wanna-ml-cookiecutter

cookiecutter template for wanna-ml projects

How to set up a WANNA ML project

1. GCP infrastructure setup

In order to set up a WANNA ML project, one must have the following things:

• group of GCP projects with suffixes per environment (usually -test, -stage, -prod), we call them GCP project bundles
• a bucket with name wanna-<project_name>-<env>
• a service account with name sa-wanna-<project_name>
• a pubsub notification channel named ms-teams-wanna-<project name>-topic

2. Bootstrap

Assuming all terraform is done and deployed we can quickly bootstrap a wanna-ml project using cookiecutter and answer a few questions like so:

Quick python setup

• pipx is installed or alternatively you have cookiecutter in your $PATH
  • pipx install cookiecutter

Launch the cutter

cookiecutter https://github.com/avast/wanna-ml-cookiecutter.git

Project name without wanna- prefix (project_name): genie-ai
project_owner_fullname (Joao Da Silva):
project_owner_email ([email protected]):
project_version (0.0.0):
project_description (Link to project page on Confluence):
gcp_project_id (your-gcp-project-id):
GCP Project bundle without tenant name (wanna):
gcp_region (europe-west1):
gcp_network_name (europe-west1-net):
gcp_subnetwork_name (europe-west1-subnet):
gcp_service_account_name (sa-wanna-genie-ai):
use_jupyter_notebooks [y/n] (y):

You may notice that with few fields we can bootstrap a project, whilst leaving the others to default will do just fine.

• project_name does not contain any wanna words in it
• gcp_project_id the initial test gcp project id
• gcp_project_bundle_name the gcp project bundle where wanna-ml project will be deployed to. Just the project bundle, not the tenant name.

Once you have completed the cookiecutter you can cd to the newly created folder, read and run the README.md top down to explore how wanna-ml works and what it can do for you.