Consider this situation: you have a zip file stored in an Azure Blob Storage container (or any other location for that matter). This isn’t just any zip file; it’s large, containing gigabytes of data. It could be big data sets for your machine learning projects, log files, media files, or backups. The specific content isn’t the focus - the size is.

The task? We need to unzip this massive file(s) and relocate its contents to a different Azure Blob storage container. This task might seem daunting, especially considering the size of the file and the potential number of files that might be housed within it.

Why do we need to do this? The use cases are numerous. Handling large data sets, moving data for analysis, making backups more accessible - these are just a few examples. The key here is that we’re looking for a scalable and reliable solution to handle this task efficiently.

Azure Data Factory is arguably a better fit for this sort of task, but In this blog post, we will specifically demonstrate how to establish this process using Azure Functions. Specifically we will try to achieve this within the constraints of the Consumption plan tier, where the maximum memory is capped at 1.5GB, with the supporting roles of Azure CLI and PowerShell in our setup.

Setting Up Our Azure Environment

Before we dive into scripting and code, we need to set the stage - that means setting up our Azure environment. We’re going to create a storage account with two containers, one for our Zipped files and the other for Unzipped files.

To create this setup, we’ll be using the Azure CLI. Why? Because it’s efficient and lets us script out the whole process if we need to do it again in the future.

1. Install Azure CLI: If you haven’t already installed Azure CLI on your local machine, you can get it from here.

2. Login to Azure: Open your terminal and type the following command to login to your Azure account. You’ll be prompted to enter your credentials.

   1

   az login

3. Create a Resource Group: We’ll need a Resource Group to keep our resources organized. We’ll call this rg-function-app-unzip-test and create it in the eastus location (you can ofcourse choose which ever region you like).

   1	az group create --name rg-function-app-unzip-test --location eastus

This secures our function app and it isn’t available publicly, any one that tries to access our function app url will get “HTTP 403 Forbidden”.

This secures our function app; now what about deploying code changes to the function app via GitHub Actions? we should be able to CI/CD to our function app, but there is a problem here. The GitHub action will fail with the same “HTTP 403 Forbidden”, this is because GitHub actions run on runners (its a hosted virtual environment), each time we run the Action we get a new runner and it can have a different ip address. So how can we get around this? do we white list the entire GitHub ip range?

GitHub’s ip ranges can change any time, so will have to keep scanning for changes to these ranges and proactively update our ip restrictions, this is not very scalable or practical. So what are other ways of getting around this? we have a couple of ways to get around this.

Possible Solutions

There are two viable solutions here

Here is a scenario that I recently encountered. Imagine we are building micro-services using serverless (a mix on Azure Function Apps and Logic Apps) with APIM in the front. Lets say we went with the APIM standard instance and all the logic and function apps are going to be running on consumption plan (for cost reasons as its cheaper). This means we wont be getting any vnet capability and our function and logic apps will be exposed out to the world (remember to get vnet with APIM we have to go with the premium version, we are going APIM standard here for cost saving reasons).

So how do we restrict our function and logic apps to only go through the APIM, in another words all our function and logic apps must only go through the APIM and if anyone tries to access them directly they should be getting a “HTTP 403 Forbidden”.

Lets visualize this scenario; We have some WAF capable ingress endpoint, in this case its Azure Front Door, that is forwarding traffic to APIM which then sends the requests to the serverless apps.
Reason for having Front Door before APIM is because APIM doesn’t have WAF natively so we will need to put something in front of it that has that capability to be secure.

There are few options like Azure Firewall, Application Gateway etc, but for the purposes of this scenario we have Azure Front Door in front of APIM (and we can have an APIM policy that will only accept traffic from Azure Font Door, we wont be going in to that, we will keep it to securing our function apps to just being available via APIM for today)