Hacker News Reader

Comment by hardwaresofton | Hacker News Reader

Yep, and you'd generally expect to spend time understanding the complexity that systemd brings, the subsystems that power it, and how you can separate resources there! There is no free lunch.

Restated, my point here is that while containers can be more complex and have pitfalls (a lot of which have been worked out somewhat at this point), there is no complexity free lunch -- `[docker|podman|crictl] run --rm --cpus 2 --memory 500mb ...` is pretty darn easy, and more so than writing properly portable and well-considered systemd unit files (and putting them in the right place, with the right permissions, under the right slice, etc). It's easier than most of the options out there (including the old methods of per-user resource segregation).

View on HN

Let's say you are installing this from a normal package manager and want to limit it:

To install:

    apt install mypackage

To edit the systemd unit (automatically creating the file in the right place):

    systemctl edit mypackage

Then add these lines to limit to 2 cpus and 500mb memory:

    [Service]
    CPUAccounting=true
    CPUQuota=200%
    MemoryAccounting=true
    MemoryHigh=500M

And then to start it now and on boot:

    systemctl enable --now mypackage

This is now integrated with package updates, starts on boot, logs to the same place that most other system utilities do and so on.

I'm not about to argue against systemd, it's great software, and it's in every distro right now for a reason. Understanding apt (+/- how to package for it), systemctl, and the options you've laid out in your unit file are not trivial, and I would argue that they are less trivial (or harder) than understanding what's happening with containers, especially if you're running rootless containers, and/or using a container tool like podman which does without the daemon.

  --cpus 2 --memory 500M

is easier, and gets you the same results though they may not be as permanent or as well managed -- the management and external stuff is an orthogonal concern, and that's not the situation I was addressing. The original point was insinuating that throwing up a binary and getting it to run. your filesystem is also not available to the container by default, and in this way docker sort of fails closed. If you're running a rootless container, the story is even better.

One thing you have not covered is filesystem isolation, which docker also does very easily. There is a lot to configure on the systemd side[0] and the parts that are overlapping are just easier to configure and run with docker. Systemd is the better tool to build repeatable installs for pet processes, but again, there is a lot of knowledge underneath that is related. People to this day still complain that systemd does too much (I personally like it a lot, and it's great to have everything in one place).

[EDIT] Just to make myself clear, systemd is an amazing tool -- I like it, I run it, I'm not smart enough to administer a more complicated setup -- but docker is easier, for a large part of the small subset of systemd's capabilities that docker covers.

[0]: https://www.redhat.com/sysadmin/mastering-systemd

But there is a lot of work to be done before you can do the simple apt install. I (gladly) don't know how it is nowadays but before Dockerfiles/Docker creating your own packages according to the various standards was a pita. Most companies needed a 'packaging specialist/release engineer' role as most developers where not up to the task. Solutions like FPM[0] did help somewhat, but it was still hard when dealing with non-homogeneous environments. Containers solved that problem universally for all distributions.

[0] https://github.com/jordansissel/fpm

I don't see how appending

    --cpus 2 --memory 500mb

to the argument vector liberates these options' definer from "understanding [...] the subsystems that power it", and reflect on their potential impact. And I'd argue that THIS is the real complexity incurred by these kinds of resource constraints that seem so simple on the surface - not the specific syntax or location you have to use to introduce them. All of which makes systemd unit files and their settings' implications (which are amazingly well-documented btw) as good as any other option, imho.

Systemd is great software -- it is useful, and powerful. A systemd unit file, the idea of what a unit is, when they run, how they run, what shells they use, what permissions they run under, and lots of other complexities are expressed as options in the unit file, configuration files on the system, and in other places.

If I want to run a useful piece of software like redis let's say, but I want to run it with a resource constraint to make sure that it doesn't take more than 2CPUs and 500MB of memory, it is far easier to do that with the following command line:

   docker run --rm redis --cpus 2 --memory 500mb -p 6379:6379

Than to write the equivalent systemd unit file, set up the isolated filesystems that docker would let you easily bind mount in, etc. This is like comparing systemd-nspawn to systemd -- if systemd-nspawn isn't simpler than systemd then what are we even doing.

