Free‑tier cloud credits run out faster than expected – a single Jupyter notebook on a GPU spot instance can consume a 10 GB quota in under an hour. The bottleneck is not the model, it is the time spent wiring containers, mounting data, and reproducing the same environment on a new VM. ## 1. Define the experiment once, deploy everywhere

The most reliable way to keep the environment consistent across GCP Free Tier, Azure for Students, and AWS Free Tier is to describe it in a docker-compose.yml . Write the file once, then spin up a replica with a single command.

version : " 3.9" services : notebook : image : jupyter/datascience-notebook:latest ports : - " 8888:8888" volumes : - ./work:/home/jovyan/work environment : - GRANT_SUDO=yes command : start-notebook.sh --NotebookApp.token='' tensorboard : image : tensorflow/tensorflow:2.13.0-jupyter ports : - " 6006:6006" volumes : - ./logs:/logs command : tensorboard --logdir=/logs --host=0.0.0.0

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Takeaway: Store…