open-source self-hosted PaaS options for multi-cloud deployments
Learn which "multi-cloud" actually means before you buy.
Self-hosted, open source PaaS tools all promise freedom from vendor lock-in, but "multi-cloud" means two completely different things depending on which tool is making the claim. Some just run anywhere, and the team does everything else by hand. Others actually manage cloud accounts, networking, and cluster provisioning from one control plane. Most teams never stop to ask which one they're buying, and that's the decision that comes back to bite them a year later, usually mid-migration, usually under deadline pressure.
What "multi-cloud support" actually means for a self-hosted PaaS
Two things get lumped under this label, and they are not close to the same thing.
The first is "runs on any cloud." Install the platform on a VM in AWS, then install it again on a VM in Azure. Fine, technically multi-cloud. But the team still manages every cloud account, every network rule, every IAM policy, and every bit of cluster hygiene by hand, one cloud at a time. The second is real multi-cloud orchestration: one control plane that provisions and manages resources across multiple cloud accounts, so nobody's stitching things together by hand every time a new region or provider gets added. Almost every tool in this piece is the first kind, wearing the second kind's name.
That gap shows up in a few concrete places. Does the platform's control plane operate separately from the customer's runtime environment, or does it share the same infrastructure? Is cluster provisioning manual, or does the tool automate EKS, GKE, and AKS setup with IAM already wired in? Data residency matters too: workloads sitting in a shared environment behave nothing like workloads that never leave the customer's VPC. And networking is either a fixed topology handed down by the vendor, or a VPC, security groups, and a service mesh the team can actually shape.
There's an orchestration ceiling worth naming up front, because it decides more than any feature list. Docker Swarm platforms are simpler to run, but they cap out before Kubernetes-native capabilities come into play, and picking a platform means picking which ceiling to live with. Picking a platform means picking which ceiling to live with, whether or not that feels obvious on day one.
Dokku: the right tool for single-server simplicity, not multi-cloud
Dokku is a CLI-first, MIT-licensed Heroku clone built on Docker, meant to run on a single VPS or a single bare-metal box. It carries 31,900 GitHub stars and only 15 open issues, which says less about popularity and more about a codebase sanded down over roughly a decade of real use.
It's the lightest option in this whole comparison, resource-wise, and the cheapest for a small team running a handful of apps. Most of the edge cases have already been found and fixed, so production surprises are rare.
But it stops early, and nobody should pretend otherwise. There's no web GUI unless someone pays for Dokku Pro, an $849 lifetime license. There's no multi-node orchestration and no Kubernetes path at all. Multi-cloud deployment means setting up Dokku by hand on each server, on each cloud, with nothing tying them together. No native preview environments, no built-in CI/CD pipeline either.
Dokku fits a Unix-comfortable solo developer or a very small team running one region with low complexity. Past that, it runs out of road fast, and no amount of scripting buys back the runway.
CapRover: one-click deployments with a Docker Swarm ceiling
CapRover is a TypeScript-based, open source PaaS, originally released in 2019 as a rebrand of CaptainDuckDuck (which dates back to 2017). It deploys on any Docker-capable infrastructure and ships with a built-in web GUI, automatic SSL and TLS through Let's Encrypt, and a local CLI for scripting.
The real differentiator is the one-click marketplace. Spinning up Postgres, Gitea, n8n, or WordPress takes a couple of clicks, no Dockerfile or compose file required. For teams running common open source stacks, that cuts a real chunk of setup work.
It's still maintained: version 1.14.1 shipped in November 2025. But it's not moving as fast as newer, dashboard-first tools in this space, and the feature gaps below are where that shows.
Underneath, it's Docker Swarm, so there's no Kubernetes path, no service mesh, no GPU scheduling. There's no native preview environment support either, a real gap next to Coolify. And multi-cloud still means manual server setup per cloud, with no unified control plane tying the accounts together. Multi-node scaling works within Swarm's limits, then it just stops.
CapRover suits infra-savvy teams that want a GUI and full self-hosted control, as long as the workload never outgrows what Swarm can do. Plenty do.
Coolify: the closest self-hosted equivalent to a managed PaaS experience
Coolify runs under Apache License 2.0, is Docker-based, and installs with a single curl command, offering a low barrier to entry. It pairs a web UI with a long list of built-in automations and tight Git integration.
The standout feature is native, per-branch preview deployments, something none of the other self-hosted tools in this comparison offer out of the box. For teams whose CI/CD workflow depends on staging previews before merge, that single feature is often the whole reason to pick Coolify over Dokku or CapRover.
Coolify also automates monitoring, backups, and server maintenance scripts, and exposes an API for managing servers and resources, which matters for teams that want deployments scripted rather than clicked through by hand.
The ceiling is the same as CapRover's, just with better polish, and that's worth saying plainly instead of glossing over it. Multi-node scaling runs on Docker Swarm, so no Kubernetes and no service mesh. Multi-cloud still comes down to manually provisioned servers per cloud account, no cross-cloud control plane. And there's no built-in equivalent to deployment health checks or testing integration.
Coolify is the pick for developer-first teams chasing Heroku-like convenience from a self-hosted tool, right up until Docker Swarm's ceiling gets in the way.
Dokploy and Kamal: two different bets on what "minimal" should mean
Dokploy installs in minutes with one command, is free to self-host, and skips Kubernetes entirely. The main codebase runs under Apache License 2.0, but the /proprietary directory falls under the Dokploy Source Available License (DSAL) 1.0, which requires a commercial agreement to use those pieces in production. Dokploy Enterprise adds SSO and SAML, audit logs, fine-grained RBAC, and priority support with SLAs, a wider gap between free and paid tiers than fully MIT-licensed tools tend to carry. Multi-cloud support follows the same pattern as Coolify and CapRover: cloud-agnostic install, no cross-account orchestration.
