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1Fix the driver behind crashes, sound loss and screen glitches2Repair Windows errors before they cause bigger problems3Scan for outdated or missing drivers - takes under a minuteThere is no documented one-click path from Coolify to Dokploy, so plan the move as a rebuild. You recreate each application, back up and restore its state on its own, and shift traffic in stages. The documentation reviewed for this article (Coolify’s docs and Dokploy’s own comparison page, checked October 2026) shows that both tools deploy Docker workloads to servers you control. Their feature lists overlap heavily. A matching checkmark does not mean the controls, defaults or edge cases match.
This is a workload-level plan, not a report of a tested Coolify-to-Dokploy migration. Nothing here is a measured result, and neither vendor endorses the procedure. For someone already running Coolify, switching is worth it only when a specific operational need outweighs the rebuild effort and the cost of learning and maintaining a second control plane.
What the two platforms share, and what the sources actually claim
Dokploy’s documentation includes a comparison with Coolify. It lists both products as supporting Docker Compose, an API and CLI, multi-node setups, monitoring, backups and rollbacks. It also lists some differences, including Bitbucket integration and volume backups. Dokploy’s page positions both tools as self-hosted options for a VPS or your own hardware. It names Docker, Compose, Nixpacks and Buildpacks as Dokploy’s build paths.
Treat that page as a starting inventory, for two reasons:
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- It is vendor comparison material, so its comparative claims (monitoring, alerting, volume backups) are Dokploy’s own and have not been independently verified. Descriptive adjectives such as “polished” or “lightweight” are marketing, not findings.
- A checkmark says a capability exists. It says nothing about how it is configured, what limits it has, or whether it behaves the same under your workload.
On the Coolify side, its documentation says applications can be created from Git repositories, from a Dockerfile without Git, from an existing image, or from a Git-based Docker Compose project. That flexibility is why there is rarely one uniform resource shape to copy across.
Is there a Coolify-to-Dokploy migration tool?
None of the reviewed sources establishes one. Two things can look like migration features and are not:
- Coolify’s instance backup. It restores Coolify’s own control-plane database and configuration. It does not contain application files, database contents, service data or persistent volumes, and its restore guidance stresses keeping the
APP_KEYand, when moving machines, the SSH key files. It is for recovering Coolify, not for feeding another platform. - Coolify’s database-migration API operation. It moves a database to another Coolify-managed server and can optionally transfer persistent volume data. That is a move within Coolify, not a cross-product transfer.
Dokploy-specific import or restore steps for a given database engine are not covered by the sources reviewed here. Check Dokploy’s documentation for the version you deploy before relying on any procedure.
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Why the control plane and the workloads move separately
Coolify’s documentation says it separates platform control from workload runtime. The instance stores configuration and coordinates actions. Docker on the connected servers runs the apps, databases and services. Coolify manages those servers over SSH, and application HTTP traffic goes through the reverse proxy on the workload server, not through the Coolify dashboard.
Two practical consequences follow:
- Your containers, volumes and proxy configuration live on the workload servers. The things you have to reconstruct in a new platform are the definitions that tell it how to create them: sources, settings, variables, domains, schedules and backup jobs.
- Control-plane availability and workload availability are related but distinct. A new platform can be built beside the old one without touching running traffic, which is what makes a staged cutover possible.
A cautious migration plan, application by application
1. Inventory every workload
For each application, record:
- repository and branch, or image and tag;
- build method and deploy command;
- exposed ports, domains and health checks;
- deployment triggers such as webhooks or auto-deploy on push;
- scheduled jobs and rollback needs;
- every environment variable and secret, captured through a secure process (a password manager or encrypted vault, not a chat message).
Keep platform-generated values separate from values your application defines. Generated domains and database credentials are examples of the first kind. They will not carry over, and anything that hard-codes them will break.
2. Back up platform state and workload state separately
Take an instance backup of Coolify so you can recover it if the migration goes wrong. That protects the old platform, not your data.
