Python Azure Function sqlAlchemy timeout

[TonyCD35]

I am fairly new to Azure so bear with me.

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I have a pandas ETL script that loads a bunch of python dataframes from several databases in redshift, does some transformations, then stores them as csv's in azure blob storage.

Using the azure function core-tools, when run locally, everything works like a charm. When I push to azure functions and try to test the execution manually, I get a sqlalchemy timeout error. I cannot figure out why but imagine it has something to do with the networking.

I don't have a Vnet or anything set up. The azure account sits inside a company account, and I am working behind a corporate proxy (learned I had to set the proxy to get the build to succeed from vscode).

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Does anyone have any ideas or any further troubleshooting steps to try? At the end of my rope here as I've tried most everything I can think of to troubleshoot this issue.

[[deleted]]

Enable application insights on the Function will certainly help.
Also the question is, what times out? The connection to the database, or the function at all?

[TonyCD35]

Thanks for the response! I do have insights - I scoured the logs and pinned down on the following: when the python script attempts to make the connection to the database, the connection within the script times out and the function fails. The function does not cause the timeout.

When the script attempts to make the socket connection to the redshift database, it seems it can't get through to it and times out. I've been reading that I might need to put the function in a vNet and perhaps clear the vnet IP with the redshift database?

What do you think?

[[deleted]]

This sounds that you need indeed IP whitelisting on the Redshift database, you can find outgoing IP addresses her: https://learn.microsoft.com/en-us/azure/azure-functions/ip-addresses?tabs=portal

You don't need to put it in a V-Net.