Coolify can dump supported databases on the server where they run, keep a local copy, and upload a second copy to an S3-compatible bucket on a schedule. To configure it, validate an S3 storage target, attach it to a database backup schedule, run a manual test, and perform a real restore into a disposable database. A green upload status alone is not proof that the data is recoverable.
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What Coolify’s S3 database backup actually does
Coolify’s database backup feature is an engine-aware workflow rather than a generic volume copy. At run time, Coolify connects to the database, creates a logical dump on the server hosting that database, and writes the temporary or retained local file under /data/coolify/backups. After the dump succeeds, it uploads a copy to the S3-compatible destination selected in the schedule.
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The two copies have separate lifecycles. A failed S3 upload can leave the local dump available, while the execution records a warning about the remote step. Conversely, selecting Delete after S3 upload removes the local file only after a successful upload; it does not remove the object already stored in S3.
Scheduled work is conditional. Coolify runs a job only while the database is running. It skips an execution when the database is stopped, starting, restarting, or importing. Allow enough time for the dump and transfer; the documented default timeout when no value is supplied is 3,600 seconds.
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Supported databases and important scope limits
The scheduled, database-aware workflow supports PostgreSQL, MySQL, MariaDB, MongoDB, ClickHouse, and SQLite. Redis, Dragonfly, and KeyDB are outside this workflow. Use each of those engines’ persistence and native backup mechanisms, or a separate service that is designed to back them up.
| Database engine | Coolify scheduled S3 workflow | Selection detail |
|---|---|---|
| PostgreSQL | Supported | Specify database names for selective backups |
| MySQL | Supported | Specify database names for selective backups |
| MariaDB | Supported | Specify database names for selective backups |
| MongoDB | Supported | Supports database and collection selection syntax |
| ClickHouse | Supported | Uses Coolify’s engine-aware dump process |
| SQLite | Supported | Back up the database through the scheduled workflow |
| Redis | Not supported by this scheduled workflow | Use persistence or an engine-specific backup tool |
| Dragonfly | Not supported by this scheduled workflow | Use persistence or an engine-specific backup tool |
| KeyDB | Not supported by this scheduled workflow | Use persistence or an engine-specific backup tool |
There are two credential contexts to keep straight. A database component inside a Coolify Service uses credentials resolved in its running container. A standalone database resource uses values stored by Coolify. If a selective backup is configured, PostgreSQL, MySQL, and MariaDB require the database names to be specified; MongoDB can narrow the operation to databases and collections.
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Prepare the S3-compatible destination
You need an object-storage bucket, its endpoint and region details where applicable, and credentials that permit the operations Coolify will perform. Use a dedicated bucket or prefix for backups rather than mixing database dumps with unrelated application objects. Restrict the credentials to the required bucket and prefix, and keep the secret values out of scripts and screenshots.
Validate the storage target in Coolify
- Open the Coolify dashboard and go to the area for S3-compatible storage targets.
- Create or edit a target under S3 storage.
- Enter the endpoint, bucket, region or location value required by your provider, access key, secret key, and any path or prefix settings exposed by your Coolify version.
- Run Coolify’s validation action and wait for a successful result. Do not attach an unvalidated target to a production schedule.
Validation checks the connection and authorization that Coolify can use. It does not demonstrate that a full database dump can be created, that the bucket has sufficient quota, or that a later restore will work. Those require a backup execution and a restore test.
Configure an automatic database backup
Once the target is validated, configure the schedule on the database itself. The labels can vary slightly by Coolify release, but the workflow is the same.
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- Open the supported database resource and select Backups.
- Choose Add schedule.
- Set a named frequency such as
daily,weekly, ormonthly, or enter a cron expression. A cron schedule should be interpreted in the server’s configured time zone, so document that time zone for your operations team. - Set the dump timeout high enough for the largest expected database. If you leave it blank, Coolify documents a default of 3,600 seconds.
- Configure local retention and, if needed, S3 retention. The limits can be expressed by backup count, age in days, and maximum storage in gigabytes.
- Open the schedule’s S3 settings, select the storage target that passed validation, enable S3 uploads, and save the schedule.
