Project Name
Built a Zero-Loss PostgreSQL Recovery System with Automated S3 Backups
Our client is a data-intensive enterprise running business-critical operations on a PostgreSQL database infrastructure. With operational continuity directly dependent on database availability and integrity, the organisation’s data engineering and DBA teams are accountable for ensuring that system failures, data corruption events, or accidental data loss do not result in unrecoverable business disruption.
Operating across multiple functions with compliance obligations around data retention and recoverability, leadership, including CTOs and Compliance Officers, required a robust, automated disaster recovery solution that could guarantee a defined recovery point objective without manual backup processes or operational overhead.
The organisation lacked a reliable PostgreSQL backup and recovery framework, creating data-loss risks, recovery uncertainty, and compliance exposure.
- No Automated Backup Process in Place: There was no scheduled mechanism for PostgreSQL backups, leaving critical operational data dependent on manual or ad hoc processes.
- Zero Recovery Point Guarantee: Without regular backups and defined retention, the organisation had no reliable recovery point, increasing the risk of significant data loss after a failure.
- Manual Recovery Would Be Slow and Error-Prone: Data restoration depended on manual DBA intervention, increasing recovery time, operational effort, and the risk of incomplete recovery.
- No Off-Site or Cloud-Redundant Storage: Database assets lacked a secondary cloud or off-site copy, leaving the organisation vulnerable to infrastructure failures and localised data loss.
- Compliance Exposure From Missing Data Retention Controls: The absence of automated backup records and retention controls made it difficult to demonstrate recoverability during audits or incident reviews.
- No Automated Retention Lifecycle Management: Backups lacked automated lifecycle management, creating risks of unnecessary storage growth or accidental deletion of important recovery points.
Ksolves, an AI-first DevOps consulting services company, engineered a fully automated PostgreSQL backup and disaster recovery pipeline using Apache Airflow and Amazon S3. The solution provides zero-touch backup execution, secure storage, automated retention, and a rolling 3-day recovery window to minimise data loss and downtime.
- Automated Daily Backup DAG: An Apache Airflow DAG runs daily on a defined Cron schedule, executes pg_dump, compresses the backup, and uploads it to Amazon S3 without manual intervention.
- Rolling 3-Day Retention Window: The DAG automatically identifies and deletes backups older than 72 hours, maintaining three recovery points without manual cleanup.
- Amazon S3 Secure Backup Storage: Backups are stored in Amazon S3 with encryption and IAM-based access controls, providing secure, cloud-based redundancy beyond the primary environment.
- Point-in-Time Restoration Capability: Structured backup naming and storage enable DBAs to quickly identify and restore a required recovery point, with restoration targeted to complete in under 15 minutes.
- Pipeline Monitoring and Failure Alerting: Airflow monitors backup execution and immediately alerts the DBA and data engineering team when a DAG fails, preventing missed backup windows from going unnoticed.
Technology Stack
| Category | Technology |
|---|---|
| Database | PostgreSQL |
| Infrastructure | Amazon S3 |
| Processing | Apache Airflow (DAG Engine) |
| Platform | Python Backup Scripts |
| DevSecOps | IAM & Encryption Layer |
| Compliance | Rolling 3-Day Retention Policy |
From no automated backup, defined recovery objective, or cloud redundancy to a zero-touch pipeline maintaining three recovery points and targeted database restoration in under 15 minutes.
- 100% of Critical Database Backups Now Automated – Zero Manual Steps: Airflow handles backup creation, compression, upload, and retention on a fixed schedule, eliminating manual DBA intervention.
- 3-Day Rolling Recovery Window Established – Three Recovery Points Always Available: Three daily snapshots are continuously maintained in Amazon S3, providing reliable recovery points for recent data states.
- Disaster Recovery Time Reduced to Under 15 Minutes: DBAs can restore the database from a retained S3 snapshot in under 15 minutes, significantly reducing recovery time and manual effort.
- Compliance Exposure Reduced Through Automated Audit Trails: Timestamped Airflow logs provide a clear record of backup execution, retention activities, and failures, supporting audit and recovery requirements.
- Storage Costs Controlled Through Automated Retention: Backups older than 72 hours are automatically purged, keeping storage lean without manual cleanup or risking accidental deletion of required recovery points.
The organisation’s PostgreSQL data was critical, but its backup and recovery process was not. Ksolves transformed it into a fully automated, zero-touch backup and disaster recovery workflow using Airflow and Amazon S3. With three rolling recovery points, automated retention, secure cloud storage, monitoring, and targeted restoration in under 15 minutes, the solution provides reliable data protection, faster recovery, and demonstrable compliance readiness.
Is Your Critical Database One Corruption Event Away From Unrecoverable Loss?