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For the data, inventory named volumes and bind mounts before deploying anything new. Coolify documents scheduled file-level archives for volume mounts, but warns that an archive taken while a database is writing can be inconsistent. Use an engine-aware database backup instead of copying live data files, and test a restore. Persistent storage is not a backup. It does not protect against disk loss, accidental volume deletion, corruption or loss of the server. Keep copies off the host, for example on S3-compatible object storage or a second server.
3. Recreate and validate databases
Before cutover:
- Take a consistent database backup and note the engine and version.
- List every consumer of the database and the credentials each one uses.
- Restore into a running, compatible target. Coolify’s restore guide says writes should stop first and that an import replaces the target’s data, so never point a restore at a database holding anything you want to keep.
- Check logs and representative records before reconnecting any application to it.
Match engine and major version unless you have a deliberate upgrade plan. Changing both platform and database version in one step makes failures hard to attribute.
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Deploy a parallel copy rather than modifying the live one. Bring over the source code or Compose definition, then reconcile each of these:
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- environment variables and secret values;
- storage paths and volume names;
- network assumptions, such as service hostnames and internal ports;
- domains and health checks;
- build settings.
Compose files need particular care. Coolify’s documentation says definitions carry images or builds, environment references, volumes, health checks, dependencies and network configuration, and that Coolify can add or normalize parts of the deployable definition. The Compose file in your repository may therefore not capture every setting in force on the running service. Compare the file with the runtime configuration (the effective container environment, mounts and networks) before assuming the file is the whole truth. Then check how the new platform handles variable interpolation, and how it names services and volumes. A changed volume name means a fresh, empty volume and no error message.
5. Test before traffic moves
Use a test hostname or private endpoint. Exercise the full request path, not just the container:
- application health, login and representative user journeys;
- database writes, background workers and scheduled tasks;
- outbound integrations such as email, payments and webhooks;
- logs, backup creation and a real restore.
Leave the existing deployment untouched while you compare. Be careful with workers and cron-style jobs: two live copies of the same app can send duplicate emails or process the same queue twice. Pause them on the copy until cutover.
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6. Cut over with a rollback window
- Lower the DNS TTL ahead of time, if your DNS setup allows it, so a revert propagates quickly.
- Freeze or coordinate writes around the final database sync.
- Make the routing change and confirm traffic reaches the new target.
- Keep the old resources and a known-good backup through an agreed observation period.
Decide in advance what triggers a rollback, who performs it, and whether writes made on the new side can be safely reconciled. Avoid promising “zero downtime” unless you can say how writes, sessions, queues and DNS caching are handled. For most single-database apps, a short planned write freeze is the honest design.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Comparing the tools against your workload
Instead of counting checkmarks, test each axis against what you run:
| Axis | What to verify |
|---|---|
| Deployment source and build path | Git provider (Dokploy’s comparison lists Bitbucket integration as a distinction), Dockerfile, prebuilt image, Compose, buildpack or Nixpacks needs |
| State portability | Database engine and version, named volumes, bind mounts, external storage |
| Operations and recovery | Independent backups, tested restores, logs, health checks, rollbacks, alerting |
| Routing and networking | Domains, TLS, proxy behavior, internal service connections, firewall rules |
| Automation and team needs | CI and webhooks, API or CLI use, scheduled jobs, permissions, shared variables, environments |
| Migration cost | Number of resources to recreate, allowable downtime, rollback complexity, your familiarity with the tool |
Volume backups deserve a specific check. Dokploy’s comparison page lists them as a point of difference, while Coolify’s documentation describes scheduled file-level archives of volume mounts. Which one fits depends on the retention, destination and consistency guarantees you need, so confirm those in the documentation for the version you will run. Remember that a volume archive is not a substitute for a database-aware backup either way.
Should you switch?
Reasons that justify the effort are concrete and specific to you: a required capability your current setup cannot provide, a multi-node or automation need, or a build or Git integration you depend on. Reasons that usually do not are a longer feature list or a nicer description on a comparison page.
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If your applications are stable, a switch costs you a rebuild of every definition, a second set of backup and restore procedures to prove, and a new control plane to learn and keep updated. Migrate one low-risk application first. Treat the experience of that single move as your own evidence for the rest, because the published sources contain no migration timings, downtime figures or success rates you could use instead.
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