Implementing Automatic Restoration from Backup on Failure
Automatic restoration is next level after having backups. System detects problem itself, chooses recovery point, spins up infrastructure, verifies result. Human involvement — only final verification.
Automatic Restoration Scenarios
DB data corruption. Trigger: monitoring detects anomaly (sharp error spike, checksum mismatch). Automation: stop writes to corrupted DB, restore from last valid snapshot, verify integrity, switch traffic.
Filesystem failure. Trigger: mount fails or read-only mode. Automation: Terraform creates new instance with clean disk, rsync or S3-sync restores data, application restarts.
Complete server failure. Trigger: health check fails N times in a row. Automation: Auto Scaling Group (AWS) or equivalent spins new instance from AMI, cloud-init deploys config, data mounted from persistent storage.
PostgreSQL Architecture
Point-in-Time Recovery (PITR) — foundation for automatic restoration in relational DBs.
WAL archiving to S3:
# postgresql.conf
wal_level = replica
archive_mode = on
archive_command = 'aws s3 cp %p s3://mybackups/wal/%f'
restore_command = 'aws s3 cp s3://mybackups/wal/%f %p'
Base snapshots via pgBackRest or pg_basebackup — daily to S3.
Restoration automation:
def auto_restore_postgres(target_time: datetime, db_config: dict):
# 1. Find closest base backup before target_time
base_backup = find_latest_base_backup_before(target_time)
# 2. Provision new PostgreSQL instance
instance = provision_postgres_instance(db_config)
# 3. Restore base backup
restore_base_backup(instance, base_backup)
# 4. Apply WAL logs until target_time
apply_wal_until(instance, target_time)
# 5. Verify integrity
verify_database_integrity(instance)
return instance
Tools: pgBackRest (best for PostgreSQL), Barman, WAL-G (minimalist, popular in cloud).
Automatic File and Media Restoration
For S3/object storage: AWS S3 Versioning + S3 Object Lock protect from accidental deletion. Restore specific file version — via AWS Lambda, triggered by SNS event or app request.
For filesystems: EBS snapshots (AWS) or Persistent Disk (GCP) scheduled every 4-6 hours. Terraform script restores volume from snapshot and mounts to new instance.
Verification After Restoration
Automatic restoration without verification — half-baked solution. Required checks:
def verify_restoration(instance):
checks = [
check_db_connectivity(instance),
check_row_counts(instance, expected_counts),
check_referential_integrity(instance),
check_recent_data_present(instance, min_age_minutes=5),
run_application_smoke_tests(instance),
]
return all(checks)
If verification fails — automation tries previous recovery point or escalates alert to team.
Restoration Orchestration
AWS Systems Manager Automation or Ansible playbook triggered by event:
- CloudWatch Alarm → SNS Topic → Lambda function
- Lambda initiates SSM Automation Document
- SSM executes steps: provision → restore → verify
- On result: switch Route 53 or escalate to PagerDuty
For Kubernetes: Velero restores namespace from snapshot. Operator pattern — custom Kubernetes Operator monitors PVC state and auto-restores on issue detection.
Testing Automatic Restoration
Weekly scheduled test: automation spins isolated backup copy in separate environment, runs verification, sends report. If verification passes — backups valid. If not — alert without waiting for real incident.
Metrics for Monitoring
- RTO actual — time from problem detection to restoration verification
- RPO actual — data lost (difference between last backup and failure moment)
- Backup freshness — age of last successful backup per component
- Restore test success rate — % successful automatic test-restores per month
Implementation Timeline
- PostgreSQL PITR with WAL archiving — 3-5 days
- S3 versioning + Lambda auto-restoration — 2-3 days
- ASG + cloud-init server auto-restoration — 3-5 days
- Orchestration + verification + alerts — 3-5 days
- Testing and documentation — 2-3 days
Total: 2-3 weeks for complete automatic restoration system.







