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Replacing a $3000/mo Heroku bill with a $55/mo server

(disco.cloud)
804 points jryio | 2 comments | 21 Oct 25 20:28 UTC | HN request time: 0s | source
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speedgoose ◴[21 Oct 25 21:12 UTC] No.45661785[source]▶
Looking at the htop screenshot, I notice the lack of swap. You may want to enable earlyoom, so your whole server doesn't go down when a service goes bananas. The Linux Kernel OOM killer is often a bit too late to trigger.

You can also enable zram to compress ram, so you can over-provision like the pros'. A lot of long-running software leaks memory that compresses pretty well.

Here is how I do it on my Hetzner bare-metal servers using Ansible: https://gist.github.com/fungiboletus/794a265cc186e79cd5eb2fe... It also works on VMs.

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levkk ◴[21 Oct 25 21:51 UTC] No.45662183[source]▶
Yeah, no way. As soon as you hit swap, _most_ apps are going to have a bad, bad time. This is well known, so much so that all EC2 instances in AWS disable it by default. Sure, they want to sell you more RAM, but it's also just true that swap doesn't work for today's expectations.

Maybe back in the 90s, it was okay to wait 2-3 seconds for a button click, but today we just assume the thing is dead and reboot.

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gchamonlive ◴[21 Oct 25 22:04 UTC] No.45662314[source]▶
How programs use ram also changed from the 90s. Back then they were written targeting machines that they knew would have a hard time fitting all their data in memory, so hitting swap wouldn't hurt perceived performance too drastically since many operations were already optimized to balance data load between memory and disk.

Nowadays when a program hits swap it's not going to fallback to a different memory usage profile that prioritises disk access. It's going to use swap as if it were actual ram, so you get to see the program choking the entire system.

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winrid ◴[21 Oct 25 22:15 UTC] No.45662410[source]▶
Exactly. Nowadays, most web services are run in a GC'ed runtime. That VM will walk pointers all over the place and reach into swap all the time.
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cogman10 ◴[21 Oct 25 22:35 UTC] No.45662595{3}[source]▶
Depends entirely on the runtime.

If your GC is a moving collector, then absolutely this is something to watch out for.

There are, however, a number of runtimes that will leave memory in place. They are effectively just calling `malloc` for the objects and `free` when the GC algorithm detects an object is dead.

Go, the CLR, Ruby, Python, Swift, and I think node(?) all fit in this category. The JVM has a moving collector.

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eru ◴[22 Oct 25 00:05 UTC] No.45663386{4}[source]▶
A moving GC should be better at this, because it can compact your memory.
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1. cogman10 ◴[22 Oct 25 00:29 UTC] No.45663579{5}[source]▶
A moving collector has to move to somewhere and, generally by it's nature, it's constantly moving data all across the heap. That's what makes it end up touching a lot more memory while also requiring more memory. On minor collections I'll move memory between 2 different locations and on major collections it'll end up moving the entire old gen.

It's that "touching" of all the pages controlled by the GC that ultimately wrecks swap performance. But also the fact that moving collector like to hold onto memory as downsizing is pretty hard to do efficiently.

Non-moving collectors are generally ultimately using C allocators which are fairly good at avoiding fragmentation. Not perfect and not as fast as a moving collector, but also fast enough for most use cases.

Java's G1 collector would be the worst example of this. It's constantly moving blocks of memory all over the place.

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2. eru ◴[22 Oct 25 04:44 UTC] No.45664965[source]▶
> It's that "touching" of all the pages controlled by the GC that ultimately wrecks swap performance. But also the fact that moving collector like to hold onto memory as downsizing is pretty hard to do efficiently.

The memory that's now not in use, but still held onto, can be swapped out.