- Choose whether to retain the local file. Keep the local copy for fast recovery, or enable Delete after S3 upload only when S3 is deliberately the sole retained copy and its access and retention controls have already been tested.
The schedule does not run against a stopped resource. If a deployment, restart, or import overlaps the scheduled time, Coolify skips that execution rather than taking a dump from a changing state.
Run a first backup and inspect the execution
Do not wait for the first scheduled window to discover a credential, permission, or timeout problem. With the database running, use Back up now from the Backups screen.
- Confirm that the database is in a running state and that no import or restart is in progress.
- Click Back up now on the schedule you configured.
- Open the resulting execution record and wait for it to finish.
- Check the dump result, selected database names, file size, local-file status, and S3 upload status separately.
- Open the bucket or prefix with an independent client and confirm that the expected object exists.
A zero-byte or missing file is a failed backup even if a job was created. If the dump succeeded but S3 failed, preserve the local file while you correct the remote configuration; the execution should identify the S3 warning.
Retention: local and S3 policies are independent
Coolify evaluates local retention and S3 retention separately. For either side, you can limit backups by number, age in days, or maximum storage in gigabytes. A value of 0 means no limit for that dimension. Deletion occurs when any configured limit is reached, with the newest backups kept first.
| Policy choice | Effect | When it fits |
|---|---|---|
| Local count, age, or size limit | Removes older files from /data/coolify/backups as limits are reached |
Control disk usage while preserving a short local recovery window |
| S3 count, age, or size limit | Removes older objects according to the remote policy | Control bucket growth independently of local disk usage |
| Delete after S3 upload | Removes the local copy only after a confirmed upload | Use when remote storage is the intentional primary retention location |
| Zero for one dimension | No limit for that particular dimension | Only when another control, quota, or lifecycle policy governs growth |
For a practical starting policy, retain several recent local dumps for rapid rollback and a longer history in S3. The correct window depends on recovery-point objectives, database growth, bucket cost, and legal or operational retention requirements. Do not assume that an object-storage lifecycle rule and Coolify’s S3 retention settings are interchangeable; document which system is authoritative.
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How to prove an S3 backup is restorable
Coolify’s documentation is explicit: “A successful backup only proves that Coolify created a file.” A successful status is therefore a creation and transfer check, not a recovery guarantee.
Verification after every test or scheduled run
- The execution status is Success.
- The intended database names, and MongoDB collections if selected, are listed.
- The backup file size is greater than zero.
- S3 upload status is successful when S3 is enabled.
- The local copy exists unless Delete after S3 upload was selected.
- The object appears in the expected bucket and prefix with a timestamp that matches the execution.
Perform a disposable restore
- Create an isolated test database or temporary environment that cannot overwrite production data.
- Copy one object from S3 into that environment, or use the local dump if it is still retained.
- Restore with the native tool for the engine and format produced by Coolify. Use credentials with only the permissions needed for the test.
- Check that schemas, tables or collections, indexes, and representative records are present.
- Point a non-production copy of the application at the restored database and exercise reads, authentication, and a representative write path.
- Record the restore duration, any warnings, and the backup timestamp. Repeat at a cadence that matches the value of the data.
A restore test should also cover the failure path: temporarily deny the backup identity access to the bucket and confirm that monitoring notices an S3 warning while any retained local dump remains available. Re-enable access immediately after the test.
Engine-specific planning
PostgreSQL, MySQL, and MariaDB
Use the selective database-name fields when the server hosts multiple logical databases and the schedule should not include all of them. Verify that the names in the execution match the application’s configuration. A successful connection to the server is not evidence that the intended database was included.
MongoDB
MongoDB selection can include databases and collections. Narrowing the scope reduces dump size, but it also increases the chance of omitting a collection that the application later needs. Keep a written inventory of selected namespaces and review it after schema changes.
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Both are included in the scheduled workflow, but their data layout and restore procedures differ from PostgreSQL-compatible engines. Test a native restore into an isolated instance rather than assuming that a file’s presence implies a usable database.