Kamal is a different animal, and comparing it to Dokploy as if they're fighting for the same job misses the point entirely. Built by 37signals, it's a minimal Docker deploy tool driven by a YAML config file and a single kamal deploy command, pushing containers out over SSH. There's no dashboard, no user management, no service catalogue, none of the trappings of a conventional PaaS. No web UI and no database provisioning either. Every surrounding concern, everything a PaaS usually handles on a team's behalf, becomes the team's job instead.
Calling Kamal a deployment script with strong conventions is more accurate than calling it a platform. Dokploy, by contrast, is a PaaS that can grow toward enterprise compliance needs, at a licensing cost. The real choice is whether a team wants zero abstraction and full SSH-level control, or a managed layer with a clear, if pricier, upgrade path.
Cloud Foundry and Convox: the Kubernetes-native open source tier
Cloud Foundry is built for standardized, multi-cloud application deployment with full infrastructure control and no vendor dependency, and the tooling backs that up. It uses BOSH to deploy and manage large-scale cloud software across platforms, and Korifi, a separate Cloud Foundry community project, offers a Kubernetes-native implementation aimed at internal developer platforms and platform engineering teams. Cloud Foundry supports most major programming languages plus custom buildpacks, and it comes with a modular service marketplace.
It's CLI-first, and the whole operational model assumes a platform engineering team is running it, not two people trying to ship a side project on a Friday night. Cloud Foundry fits large engineering organizations that need a vendor-independent, self-managed multi-cloud platform and already employ the staff to run one. Anyone smaller looking at Cloud Foundry is looking at the wrong tool, full stop.
Convox is lighter, and closer to what a smaller team can actually operate day to day. It's free and open source, and it automatically provisions a Kubernetes cluster and deploys applications onto it, supporting AWS, Google Cloud, DigitalOcean, and Microsoft Azure, genuine multi-cloud at the provisioning layer, not just at the install layer. It covers deployments, rollbacks, CI/CD, secrets management, autoscaling, and logging, all Kubernetes-native. Its footprint is lighter than Cloud Foundry's, closer to a developer tool than a platform engineering project, though community adoption is smaller than the Docker Swarm tools, which means fewer shared answers available when something breaks at 2am.
What puts both of these in a different tier is Kubernetes itself. No Docker Swarm ceiling means Kubernetes-native capabilities are within reach, and multi-cloud gets handled at the platform level instead of through manual, server-by-server setup. The trade-off is complexity: both demand more setup work and more ongoing attention than any of the Docker Swarm tools ask for.
The cost case for self-hosting, and where its limits appear
The headline number, per analysis from kanopylabs.com, is that self-hosted tools like Coolify, Dokku, and CapRover can cut hosting costs by 60 to 80% compared to managed PaaS pricing. Managed platforms often bill per seat or per deployment before a single real user ever touches the app. Self-hosting swaps that billing model for the raw cost of the underlying infrastructure, and for a lot of small teams that math is genuinely lopsided in their favor.
The savings story gets messier once engineering time enters the picture, and this is where most cost comparisons quietly stop being honest. Self-hosting doesn't remove cost, it moves it: cluster upgrades, CVE patching, SSL renewal, database backups, and incident response all become the team's job instead of the vendor's. Docker Swarm tools keep that operational surface smaller and more tractable than Kubernetes-native alternatives. Kubernetes-native tools ask for real expertise before that same 60 to 80% savings shows up reliably, and teams that skip that step usually pay for it in downtime instead of dollars.
Compliance adds another layer. SOC 2 or HIPAA requirements, without automated tooling built into the self-hosted stack, can turn what looked like a one-time cost saving into a multi-month engineering project. A full cost comparison has to count the engineering hours spent maintaining the platform instead of building the product, the cost of any outage caused by a misconfiguration the platform would otherwise have caught, and the fact that moving from Docker Swarm to Kubernetes later isn't an upgrade. It's a migration, full stop, and it should get budgeted like one.
How to match each platform's architecture to your deployment requirements
A few questions actually separate these tools in practice, more than any feature checklist does.
Single server, or multiple nodes? Dokku answers the single-server case well. Docker Swarm tools, Coolify and CapRover, handle multi-node up to their ceiling. Anything past that ceiling points toward Kubernetes-native tools like Cloud Foundry or Convox, and pretending Swarm will stretch further than it does is exactly how teams end up mid-migration under deadline pressure.
How much does the team care about preview environments? Coolify is the only self-hosted open source tool here that offers them natively. For teams whose workflow depends on staging previews, that's close to a dealbreaker.
Does the deployment need to satisfy data residency or compliance requirements across multiple cloud accounts, not just multiple servers? None of the Docker-based tools covered here solve that at the platform level. They solve "runs on any cloud," not "manages multiple cloud accounts from one control plane." Cloud Foundry and Convox get closer, at the cost of needing a team that can run Kubernetes well.
And does the team have, or want to build, the operational capacity that self-hosting demands? That's the real fork in the road. Porter takes a different approach here: instead of self-hosting a PaaS, it deploys production infrastructure straight into a customer's own AWS, GCP, or Azure account, sidestepping vendor lock-in without asking a team to run its own Kubernetes cluster or manage cloud infrastructure by hand. It's one more point on the map between "manage everything yourself" and "hand everything to a vendor," worth weighing alongside the tools above rather than instead of them.
None of these platforms is the wrong choice for everyone. Each one trades simplicity against control, and against how much cloud infrastructure a team is willing to own directly. But there is a real mistake hiding in this list, and it's picking Dokku or Coolify for a workload that's going to need Kubernetes in eighteen months. Better to find that out on day one than mid-migration, with production traffic already depending on the answer.
