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Comment by danielvaughn | Hacker News Reader

How are the cold starts? I tried a similar setup with GCP cloud functions and I was running into (I shit you not) 5-7 second cold start times.

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<3s is our target 95% is <2.5s. We have a keep warm function that always keeps 5x "warm"-ish so we rarely hit cold starts. Keep warm is not fool proof as AWS got smart about people constantly doing keep warms, but it definitely helps.

There will likely be very few cold starts when the whole monolith is running in it

At that point you’re just paying an exorbitant rate for… the same thing you would get from hosting it on EC2

Or if you can take a bit of up-front setup cost, running it on GKE with Autopilot means you've got many of the benefits of lambda on a K8s cluster (e.g. immutable container-driven development, no need to manage long-running VMs) and only pay for used resources (not idle machines). The main caveat is no scale-to-zero, but as mentioned previously, that's unlikely to happen.

IMXP, autopilot is multiple times the price of a VM on a non-GCP platform.

How come? I see Autopilot is $0.10 per cluster hour, or ~$75 a month, add the standard GKE cluster management overhead of $150, that's $225 a month for a cluster which rounds to zero given any reasonable load. Then in my experience GCP VMs have always been price competitive with basically any other cloud provider.

The issue we had was getting the bin-packing right on our cluster, and we often ended up with 20% unallocated capacity per VM. Autopilot basically solves that (and probably pays for itself with only a few VMs) as you only pay for the K8s defined resources, and therefore only have 1 level of cost optimisation at the pod level, rather than 2 at the pod and VM level.

Yeah, I wouldn‘t do it

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