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The dependable way to automate Coolify backups is to run two different schedules: a storage backup for application files and an engine-aware database backup for database records. Storage backups create compressed archives from an eligible volume or directory mount, optionally copy them to validated S3-compatible storage, and apply local and remote retention rules. Database schedules create dumps appropriate to the database engine. Neither workflow replaces the other.
After scheduling, inspect executions and perform a test restore. A successful archive or dump proves that a job ran; it does not prove that your application can use the result.
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What Coolify can back up—and what each workflow means
Coolify separates application storage from database data because the two types require different consistency methods.
| Workflow | Data covered | How consistency is handled | Remote copy | Restore behavior |
|---|---|---|---|---|
| Storage backup | Files in an eligible volume or directory mount | You choose whether containers keep running or stop while the archive is created | Optional upload to a validated S3-compatible storage destination | No dashboard restore action; download the archive and test restoration separately |
| Database backup | Records managed by a supported database engine | Coolify runs an engine-aware database backup on the database server | Optional S3 upload, with retention settings | Restore into a disposable database and verify that the application can read it |
| Coolify control-plane backup | Coolify projects, resources, settings, and deployment history | Protects the Coolify instance configuration, not application data | Depends on how you store the instance backup | Requires the original encryption key to read stored credentials and private keys |
Persistent storage is not automatically a backup. Coolify’s documentation states: “Persistent storage keeps data outside a replaceable container, but it is not a backup.” Keep at least one tested copy away from the deployment server.
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Prepare the application before creating a schedule
Check that the mount is eligible
Storage backups work with an application’s Volume Mount, whether or not it has a Source Path, and with a Directory Mount. They do not support File Mount or Host File Mount entries for this workflow. If the data you need is attached through one of the unsupported mount types, change the storage design or use a separate backup process.
Decide which data belongs in a file archive
Uploads, generated assets, configuration files, and other file-based state are candidates for a storage schedule. Database tables, indexes, transaction logs, and engine metadata should be protected by a database schedule. Archiving a database volume while the engine is writing can produce an unusable or internally inconsistent copy.
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For an off-server copy, create and validate an S3-compatible storage destination in Coolify before attaching it to a schedule. A local archive protects against an application deployment mistake, but not against loss of the deployment server itself.
Choose a consistency policy
In a storage schedule’s general settings, you can keep containers running or stop them during the archive. Keeping them running avoids an outage but permits files to change during the operation. Stopping them makes the application unavailable for that step, while reducing the chance of a partially changed file being captured. Coolify’s documentation warns that “A file-level archive can contain inconsistent data.” If the application offers an application-aware export, prefer it for data that must be transactionally consistent; otherwise, stop writes or containers for the archive window.
Set up an automated application storage backup in the dashboard
1. Open the storage backup screen
- Open the relevant project in Coolify.
- Select the environment that contains the application.
- Open the application and choose Backups.
- Under Storage backups, select Add.
2. Select the volume or directory
Choose the eligible Volume Mount or Directory Mount that contains the files to protect. If the application has several independent data locations, create a schedule for each one or confirm that a single selected mount contains all required files.
3. Set the frequency
A new schedule defaults to daily. You can keep that named frequency, choose another named interval, or enter a five-field cron expression.
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| Coolify value | Equivalent cron expression | Interpretation |
|---|---|---|
every_minute |
* * * * * |
Every minute |
hourly |
0 * * * * |
At minute 0 of every hour |
daily |
0 0 * * * |
At midnight every day |
weekly |
0 0 * * 0 |
At midnight each Sunday |
monthly |
0 0 1 * * |
At midnight on the first day of each month |
yearly |
0 0 1 1 * |
At midnight on January 1 |
A custom cron expression is useful when the archive must avoid a maintenance window or a known high-write period. Record the intended timezone and verify the first execution rather than assuming the schedule ran at a particular local time.
4. Choose whether containers stop
Open the schedule’s general settings and set the stop-during-backup option. Use running containers when uninterrupted service is more important than a perfectly quiescent file tree. Use stopped containers when writes must pause for a coherent point-in-time archive.
