Have you tried Google Cloud Run(based on KNative) I've never used it in production, but on paper seems to fit the bill.
It's in a weird place between heroku and lambda. If your container has a bad startup time like one of our python services, autoscaling can't be used as latency becomes a pain. Its also common deploy services on there that need things like health checks (unlike functions which you assume are alive), this assumes at least 1 instance of sustained use as well, assuming you do minute health checks. Their domain mapping service is also really really bad and can take hours to issue a cert for a domain so you have to be very careful about putting a lb in front of it for hostname migrations.
I don't care right now but the fact that we're paying 5x in compute is starting to bother me a bit. A 8core 16gb 'node' is ~$500/month ($100 on DO) assuming you don't scale to zero (which you probably wont). Plus I'm pretty sure the 8 cores reported isn't a meaty 8 cores.
But its been pretty stable and nice to use otherwise!
I do get that it is a bare server, but if you deploy even just bare containers to it, you would be saving a good bit of money and get better performance from it.
There is also a $63/month option that is significantly worse.
Our solution was to migrate the service to Kubernetes using an HPA scaling on the number of un-acked messages in the subscription, and then use a pull subscription to ensure reliable delivery (if the service is down they just sit in the queue rather retrying indefinitely).
I'm convinced Cloud Run/Functions are only useful for trivial HTTP workloads at this point and I rarely consider them.
But sweet sweet github triggered deploys. Have you found an easy solution to this?
Triggered deploys to Kubernetes you mean? There's a million ways to solve this problem for better or worse. We use Gitlab CI so we invoke helm in our pipelines (I'm sure there's a way to do this with github actions), but there's also flux cd, argo, etc. etc.
We use Kubernetes (GKE) elsewhere so we already had this machinery in place luckily. I can see the appeal of CloudRun/Functions as a way to avoid taking that plunge
Starting containers on Cloud Run is weirdly slow, and oh boy, how expensive that thing is. I'm getting the impression that pure VMs + Nomad would be a way better option.
As a long time Nomad fan (disclaimer: now I work at HashiCorp), I would certainly agree. You lose some on the maintenance side because there's stuff for you to deal with that Google could abstract for you, but the added flexibility is probably worth it.
What is this about? I assumed a highly throttled cpu or terrible disk performance. A python process that would start in 4 seconds locally could easily take 30 seconds there.