Catalog
method#Reliability#Platform#Observability#Security

Backup and Recovery

Methodical process for protecting and restoring data and systems to minimize downtime and data loss.

Backup and Recovery is a methodical process to ensure restoreability of data and systems after failures.
Established
Medium

Classification

  • Medium
  • Technical
  • Architectural
  • Intermediate

Technical context

Object storage (e.g., S3-compatible)Kubernetes backup operatorsDatabase-specific tools (e.g., pg_basebackup, mysqldump)

Principles & goals

Avoid single points of failure via redundancy and offsite copies.Define clear RTO/RPO and prioritize assets accordingly.Validate backups regularly through restore tests.
Run
Enterprise, Domain, Team

Use cases & scenarios

Compromises

  • Faulty or corrupted backups going undetected.
  • Insufficient testing leading to false assumptions about recoverability.
  • Attacks on backup archives (e.g., ransomware) compromising restores.
  • Implement 3-2-1 rule (3 copies, 2 media, 1 offsite copy).
  • Encrypt backups at rest and in transit.
  • Conduct regular, scheduled recovery drills.

I/O & resources

  • Asset inventory and classification
  • RTO/RPO specifications
  • Available storage and network infrastructure
  • Documented backup strategy and playbooks
  • Planned recovery tests and reports
  • Monitoring metrics for RPO/RTO

Description

Backup and Recovery is a methodical process to ensure restoreability of data and systems after failures. It covers strategy, retention, backup mechanisms, validation, and recovery testing. The goal is to minimize data loss, recovery time, and operational downtime through defined processes, roles, and periodic verification.

✔

  • Reduced data loss and faster business resumption.
  • Improved compliance and traceability of recovery processes.
  • Increased system resilience through documented processes and tests.

✖

  • Requires additional storage and operational costs.
  • Complexity increases with heterogeneous system landscapes.
  • Incomplete backups can make recovery impossible.

  • RTO (Recovery Time Objective)

    Maximum tolerable time to restore a service.

  • RPO (Recovery Point Objective)

    Maximum tolerable data loss measured in time (e.g., minutes/hours).

  • Restore duration and success rate

    Measured time and share of successful restores during drills.

Database point-in-time restore

Example implementation of a point-in-time restore for PostgreSQL using WAL archiving with full validation.

Cloud backup using object storage

Use of incremental backups to object storage with lifecycle policies for cost optimization.

Offsite backup and disaster recovery

Combination of daily snapshots and weekly offsite archive copies to protect against site failure.

1

Inventory critical assets and classify by business value.

2

Define RTO/RPO and prioritize backup targets.

3

Select appropriate backup media and methods (snapshots, incremental, replication).

4

Automate backup execution and set up monitoring.

5

Regularly validate via restore tests and document results.

6

Continuously adjust retention and cost strategy.

⚠️ Technical debt & bottlenecks

  • Old, unstructured backup scripts without automation.
  • Missing monitoring and alerting mechanisms for backup failures.
  • Undocumented restore processes for critical assets.
Network bandwidth for replicationStorage performance during restoreStaff availability for disaster recovery
  • Restoring corrupted backups without integrity checks.
  • Using old snapshots that do not meet compliance requirements.
  • Using production backups for test environments without masking sensitive data.
  • Assuming backups automatically mean restores will work.
  • Underestimating network capacity for regular replication.
  • Neglecting test documentation and lessons learned.
System and storage administrationDatabase-specific knowledgeSecurity and compliance understanding
RTO and RPO requirementsData classification and compliance requirementsCost and retention strategy
  • • Budget constraints for redundant infrastructure
  • • Data sovereignty and regulatory requirements
  • • Technical compatibility of heterogeneous systems