Practical MLOps: container tutorial
freeCodeCamp published a high‑engagement tutorial on containerizing MLOps pipelines using MLflow, DVC, Docker Compose and GPU handling to bridge notebooks to deployable services. The guide focuses on reproducibility and the infra patterns teams need to move models from experiment to production. (x.com)
Published March 12, 2026 and authored by Balajee Asish Brahmandam, the freeCodeCamp tutorial runs through a full container-first MLOps workflow rather than a short blog post. (freecodecamp.org/news/containerize-mlops-pipeline-from-training-to-serving/) The piece opens with a concrete production post‑mortem—dependency conflicts between scikit‑learn builds, a NumPy/OpenBLAS vs MKL mismatch, and a missing system library—that the author says cost their team three weeks to debug and motivated the end‑to‑end container approach. (freecodecamp.org/news/containerize-mlops-pipeline-from-training-to-serving/) Explicit environment prerequisites are listed: Docker Engine 24+ or Docker Desktop 4.20+ with Compose v2.22.0+, and for GPU training the NVIDIA Container Toolkit plus a compatible GPU driver with checks such as running nvidia‑smi and docker compose version. (freecodecamp.org/news/containerize-mlops-pipeline-from-training-to-serving/) The tutorial includes copy‑paste commands for DVC (for example dvc init and dvc add data/training_data.parquet) and prescribes multi‑stage Dockerfiles plus a single docker‑compose.yml using profiles to switch between training and serving configurations. (freecodecamp.org/news/containerize-mlops-pipeline-from-training-to-serving/) On architecture, the article recommends separating training and serving images, decoupling model artifacts from runtime containers to keep serving images small, and a focused section on CUDA/driver compatibility to avoid the host/kernel‑level mismatches the author experienced. (freecodecamp.org/news/containerize-mlops-pipeline-from-training-to-serving/) The containerization guide is part of a recent run of Docker/Compose tutorials by the same author, including a March 6, 2026 follow‑up on using Docker Compose in production with profiles, watch mode, and GPU support, which reinforces the practical Compose patterns used in the MLOps walkthrough. (freecodecamp.org/news/containerize-mlops-pipeline-from-training-to-serving/, freecodecamp.org/news/how-to-use-docker-compose-for-production-workloads/)
