I once migrated a monitoring task from a smallish VM to GCP Cloud Functions triggered by the Cloud Scheduler. Nothing super fancy; imagine some code that runs o

I once migrated a monitoring task from a smallish VM to GCP Cloud Functions triggered by the Cloud Scheduler. Nothing super fancy; imagine some code that runs on a cron once per hour, collects a bunch of metrics on various things then writes the results somewhere. Straightforward but takes a couple minutes to execute and needs a good chunk of memory while it's running. Costs went from about $100/month for the VM size we needed to $0.12/month for the Cloud Functions version. Plus there was no longer a VM that needed to be secured, updated, monitored, etc. That aspect was arguably the much bigger savings than the basic VM cost. My current company is running entirely on Cloud Run. Not quite as "serverless" as pure Functions or Lambdas, but we have zero VMs or hardware that we manage, so I feel like it counts. We don't do huge amounts of traffic (and don't need to), but it's not trivial either and it's very spiky. The Cloud Run part of our setup is almost negligable (dominated by the database and storage/network costs by several orders of magnitude). With that we get easy deploys and rollbacks, auto-scaling, ephemeral preview environments for every PR, and a simple security story (when the security questionnaire spreadsheets come around, I get to just say "not applicable" and skip entire sections on host-based security, SSH keys, OS updates, etc). And it's basically just a standard Docker image for the app, so if we ever felt like it would be more cost effective to run it on a VM or K8s cluster, it wouldn't be that difficult. I agree that not everything is better with serverless, but there are some things where it's just a vastly better fit.