model governance

Practical, Bash-first playbook for end-to-end AI model management on Linux: version code/data/models with Git LFS + DVC, track experiments in MLflow, lock dependencies and containerize for consistent deploys, register/serve via MLflow or Hugging Face, and automate CI promotion gates—enabling reproducible, auditable pipelines that prevent regressions and speed releases.

Practical, bash-first guide to securing AI models and pipelines on Linux: distro-ready installs (apt/dnf/zypper), venvs with hash-pinned deps and CVE audits, secret hygiene with git-secrets and sops/age, artifact hashing/signing (SHA256, minisign), sandboxed runtimes (firejail, bwrap, rootless Podman), image/file scans via Trivy, a copy-paste checklist script, and real-world tips to cut supply-chain and runtime risk.