A look inside the Cloudflare ML Ops platform

What this post added

This post details Cloudflare's internal ML Ops platform, focusing on the training side of the ML equation. It covers the use of JupyterHub on Kubernetes for scalable notebook environments, GitOps with ArgoCD for continuous delivery and infrastructure management, curated model templates for training, batch inference, stream inference, and explainability, and various orchestration tools (Airflow, Argo Workflows, Kubeflow Pipelines, Temporal) based on team and use case preferences. It also touches on hardware considerations for GPUs and CPUs.