Comment by parhamn | Hacker News Reader

Comment by parhamn | Hacker News Reader

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Yeah we're mostly hosted there now. The cpu/virtualization feels slow but I haven't had time to confirm (we had to offload super small ffmepg operations).

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!

A 6c / 12t Dedicated Server with 32GB of ram is 65$ a month with OVH

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.

Another interpretation is the so-called dedicated servers are too good to be true.

It depends on what the 6 cores are. Like I have a 8C/8T dedicated server sitting in my closet that costs $65 per the number of times you buy it. (Usually once.) The cores are not as fast as the highest-end Epyc cores, however ;)

At the $65/month level for an OVH dedicated server, you get a 6-core CPU from 2018 and a 500Mbps public network limit. Doesnt even seem like that good a deal.

There is also a $63/month option that is significantly worse.

We also run some small ffmpeg workloads and experimented with Cloud Run consuming Pub/sub via EventArc triggers. Since Cloud Run's opaque scaling is tied to http requests, EventArc uses a push subscription. In pub/sub these don't give you any knobs to turn regarding rate limiting/back pressure, so it basically tries to DoS your service and then backs off. This setup was basically impossible to tune or monitor properly.

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.

Thats very interesting. Thanks for sharing.

But sweet sweet github triggered deploys. Have you found an easy solution to this?

> 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

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