[aelzeiny]

As someone who works in Data Engineering, I'm a big fan of cloud-based docker containers with services like AWS Fargate/Google Run. It allows us to be able to pay for resource use rather than provisioning. For the longest time I had to justify the additional cost and constant maintenance of an n-th server just to accommodate for capacity at peak hours. Anecdotally, most of our batch jobs don't need high availability, so the startup time of a server-less docker is an acceptable trade-off to parallelism.

[wtmt]

> It allows us to be able to pay for resource use rather than provisioning.

Not arguing against the choice, but at some level, you are paying for the provisioning costs of the cloud provider. The higher initial costs of provisioning is what you may be escaping, and instead paying on an ongoing basis (as if you’re leasing equipment and services).

Once your needs scale significantly, cloud providers would end up being quite expensive if your load is not highly variable.

[chrisbroadfoot]

It's compatible with Knative, which is easy to set up in GKE, so you can migrate loads over to that if you want more control over your compute costs. And of course, you can run Knative outside of GKE, too.

Disclaimer: I work on GCP but have only touched Cloud Run/Knative a little bit.

[cwyers]

> if your load is not highly variable

Most real-world loads are in fact pretty variable.

[kortilla]

You know you can also boot instances that bill at hour and less granularity right? Billing is probably the least compelling argument to a service like this.