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Redis, Dragonfly, and KeyDB
Do not create a Coolify scheduled S3 database backup for these engines expecting it to behave like the supported workflow. Configure persistence and engine-specific snapshots or use a separate backup-capable service, then test restoration independently.
CLI alternative for repeatable configuration
The Coolify CLI can create a schedule without using the dashboard. A representative pattern is:
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coolify database backup create <database-uuid> --frequency "0 2 * * *" --enabled --save-s3 --s3-storage-uuid <s3-storage-uuid> --retention-days-locally 7This pattern enables a 02:00 cron schedule, turns on the schedule, enables S3 saving, identifies the S3 storage target, and retains local files for seven days. The CLI also exposes options for timeout, database selection, and S3 retention. Run the installed command’s help before scripting because option names and availability can vary by CLI version.
- Find the database UUID and the validated S3 storage UUID in your Coolify installation.
- Run the command with a non-production or test database first.
- Inspect the created schedule in the dashboard and confirm its frequency, timeout, retention, and S3 target.
- Trigger a manual backup and complete the verification and restore checks before applying the same pattern to production.
Troubleshoot common failures
No execution was created
Check that the database was running at the scheduled time and was not starting, restarting, or importing. Confirm that the schedule is enabled and that the cron expression is valid for the server’s time zone.
The dump fails before upload
Review the database credentials in the correct context: service-container credentials for a database component inside a Service, or Coolify-stored values for a standalone resource. Confirm that selected database names exist and that the timeout covers the dump duration.
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The dump succeeds but S3 upload warns or fails
Revalidate the S3 target, then check endpoint, bucket, region, credentials, network egress, and bucket permissions. Keep the local file while investigating unless you intentionally selected deletion after upload. A remote permission failure should not be “fixed” by deleting the only known-good local copy.
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Increase the schedule timeout to exceed the observed dump-and-upload duration, then test during a period representative of production load. The documented unset default is 3,600 seconds; large databases or slow links may require a higher value.
The object exists but restore fails
Check that you downloaded the object completely, used the matching engine and restore utility, and supplied the correct namespace or database selection. Compare the object size with the execution record and repeat the restore from a fresh copy in a disposable environment. If the application still cannot read the result, treat the backup as unproven and investigate the dump and restore logs rather than relying on the green upload status.
Security and operational controls
- Use a dedicated S3 identity with the narrowest bucket and prefix permissions practical.
- Rotate access keys and update the validated Coolify target through a controlled change.
- Encrypt the bucket and restrict public access; database dumps commonly contain credentials and personal data.
- Separate production and test prefixes or buckets so restore exercises cannot overwrite live objects.
- Monitor both execution status and bucket growth. An alert that checks only for a scheduled job can miss repeated S3 warnings.
- Record the schedule, time zone, timeout, retention values, selected databases, storage target, and last successful restore date.
- Calculate capacity from actual dump sizes and growth, not from the database’s nominal disk allocation.
Do not confuse database backups with Coolify instance backups
A Coolify instance backup covers Coolify’s own projects, resources, settings, and deployment history. It does not include data inside deployed applications, databases, or volumes. You need the database schedule described here for database contents.
For instance recovery, preserve the complete APP_KEY separately. Without that key, restored encrypted secrets cannot be read even if the instance backup itself is available. Test instance recovery and database recovery as two related but distinct procedures.
Production readiness checklist
- Every supported production database has an enabled schedule.
- The selected engine is covered by Coolify’s workflow, or an alternative is documented for Redis, Dragonfly, or KeyDB.
- The S3-compatible target validates successfully.
- The schedule’s database selection is explicit and reviewed after schema changes.
- Timeout, local retention, and S3 retention are sized for current growth.
- A manual run produced a non-zero file and a successful upload.
- The local-versus-remote deletion policy is intentional.
- An object was restored into a disposable database and the application passed a read test.
- Operators know where to find execution warnings and who owns S3 credentials.
- The complete Coolify
APP_KEYis preserved for instance recovery.
The Bottom Line
Use Coolify’s validated S3 target and database schedule for automated copies, retain a local recovery window when you need speed, and accept a backup as reliable only after a disposable restore proves the application can read it.
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