5. Configure S3 and retention
Enable the validated S3-compatible destination when you need an off-server copy, then choose whether Coolify should retain the local archive after a successful upload or delete it. Local and S3 retention are independent. Each side can have its own limits for:
- How many archives to keep.
- How old an archive may be.
- How much total storage archives may consume.
Keeping a local copy can make a nearby recovery faster. Deleting it after a verified upload reduces disk usage, but leaves the remote copy as the immediately available version.
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Open the schedule’s Executions view after the first run. Treat Success with an available location as a usable result. Treat Success (S3 Warning) as a local success with a failed remote upload; investigate the S3 destination before relying on it for disaster recovery. Failed and Needs attention require investigation before you count the run as a backup.
Automate storage schedules through the authenticated API
For many applications, infrastructure-as-code workflows, or repeatable environment setup, use the authenticated Coolify API. The schedule endpoint is:
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PUT /api/v1/applications/{{application_uuid}}/storages/{{storage_uuid}}/backupsSend the schedule values supported by your Coolify version, including:
frequencyandenabled.save_s3and the selecteds3_storage_uuidwhen a remote copy is required.- The local and S3 retention fields exposed by the endpoint.
stop_during_backupto control write quiescence.timeoutto limit how long the operation may run.
A minimal request shape looks like this; replace the double-curly-brace variables with values from your environment and include the retention properties required by your API version:
PUT /api/v1/applications/{{application_uuid}}/storages/{{storage_uuid}}/backups
{
"frequency": "daily",
"enabled": true,
"save_s3": true,
"s3_storage_uuid": "{{s3_storage_uuid}}",
"stop_during_backup": false,
"timeout": "{{timeout}}"
}The API replaces the schedule for the specified application storage. Authenticate the request as an account permitted to manage that application and storage, and keep the request definition under the same change control as the rest of your deployment configuration.
To queue an immediate run, the storage must already have a schedule. Send an authenticated request to:
POST /api/v1/applications/{{application_uuid}}/storages/{{storage_uuid}}/backups/runUse the immediate run after changing a schedule, before a migration, or when you need to verify the archive and S3 path without waiting for the next cron occurrence. Check the resulting execution in the dashboard and confirm that the reported location is accessible.
Schedule database dumps with the Coolify CLI
1. Verify the CLI context and discover resources
coolify context verify
coolify database list
coolify s3 listThese commands confirm that the CLI is pointed at the intended Coolify instance, show database identifiers, and show the S3 destinations available for remote copies. Do not create a schedule against an identifier from a different context.
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2. Create the recurring database schedule
The following example runs at 02:00 according to the scheduler’s cron interpretation, enables the job, saves to S3, and retains seven days of local copies:
coolify database backup create {{database_uuid}} --frequency "0 2 * * *" --enabled --save-s3 --s3-storage-uuid {{s3_uuid}} --retention-days-locally 7Save the backup UUID returned by the command. You will need it to trigger an immediate execution or to identify the schedule during operations work.
3. Trigger a run when you need an immediate dump
Use coolify database backup trigger with the backup UUID returned during creation. The trigger is useful for validating credentials, testing an S3 destination, or taking a dump immediately before a risky change.
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4. Inspect executions
Run coolify database backup executions for the backup schedule and verify the result, destination, and timing. A scheduled job that has never produced a confirmed execution should not be treated as protection.
Supported and unsupported database engines
Coolify’s scheduled database workflow supports PostgreSQL, MySQL, MariaDB, MongoDB, ClickHouse, and SQLite. It does not support Redis, Dragonfly, or KeyDB through this workflow. For those engines, use the engine’s own persistence and backup facilities or deploy a separate backup-capable service.
Database jobs run on the database server and only while the database is running. A stopped database cannot produce a scheduled dump, so include database availability in your monitoring and recovery plan.
