Cloud Deployment

The arc of Cloud Deployment: get the dockerized service answering at a real public URL, promote the same artifact instead of rebuilding, put it on a domain over TLS, make failure cheap with a one-step rollback, and bound the cost before it bounds you.

Push the M6 dockerized /predict image to a scale-to-zero container host and score a Lending Club record at a real public URL: happy path, end to end.

Promote the exact image you tested by its content digest instead of rebuilding it, keep configuration in the environment so one artifact runs in every stage, and see why a baked secret survives in a layer even after a later layer deletes it.

Put the service on a real domain over https:// and survive the hour where it does not work yet. DNS propagation and certificate provisioning are two clocks, chained in series, and that hour is normal.

Choose how new versions go out, gate the cutover on a probe that means can-serve, and guarantee a one-step rollback to the last good version under real traffic.

Make idle cost near-zero or capped, pick the billing model from the traffic curve, and state the expected and worst-case monthly figure out loud.

A recap of Cloud Deployment: the dockerized model now answers at a real public URL on a real domain over TLS, ships as the exact artifact you tested, rolls back in one step under live traffic, and runs at a cost you stated in advance — and where the system goes next.