mlops-with-vertex-ai

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An end-to-end example of MLOps on Google Cloud using TensorFlow, TFX, and Vertex AI

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- Dockerfile
- model-deployment.yaml
- pipeline-deployment.yaml
- serving_resources_spec.json
- utils.py
- - gcs-bucket.tf
  - main.tf
  - notebook-instance.tf
  - service-accounts.tf
  - services.tf
  - terraform.tfvars
  - variables.tf
- README.md
- - __init__.py
  - datasource_utils.py
  - features.py
- - __init__.py
  - data.py
  - defaults.py
  - exporter.py
  - model.py
  - runner.py
  - task.py
  - trainer.py
- - __init__.py
  - main.py
  - requirements.txt
- - __init__.py
  - etl.py
  - transformations.py
- - schema.pbtxt
- - __init__.py
  - datasource_utils_tests.py
  - etl_tests.py
  - model_deployment_tests.py
  - model_tests.py
  - pipeline_deployment_tests.py
- - __init__.py
  - components.py
  - config.py
  - prediction_pipeline.py
  - runner.py
  - training_pipeline.py
- __init__.py
.gitignore
01-dataset-management.ipynb
02-experimentation.ipynb
03-training-formalization.ipynb
04-pipeline-deployment.ipynb
05-continuous-training.ipynb
06-model-deployment.ipynb
07-prediction-serving.ipynb
08-model-monitoring.ipynb
Dockerfile
LICENSE
mlops.png
README.md
requirements.txt
setup.py

# Installation Guide

1. Get the code

git clone https://github.com/GoogleCloudPlatform/mlops-with-vertex-ai

Downloads the entire project code from GitHub to your computer.

cd mlops-with-vertex-ai

Moves into the project folder you just downloaded.

2. Official Install Script

Easy Recommended

Prerequisites

Python 3 Python is required to use pip.
APT (Debian/Ubuntu 계열) Built into Debian/Ubuntu-based Linux distributions.

pip install tfx==1.2.0 --user

Installs the package published on PyPI directly — no need to clone the source.

sudo apt-get install google-cloud-sdk

Installs directly from the APT package repository (Debian/Ubuntu-based).

✅ After installing, open a new terminal and run the program's version command (e.g. --version) to confirm it worked.

Pulled directly from this repo's README.

3. Docker

Easy

Prerequisites

Git Needed to download the project code from GitHub.
Docker Desktop Needed to build and run containers. Install it and keep it running in the background.

docker build -t mlops-with-vertex-ai .

Builds a runnable image based on the Dockerfile.

docker run -p 8080:80 mlops-with-vertex-ai

Runs the built image as an actual container.

✅ Run docker compose ps to check the containers are Up. If the README mentions a port, open http://localhost:PORT in your browser.

4. Python

Easy

Prerequisites

Git Needed to download the project code from GitHub.
Python 3 On Windows, be sure to check 'Add Python to PATH' during installation.

pip install tfx==1.2.0 --user

Installs the package published on PyPI directly — no need to clone the source.

pip install -r requirements.txt

Installs the Python libraries listed in requirements.txt (or similar).

**NOTE**: You can ignore the pip dependencies issues. These will be fixed when upgrading to subsequent TFX version.

Type this command into your terminal and run it.

✅ If it runs without errors and prints output in the terminal, it worked.

Pulled directly from this repo's README.