Docker won because of it's developer ergonomics (containers weren't new), systemd won because of it's feature set, convenience and sturdiness. They're different tools with different primary use-cases.

Then you will want to manage the configuration file and to browse logs, and you ll have to mount files to you container. And your deployment start to reimplement (a subset to your needs) what distros did System integration complexity didn't disappear thanks to containers. It was just moved to another place. I dd add that, being convenient for developers doesn't mean it's convenient for hosting management. At the end, when one side convenience is taken in consideration, it often translate to complexity and pain at the other side. K8S become in some companies more a mandatory runtime requirement than a hosting commodity/facility.

As a (former) developer I d rather ran redis in a container during development, but for production I d rather rely on boring VMs unless some scaling is required. (Managed k8s case set apart)

> Then you will want to manage the configuration file and to browse logs, and you ll have to mount files to you container. And your deployment start to reimplement (a subset to your needs) what distros did System integration complexity didn't disappear thanks to containers.

Agree, but my view on this is that the implicit answer of how you do all that (i.e. the file system, syslog) is now gone. There will be pain (complexity) in the short term, but at the end of the day, we're going to be able to build much better orchestration and systems. To kind of restate that, before you had to worry where a process wrote out it's output (stdout? /var/log/<program>? /etc/<program>/logs? /home/<user>/<program>/logs? syslog?), now you know want to get the non-stdout/stderr logs of the thing you're running, you'd better give it a volume to write to (which may be fake, and actually write everything to some remote storage or something), and I think that's a step forward.

Of course, I'm not saying containers should go everywhere -- relying on boring VMs over containers is fine too -- but I think rich world of functionality available to container-driven workflows is popular for good and bad reasons, and the good reasons are worth exploring/beneficial to me.

can anyone explain why you might need to limit memory consumption of your service?

I thought the kernel has virtual memory and if you consume more it will swap some memory and thats it.

Couldnt you just manage memory from inside your app? if its redis, then check the db size and shutdown/cleanup gracefully, and not crash redis with OOM?

> can anyone explain why you might need to limit memory consumption of your service?

> I thought the kernel has virtual memory and if you consume more it will swap some memory and thats it.

Well just to make sure the right memory goes to the right places -- if someone uploads a large file and you've made a mistake in your code that tries to hold it all in memory instead of buffering it straight to disk for example, you'd want that process to crash, and not your machine.

Also you generally don't want to swap, so much so that Kubernetes disables it immediately[0]. Not that Google is the only group with the right answer but they seem to think nothing can come of a machine having to swap. Maybe they're right. Even if they're not, A world where one service swaps[1] (I've never done this with docker to try it though) is probably better than one where it uses all the memory and everything swaps.

> Couldnt you just manage memory from inside your app? if its redis, then check the db size and shutdown/cleanup gracefully, and not crash redis with OOM?

You'd be surprised -- some languages just don't have a way to very easily get feedback from GC[2]. It's also something that I don't think most people think about, messing with the -XmXx<setting>s in Java is definitely year 2/3/4 java development for most people.

[0]: https://github.com/kubernetes/kubernetes/issues/53533

[1]: https://docs.docker.com/config/containers/resource_constrain...

[2]: https://github.com/golang/go/issues/29696

Also thank you very much for kubernetes link.

Wow, given how expensive RAM is it is no surprise they will never allow kubernetes work with swap, becausr it directly translates to $$$ for GCP and other cloud providers. Also since everyone loves using Java/Spring/Node and other memory hungry frameworks - it print enormous $ for cloud providers to require users overallocate RAM and disable swap.

or am I just spitballing conspiracy theory here and there is no conflict btw decisions like these and vendors' revenue streams?

For years, nay decades, the standard for data centers is no swapping. An incident caused by machine went slow due to swapping is almost as embarrassing as one caused by disk filling. Better to orchestrate a restart every night on your leaky code.

I think it is just different thinking: DEV where software is a pet, where I want full control of my memory and take care of it carefully, and dont want anyone shutting down my service violently.

contrast it to Ops mentality of software is a cattle (here is your memory quota and if its OOM, just kill/restart the service and hope next run it wont run OOM)

Reply on news.ycombinator.com