Kevin Veen-Birkenbach 8409843ff9 fix(restore): wrap the postgres dump replay in a single transaction
The dump replay ran statement-by-statement with autocommit. When restore --empty runs against a LIVE database, the pre-clean drops a table, the replay recreates it and autocommits, and a concurrent writer (discourse's mini_scheduler upserting scheduler_stats(id=1)) inserts the same primary key into the empty table before the dump's COPY loads it. The COPY then aborts with a duplicate-key violation under ON_ERROR_STOP and the whole restore fails. Running the replay with --single-transaction keeps the recreated table invisible to other sessions until commit, so the writer can never insert the racing row.

The --empty pre-clean stays multi-statement (\gexec, one DROP per statement): running every DROP in one transaction exhausts max_locks_per_transaction on large schemas (e.g. gitlab).

Extract the pre-clean SQL from the inline string into restore/db/empty_preclean.sql (loaded via dirname(__file__)) and declare it as package-data so it ships in the wheel. Add a unit test guarding the single-transaction/multi-statement split and an e2e that reproduces the live-writer race.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-07-20 20:00:31 +02:00
2026-07-18 00:39:10 +02:00
2020-10-11 11:54:16 +02:00
2025-12-27 12:49:24 +01:00

baudolo Deterministic Backup & Restore for Docker Volumes 📦🔄

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baudolo is a backup and restore system for Docker volumes with mandatory file backups and explicit, deterministic database dumps. It is designed for environments with many Docker services where:

  • file-level backups must always exist
  • database dumps must be intentional, predictable, and auditable

Key Features

  • 📦 Incremental Docker volume backups using rsync --link-dest
  • 🗄 Optional SQL dumps for:
    • PostgreSQL
    • MariaDB / MySQL
  • 🌱 Explicit database definition for SQL backups (no auto-discovery)
  • 🧾 Backup integrity stamping via dirval (Python API)
  • ⏸ Automatic container stop/start when required for consistency
  • 🚫 Whitelisting of containers that do not require stopping
  • ♻️ Modular, maintainable Python architecture

🧠 Core Concept (Important!)

baudolo separates file backups from database dumps.

  • Docker volumes are always backed up at file level
  • SQL dumps are created only for explicitly defined databases

This results in the following behavior:

Database defined File backup SQL dump
No ✔ yes ✘ no
Yes ✔ yes ✔ yes

📁 Backup Layout

Backups are stored in a deterministic, fully nested structure:

<backups-dir>/
└── <machine-hash>/
    └── <repo-name>/
        └── <timestamp>/
            └── <volume-name>/
                ├── files/
                └── sql/
                    └── <database>.backup.sql

Meaning of each level

  • <machine-hash> SHA256 hash of /etc/machine-id (host separation)

  • <repo-name> Logical backup namespace (project / stack)

  • <timestamp> Backup generation (YYYYMMDDHHMMSS)

  • <volume-name> Docker volume name

  • files/ Incremental file backup (rsync)

  • sql/ Optional SQL dumps (only for defined databases)

🚀 Installation

Local (editable install)

python3 -m venv .venv
source .venv/bin/activate
pip install -e .

🌱 Database Definition (SQL Backup Scope)

How SQL backups are defined

baudolo creates SQL dumps only for databases that are explicitly defined via configuration (e.g. a databases definition file or seeding step).

If a database is not defined:

  • its Docker volume is still backed up (files)
  • no SQL dump is created

No database definition → file backup only Database definition present → file backup + SQL dump

Why explicit definition?

baudolo does not inspect running containers to guess databases.

Databases must be explicitly defined to guarantee:

  • deterministic backups
  • predictable restore behavior
  • reproducible environments
  • zero accidental production data exposure

Required database metadata

Each database definition provides:

  • database instance (container or logical instance)
  • database name
  • database user
  • database password

This information is used by baudolo to execute pg_dump, pg_dumpall, or mariadb-dump.

💾 Running a Backup

baudolo \
  --compose-dir /srv/docker \
  --databases-csv /etc/baudolo/databases.csv \
  --database-containers central-postgres central-mariadb \
  --images-no-stop-required alpine postgres mariadb mysql \
  --images-no-backup-required redis busybox

Common Backup Flags

Flag Description
--everything Always stop containers and re-run rsync
--dump-only-sql Skip file backups only for DB volumes when dumps succeed; non-DB volumes are still backed up; fallback to files if no dump.
--shutdown Do not restart containers after backup
--backups-dir Backup root directory (default: /Backups)
--repo-name Backup namespace under machine hash

♻️ Restore Operations

Restore Volume Files

baudolo-restore files \
  my-volume \
  <machine-hash> \
  <version> \
  --backups-dir /Backups \
  --repo-name my-repo

Restore into a different target volume:

baudolo-restore files \
  target-volume \
  <machine-hash> \
  <version> \
  --source-volume source-volume

Restore PostgreSQL

baudolo-restore postgres \
  my-volume \
  <machine-hash> \
  <version> \
  --container postgres \
  --db-name appdb \
  --db-password secret \
  --empty

Restore MariaDB / MySQL

baudolo-restore mariadb \
  my-volume \
  <machine-hash> \
  <version> \
  --container mariadb \
  --db-name shopdb \
  --db-password secret \
  --empty

baudolo automatically detects whether mariadb or mysql is available inside the container

🔍 Backup Scheme

The backup mechanism uses incremental backups with rsync and stamps directories with a unique hash. For more details on the backup scheme, check out this blog post.
Backup Scheme

👨‍💻 Author

Kevin Veen-Birkenbach

📜 License

This project is licensed under the GNU Affero General Public License v3.0. See the LICENSE file for details.

🔗 More Information


Happy Backing Up! 🚀🔐

Description
Backup Docker Volumes to Local is a comprehensive solution that leverages rsync to create incremental backups of Docker volumes, providing seamless recovery for both file and database data. Ideal for ensuring the integrity and security of your container data.
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