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Design frequencies and retention around recovery needs
Use the shortest interval that matches how much data you can afford to lose and how much storage and transfer your retention policy can support. A practical policy often gives databases a different schedule from large file trees:
| Application state | Storage schedule example | Database schedule example | Operational reason |
|---|---|---|---|
| Frequently changing production data | Daily or a custom cron window, with containers stopped if file consistency requires it | Daily at a low-traffic hour, such as 0 2 * * * |
Reduces the interval between recoverable points while limiting disruption |
| Occasionally changing content | Weekly or monthly | Weekly or daily, depending on record-change tolerance | Avoids creating archives more often than the data changes |
| Pre-migration or pre-deployment checkpoint | Trigger an immediate storage run through the API | Trigger an immediate database run through the CLI | Creates a known checkpoint before an irreversible operation |
These are scheduling patterns, not guarantees. Measure archive size, runtime, and the amount of data your application can recreate before selecting retention limits. Set local and S3 policies independently so that a full local disk does not silently prevent remote retention, and so that remote lifecycle limits do not remove every copy you intended to keep.
Prove that backups can be restored
Storage archive test
- Select a recent execution marked Success with an available location.
- Copy the archive to an isolated test host or a disposable deployment environment. Do not overwrite production data.
- Extract it into a test mount that matches the application’s expected directory layout.
- Start a disposable application instance against the extracted files.
- Check representative uploads, generated assets, permissions, and application logs.
- Record the archive identifier, extraction steps, and any ownership or permission adjustments needed for a real recovery.
Storage backups have no dashboard restore action, so a download-and-restore exercise is the only way to validate the archive’s practical usefulness. If the application was left running during the archive, test files that were actively changing; a successful extraction alone does not prove that those files are coherent.
Database restore test
- Choose a completed database execution and obtain its dump from the reported location.
- Create a disposable database instance running the same engine and a compatible version.
- Restore the dump using that engine’s documented restore procedure.
- Run representative queries and inspect schema objects, indexes, and row counts that matter to the application.
- Point a disposable application at the restored database and confirm that it can authenticate, read, and perform a safe test write.
- Document the time required, credentials needed, and any version or extension prerequisites.
Coolify’s documentation puts the rule plainly: “A backup is not a restore test.” A dump that cannot be restored within your recovery window is not an adequate recovery plan, regardless of its execution status.
Troubleshoot failed or incomplete runs
| Observed status or symptom | What it means | Next checks |
|---|---|---|
| Success with a location | The archive or dump completed and a location is available | Download a copy, verify its size and accessibility, and include it in a restore test |
| Success (S3 Warning) | The local archive succeeded but the S3 upload failed | Check S3 credentials, bucket or endpoint configuration, network access, available capacity, and whether the destination remains validated; rerun after correction |
| Failed | The backup operation did not complete | Review execution details, mount selection, permissions, free space, timeout, and database availability; correct the cause before relying on the schedule |
| Needs attention | Coolify requires operator review | Open the execution details, determine whether a local or remote artifact exists, and either repair the schedule or perform a fresh run |
| No database execution while the schedule is enabled | The database may be stopped when the scheduler runs | Confirm that the database is running on its server during the cron window |
| Archive contains changing or incomplete files | Writes occurred while a file-level archive was being created | Use an application-aware export where available, or stop writes and containers during the archive |
Back up Coolify itself separately
An instance-level Coolify backup protects Coolify’s own projects, resources, settings, and deployment history. It does not include application data, database contents, or mounted volumes. Schedule and test application storage and database backups even when the control plane is protected.
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Quick Recap
A repeatable operating checklist
- List every application Volume Mount and Directory Mount that contains irreplaceable files.
- Exclude File Mount and Host File Mount entries from the storage-backup workflow.
- Create a storage schedule for file data and an engine-aware database schedule for records.
- Use a validated S3-compatible destination for at least one copy outside the deployment server.
- Choose running or stopped containers deliberately, based on write consistency and outage tolerance.
- Set local and S3 retention limits independently and monitor available capacity.
- Verify the first execution and investigate every S3 Warning, Failed, or Needs attention result.
- Remember that database schedules cover PostgreSQL, MySQL, MariaDB, MongoDB, ClickHouse, and SQLite—not Redis, Dragonfly, or KeyDB.
- Run a disposable storage restore and database restore on a recurring basis.
- Protect the Coolify control plane and store the complete
APP_KEYline separately.
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