Azure Billing Repots

The azure billing reports are an unofficial collection of reports built on top of the Azure Billing API.

Azure provides an hourly usage report for their customers. The azure billing reports use a script to fetch the data and use PowerBI M queries to parse the data info useful fields.

This repository has:

• Scripts to fetch billing related information
• Modern Data Warehouse Architecture for Cost Optimization

Overview

Billing Scripts - Getting Started

• First obtain your enrollment id and a valid api authentication key.
• Run the /scripts/get_usage_data.py script to get the latest billing usage data. This will download and save the billing data into a csv file.
• Run the /scripts/get_ri_recommendations.py script to get the latest reserved instance recommendations.

python get_usage_data.py enrollment_id api_auth_key
python get_ri_recommendations.py enrollment_id api_auth_key
python get_price_list.py enrollment_id api_auth_key

• Open the AzureBillingViaCsv.pbit template file
• Provide the full path to the downloaded csv file.

Building and Deploying

# Build docker image
docker build --pull --rm -f "Dockerfile.dev" -t azurebillingreports:latest "."

# Run docker image
docker run --rm -it --env-file local.env azurebillingreports:latest

# If you want to see STDOUT use
docker run --rm -a STDOUT --env-file local.env azurebillingreports:latest

# Deploy the image to repository. Replace the name <registryname> with the name of your repository. After deploying, this will remove the image from your local Docker environment
az acr login --name  <registryname>
docker tag azurebillingreports <registryname>.azurecr.io/azurebillingreports:v1
docker push <registryname>.azurecr.io/azurebillingreports:v1
docker rmi <registryname>.azurecr.io/azurebillingreports:v1

# Create a container instance with the following:
az container create --resource-group blxbilling --name blxcontainergroup --image blxcontainerregistry.azurecr.io/azurebillingreports:v1 --registry-login-server blxcontainerregistry.azurecr.io --registry-username <acr_username> --registry-password <acr_password> --secure-environment-variables ENROLLMENT_ID=<enrollment_id> BILLING_AUTH_KEY=<billing_auth_key> STORAGE_CONTAINER_NAME=<billingfiles> STORAGE_CONNECTION_STRING=<connection_string> --restart-policy Never

# Deploy with yaml
az container create --resource-group blxbilling --file billing-container.yaml

# Delete instance
az container delete --resource-group blxbilling --name blxcontainergroup

Update Container Environment Variables

# Export the container settings
az container export -g blxbilling --name blxcontainergroup -f output.yaml

# Edit the settings and recreate
az container create -g blxbilling -f output.yaml

# Reset Service Principal credentials
az ad sp credential reset --name name-of-service-principal

Create Docker Image repository

az acr create --resource-group myResourceGroup --name myContainerRegistry007 --sku Basic

Configure Databricks

Azure Databricks is used during the prep phase of the data pipeline.

Configure Secrets

The notebook uses secrets to connect to the storage account. Use the databricsk cli to set a secrets

# Create a secret scope for premium cluster
databricks secrets create-scope --scope billing

# Or Create secret scope for standard cluster
databricks secrets create-scope --scope billing --initial-manage-principal users

# Add secrets to cluster
databricks secrets put --scope billing --key storage_key
databricks secrets put --scope billing --key db_connection
databricks secrets put --scope billing --key db_username
databricks secrets put --scope billing --key db_password

Common Issues

• Request date header too old: 'Mon, 16 Dec 2019 22:00:09 GMT'
  • The docker image time has drifted. Restart docker on host container.
• API Key Expired
  • update the key found in secure environment variables

Development

You'll need to set up a development environment if you want to develop a new feature or fix issues. The project uses a docker based devcontainer to ensure a consistent development environment.

• Open the project in VSCode and it will prompt you to open the project in a devcontainer. This will have all the required tools installed and configured.

Setup local dev environment

If you use the devcontainer image you need to log into the Container registry

# load .env vars (optional)
[ -f .env ] && while IFS= read -r line; do [[ $line =~ ^[^#]*= ]] && eval "export $line"; done < .env

az login --use-device-code --tenant "$AZURE_TENANT_ID"
az acr login --name $REGISTRY_LOGIN_SERVER

If you want to develop outside of a docker devcontainer you can use the following commands to setup your environment.

# Configure the environment variables. Copy example.env to .env and update the values
cp example.env .env

# load .env vars
# [ ! -f .env ] || export $(grep -v '^#' .env | xargs)
# or this version allows variable substitution and quoted long values
# [ -f .env ] && while IFS= read -r line; do [[ $line =~ ^[^#]*= ]] && eval "export $line"; done < .env

# Create and activate a python virtual environment
# Windows
# virtualenv \path\to\.venv -p path\to\specific_version_python.exe
# C:\Users\!Admin\AppData\Local\Programs\Python\Python312\python.exe -m venv .venv
# .venv\scripts\activate

# Linux
# virtualenv .venv /usr/local/bin/python3.12
# python3.12 -m venv .venv
# python3 -m venv .venv
python3 -m venv .venv
source .venv/bin/activate

# Update pip
python -m pip install --upgrade pip

# Install dependencies
pip install -r requirements_dev.txt

# Configure linting and formatting tools
sudo apt-get update
sudo apt-get install -y shellcheck
pre-commit install

# Install the package locally
pip install --editable .

Style Guidelines

This project enforces quite strict PEP8 and PEP257 (Docstring Conventions) compliance on all code submitted.

We use Black for uncompromised code formatting.

Summary of the most relevant points:

• Comments should be full sentences and end with a period.
• Imports should be ordered.
• Constants and the content of lists and dictionaries should be in alphabetical order.
• It is advisable to adjust IDE or editor settings to match those requirements.

Use new style string formatting

Prefer f-strings over % or str.format.

# New
f"{some_value} {some_other_value}"
# Old, wrong
"{} {}".format("New", "style")
"%s %s" % ("Old", "style")

One exception is for logging which uses the percentage formatting. This is to avoid formatting the log message when it is suppressed.

_LOGGER.info("Can't connect to the webservice %s at %s", string1, string2)

Testing

Ideally, all code is checked to verify the following:

All the unit tests pass All code passes the checks from the linting tools To run the linters, run the following commands:

# Use pre-commit scripts to run all linting
pre-commit run --all-files

# Run a specific linter via pre-commit
pre-commit run --all-files codespell

# Run linters outside of pre-commit
codespell .
shellcheck -x ./script/*.sh

References

• https://docs.microsoft.com/en-us/azure/container-instances/container-instances-using-azure-container-registry
• Databricks secrets https://docs.databricks.com/security/secrets/secrets.html