Automating the path to production.
WHAT DIFFERS FROM SOFTWARE DELIVERY
Three things change, not one: code, data and model.
WHAT THAT REQUIRES
Versioning all three, and understanding which changed.
WHAT THE PIPELINE SHOULD DO
Validate data Train Evaluate against thresholds and the current model Package Test the packaged artefact Deploy to a staging environment Promote on approval
WHAT TO GATE ON
Evaluation thresholds Comparison with the current model Behavioural tests passing Data validation passing
WHAT TO NEVER AUTOMATE WITHOUT GATES
Promotion to production.
WHY
An automated pipeline will otherwise deploy a worse model confidently.
WHAT TO TEST IN STAGING
The full serving path, with real request shapes.
WHAT TO KEEP REPRODUCIBLE
Everything, so a deployed model can be rebuilt.
WHAT TO ALERT ON
Pipeline failure Evaluation below threshold A model failing comparison
WHAT TO RECORD
Every run, and its outcome.
WHAT TO AVOID
Manual steps that are forgotten Different processes for different models
