[tcgv]

I love Docker Compose. It is simple to use, easy to organize and manage, and very robust. Also, our company does not need to "scale" production aggressively. Our production load is very predictable, so Docker Compose fits like a glove.

We have been using it for more than five years now. Before that, we had a legacy deployment model, and I do not remember a single major issue related to Docker Compose.

We use it for both staging and production environments. The same Docker image validated in staging is deployed to production. Never fails!

[api]

"It is simple to use, easy to organize and manage, and very robust."

This is why nobody uses it. Cloud stuff has to be as baroque as possible.

[iamtedd]

To misquote Douglas Adams:

There is a theory which states that if ever anyone discovers exactly what Kubernetes is for and how it works, it will instantly disappear and be replaced by something even more bizarre and inexplicable.

[DeathArrow]

>if ever anyone discovers exactly what Kubernetes is for

This part is easy, Kubernetes is for your CV. /s

[gear54rus]

It's simple to use only for toy use cases, that's why nobody uses it. The article everyone in this thread seems to like only goes as far as 'I pushed to git so it must be ok' which is laughable and I'm not even DevOps.

What happens if it errored on deployment or after that? you wanna write custom (bash? :D) hooks for that? What about upgrading your 'very vertically scalable' box? What if it doesn't come up after the upgrade? your downtime is suddenly hours, oops.

The k8s denial is strong and now rivals frontend frameworks denial. Never fails to amuse.

[tcgv]

Fair points, and yes, failed deploys need to be handled explicitly.

In our case, the answer is not "hope and bash". We deploy versioned images, use health checks, monitor the result, and keep rollback simple: redeploy the previous known-good image/config. Host upgrades are also treated as maintenance events, with backups and a recovery path, not as something Compose magically solves.

But I think there is an opposite mistake too: assuming every production system should be operated like a high-scale tech company.

Many production workloads are boring, predictable, and business-critical. They do not need aggressive autoscaling, multi-node orchestration, or constant traffic-spike handling. They need reliable deploys, backups, monitoring, health checks, and a clear rollback path.

That is where Compose can be a good fit: simple operational model, understood failure modes, low moving parts.

Kubernetes becomes much more compelling when you actually need automated failover, rolling deploys, autoscaling, multi-node scheduling, and stronger deployment primitives.

Not needing Kubernetes is not necessarily denial, it is just choosing the complexity budget that matches the problem.

[scottyah]

Definitely not a one-size-fits-all choice, but Kubernetes can be so easy and there are so many benefits that get you from one small app to a medium sized business that it seems like a no-brainer for someone starting out. Spinning up k3s is pretty minimal overhead, but right away you can handle storage and backups very easily, automatic certs for all your apps with cert-manager is pretty much a one-and-done, traffic management for external and internal tools is easy, and even logins for websites is just an annotation in a yaml file. You can spin up and try out any software you want without spending time configuring it or setting up additional servers- and when you do need more hardware, it's one command on a virtual server, and just about as easy with physical hardware.

2-3 miniPCs, cloudflare, tailscale, and k3s can save (possibly tens of) thousands on SaaS products, and would probably scale you to a company of dozens AND host your product.

[fud101]

>2-3 miniPCs, cloudflare, tailscale, and k3s can save (possibly tens of) thousands on SaaS products, and would probably scale you to a company of dozens AND host your product.

outline a simple real world system to illustrate?

[scottyah]

Sure!

Get a few Beelink SER5 or SER9's, install Nextcloud to cover the files, document editing, communications (to save on Microsoft 365). Then you can have Gitea (and gitea actions) for your source code and building (skipping github enterprise), Harbor to host and scan your containers, frappe for HR, etc. Pretty much anything you pay enterprise rates for, you can self-host a version that will get your company from 1 to 100s with minimal extra work. If it's not on https://github.com/awesome-selfhosted/awesome-selfhosted, you can probably vibe code it in a couple hours.

I just started to run a k3s cluster with an almost enterprise grade software factory and a few (light) production workloads on a single cheap minipc.

https://scottyah.com/cluster

[jdw64]

I think people are using different meanings of “production environment.”

I agree with gear54us and upvoted their comment, but I also understand what the author of the root comment is saying.

I have also delivered systems using Docker Compose that are actually running in production. The point I want to make is that people may define “production” differently depending on the number of active users, operational requirements, and risk level.

To me, this debate feels similar to the broader monolith vs. microservices debate.

[bdangubic]

"Not just for my own projects but for $500 million dollar companies and more."

