This repository contains Chapter 1 exercises files and resources for the Practical MLOps book. These exercises provide practical examples of MLOps concepts.

What was done:

• The application was developed in Python (no ML yet, the main idea was to build something simple to practice basic MLOps project scaffolding repository).
• The Makefile was used to define steps related to build, unit test and API load test through Locust.
• The Makefile was used in a CI/CD pipeline using GitHub Actions, further in the pipeline the application was containerized using Docker and registered in the AWS ECR using AWS CodeBuild.
• The AWS resources infrastructure required for this exercise was provisioned with Terraform.

.
├── Dockerfile                  # Docker configuration file
├── Makefile                    # Makefile for automating commands
├── README.md                   # This README file
├── buildspec.yml               # Build specifications for CI/CD
├── exercises.md                # Markdown file with exercise descriptions
├── infra                       # Infrastructure as code (IaC) files
│   ├── main-infrastructure     # Main infrastructure setup
│   └── terraform-backend-setup # Terraform backend configuration
├── locustfile.py               # Locust file for load testing
├── requirements.txt            # Python dependencies
├── src                         # Source code directory
│   └── main.py                 # Main application file
└── tests                       # Test scripts
    └── test_main.py            # Test for main.py

• Docker
• Terraform
• Python 3.x

1. Create an AWS account and an IAM user.

2. Fork this repository.

3. Clone the repository:

   git clone https://github.com/<user>/practical-mlops-ch1-exercises.git

Remember to replace variables on the variables.tf files and also parameters on infra/main-infrastructure/backend.tf with your own AWS ARNs, ID accounts etc.

4. Set up your AWS keys for GitHub Actions (https://docs.github.com/pt/actions/security-guides/using-secrets-in-github-actions)

5. Before deploying the infrastructure and running the CI/CD pipeline for main resources:

   5.1 First deploy resources for the Terraform file state in an S3 backend merging to the terraform-backend-setup branch;

   5.2 After merge to the main branch, the AWS resources required on the exercise will be created;

   5.3 To destroy AWS resources built by workflow.yml through main branch, merge to destroy-infra branch;

• Practical MLOps book authors Noah Gift and Alfredo Deza.
• O'Reilly Media.