report=error_msg) botocore.exceptions.ParamValidationError: Parameter validation failed: Invalid bucket name “s3“ Bucket name must match the regex “^[a-zA-Z0-9.\-_]{1,255}$” or be an ARN matching the regex “^arn:(aws).:(s3|s3-object-lambda):[a-z\-0-9][0 9]{12}accesspoint[/:][a-zA-Z0-9\-.]{1,63}$|^arn:(aws).*s3 outposts[a-z\-0-9]+[0 9]{12}outpost[/][a zA Z0 9\ ]{1,63}[/]accesspoint[/:][a-zA-Z0-9\-]{1,63}$”

Lambda is what deploys and runs those flows, not Prefect. Check out https://github.com/anna-geller/prefect-aws-lambda/blob/master/serverless.yml and the accompanying Blog post to get a better picture of how this works

@Anna Geller I have deployed successfully but no data is being written to my s3 bucket and I cant see anything on my ui

What UI - do you mean flow run from Lambda is not recorded in the Prefect backend? If so, then you didn't set the PREFECT_API_URL of your Prefect Cloud workspace

@Anna Geller Got it! Thanks. This literally means I can safely do away with the “stop and start ec2 schedule” to run my flow, I had under prefect 1. Wow!!👏

Yeah exactly 💯

@Anna Geller I however observed that in the Dockerfile wherein we are pulling from

public.ecr.aws/lambda/python:3.9

doesn’t allow installation from requirement.txt file. I have tried by copying the

requirement.txt

file and running

pip install -r requirement.txt

but alway end with error that “no such file found”.-cant’ build. What do you think could be wrong? Although I observed in the template you install the packages directly.

try:

ADD requirements.txt .

you can also list packages this way:

RUN pip install prefect requests pandas package1 package2 package3 package4

@Anna Geller ok. meanwhile last question on this serverless with lambda. I have a directory :

engineroom

inside it I have several

.py

files each with a task function. also inside this directory I have

engineroom.py

in this py file I imported the various task function which I called under a flow e.g

from nnfm import get_nnfm_ideas

from sofia import get_sofia_ideas

@flow(name="run all ideas")

def gather_all_ideas():
        get_nnfm_ideas()
        get_sofia_ideas()
#def handler(event,context):
      gather_all_ideas()
if __name__ == "__main__":
    gather_all_ideas()

I was able to run locally successfully by doing:

python engineroom/engineroom.py

My challenge is how to represent in

Dockerfile

and the

serverless.yml

file to run “serverlessly” I have tried but all I get is “module engineroom not found” sorry for taking your time!

You would need to copy the whole directory and add it to Pythonpath or build a package within your image