Seems reasonable to assume these are serious production environments, no?!

[Cpoll]

Not necessarily. When you get to those numbers you're seeing dozens of teams with their own silos and deployment methods. So they might be responsible for the core business that's running 30 nodes and serving 100MM users a day, or they might be working on some internal portal or a WordPress site.

[nickjj]

When I mentioned that, it was for a company that got acquired by a bigger company. I can't give specifics with revenue / profits but it is a 10+ year old online SAAS business and all of their web apps are being served by Docker Compose with a non-trivial amount of direct customer facing traffic.

Lots of data, caching, web apps, background workers and lots of various API integrations. No fancy React front-end, no fancy crazy system architectures. Just a typical LAMP stack but running in Docker Compose, cranking away serving value to customers with very good uptime and a very low cloud cost relative to revenue. With that said, a managed database was involved but all of the web traffic was served by apps running through Docker Compose with a simple git push model of deployment that handled thousands of deployments over the years without much fuss.

[nonameiguess]

That as well as different definitions of scale. I've done small bits of consulting work for a research company for the past four years, deploying and managing Kubernetes clusters for them as well as helping get some of the main applications up on it. This is all internal tooling, though. Their customer-facing sites are just Drupal instances running on bare EC2.

Internally, though, they wanted to self-host a chat server, Apache airflow, Overleaf for collaborative editing of research proposals, three separate Git servers, a container registry, many other things, all with extremely strict multi-tenancy isolation requirements for storage and networking because they're handling customer data and their own customers audit them for it. That was a hell of a lot easier to do with Kubernetes than trying to figure out some giant universe of barely related technologies with vastly different APIs, having to buy specialized appliances for network and storage that probably also need their own control plane software hosted somewhere else.

But if you just look at "scale" as number of http requests a particular URL gets per some unit of time, the customer-facing sites have far greater scale. If you're trying to attribute revenue, beats me. They wouldn't sell anything without the customer-facing sites, but they wouldn't have anything to sell without the internal tooling. Solo web devs get into this tunnel vision view of ops because, to them, often the web site is the product. That's not the case for most businesses.

And, of course, they'd probably just use someone else's SaaS for tooling. But if you're in a heavily regulated space where that isn't possible and you have to self-host most of your business systems, then what?

[nickjj]

The post receive hook provides you real-time feedback as it runs in the terminal where you did the git push. If something broke during the deployment you'd get notified by looking at the output. If it's running in CI, you'd see a CI failure and get notified using whatever existing mechanisms you have in place to get notified of deployment pipeline failures.

Zero downtime server upgrades are easy. You could make a new server, ensure it's working in private and then adjust DNS or your floating IP address to point to the new server when you're happy. I've done this pattern hundreds of times over the years for doing system upgrades without interruption and safely. The only requirement is your servers are stateless but that's a good pattern in general.

[VorpalWay]

Define production. Docker compose is fine for running a small internal service in production for dozens of users (i.e. not for developing said service, but for using it). I would assume it isn't fine to run a hyperscaler (but I wouldn't know). Those are extremes, and there are going to be a ton of situations in between.

I can't personally speak to what the limit of docker compose is, as I have only worked on the lower end of this: self hosting for personal use and for small internal services serving maybe 20 users.

[Ronsenshi]

From my personal experience if deployment strategy is thought through then Docker running through Compose can handle few hundreds of thousand of users per day without an issue and probably could handle more with proper hardware upgrades.

[tracker1]

Most people/apps only need the toy cases... If you're writing an internalized tool for a company that will only have a handful of users, then doing much more than compose for deployments is a violation of KISS and YAGNI.

Are you really going to try to get 4+ 9's of uptime for a small, one-off app? Do you really need to use a cloud distributed data store that only slows things down for no real gains in practice? Do you really think the cloud services are never down, and you're willing to spend a f*ck-ton of money to create a distributed app when historically an Access DB or VB6 app would have done the job?

I've moved applications deployed via compose pretty easily... compose down -t 30 then literally sftp the application to a backup location then to the new server which only needs the Docker Engine community stack installed.. then compose up -d ... tada! In terms of deployment, you can use github action runners if you want, or anything else... you can even do it by hand pretty easily.

[daitangio]

I love it so much I have created a thin statless orchestrator layer upon it:

https://github.com/daitangio/misterio

It works very well!

[monkpit]

You have built a kubernetes…

https://www.macchaffee.com/blog/2024/you-have-built-a-kubern...