CI/CD for Data & AI Engineers: Build, Train, Deploy, Repeat – The DevOps Way

I just published a detailed article on how Data Engineers and ML Engineers can apply DevOps principles to their workflows using CI/CD.

This guide covers:

Building ML pipelines with Git, DVC, and MLflow Running validation & training in CI Containerizing and deploying models (FastAPI, Docker, Kubernetes) Monitoring with Prometheus, Evidently, Grafana Tools: MLflow, Airflow, SageMaker, Terraform, Vertex AI Best practices for reproducibility, model testing, and data validation

If you’re working on real-world ML systems and want to automate + scale your pipeline, this might help.

📖 Read the full article here:
👉 https://medium.com/nextgenllm/ci-cd-for-data-ai-engineers-build-train-deploy-repeat-the-devops-way-0a98e07d86ab

Would love your feedback or any tools you use in production!

#MLOps #CI/CD #DataEngineering #MachineLearning #DevOps