Move backup execution out of the management command into a reusable
backup runner service that can execute an existing BackupRun record.
Add queue primitives and a run_pobsync_worker command so manual backup
requests can be recorded as queued SQL state and processed outside the
web request path.
Add a worker Docker service and pobsync worker CLI alias, with tests for
queued run creation, worker execution, manual run typing, and command
mapping.
Stop passing prune options into the legacy scheduled backup engine from the
Django backup command. Record the completed snapshot first, then apply retention
through the SQL-backed retention service so pruning sees the same SnapshotRecord
state as the admin and retention command.
Also record prune failures on BackupRun.result instead of leaving the run in an
ambiguous state.
Add a nullable SnapshotRecord foreign key to BackupRun and populate it
when run_pobsync_backup records a completed or failed snapshot. Keep the
existing snapshot_path for audit compatibility while making run-to-snapshot
navigation explicit in the database and admin.
Upsert SnapshotRecord rows directly from run_pobsync_backup results so
new successful and failed backup runs are reflected in the database
without requiring a separate discovery pass. Keep discovery for existing
snapshots and repair workflows, and cover success, failure, and dry-run
behavior with tests.
Allow retention planning and pruning to use the same ConfigSource
abstraction as scheduled backups. This removes the remaining SQL-to-YAML
export dependency from Django backup runs with pruning, keeping YAML only
as a legacy CLI compatibility path.
Introduce a ConfigSource interface so scheduled backups no longer need
to load host configuration directly from runtime YAML. Add a Django-backed
config source for SQL-driven backup runs, keep file-based config as the
CLI default, and make scheduled prune execution actually apply retention
after successful runs.
Treat SQL-backed Django models as the source of truth for pobsync
configuration, exporting runtime YAML only as a compatibility layer for
the existing engine. Add a database-driven scheduler command, Docker
scheduler services, schedule run-state fields, and tests for scheduler,
config export, and retention behavior.
Add a Django admin-backed management layer for pobsync configs, runs,
snapshots, and schedules. Keep the existing CLI engine as the execution
source of truth, add import/run management commands, and provide SQLite
default plus optional MariaDB Docker Compose support.
