Automate Backup Retention Policies

Backup Retention Policy helps develop, implement, and manage backup retention policies across cloud and on-premises storage. It connects the recovery policy to concrete storage and rotation decisions, covering data lifecycle management, disaster recovery, storage optimization, and automated cleanup.

The foundation is the 3-2-1-1-0 rule: three copies of critical data, two storage media types, one offsite or cloud copy, one offline or immutable copy, and zero errors after recovery testing. Storage is divided into hot, warm, cold, and archive tiers. The example tier windows are 0-30 days for hot storage, 30-90 days for warm storage, 90 days to seven years for cold storage, and seven years or more for archives.

Retention schedules distinguish daily, weekly, monthly, and yearly backups. The examples connect backup frequency, retention duration, and storage tier instead of treating every backup as an identical file with one expiration date.

Use this skill when a backup policy needs to reflect maximum allowable downtime and data loss. Recovery Time Objective (RTO), Recovery Point Objective (RPO), regulatory requirements, data classification, and change frequency all shape the schedule. Critical, important, standard, and non-essential data can therefore receive different treatment.

The policy guidance also covers deletion, data minimization, purpose limitation, and record retention considerations. Its regulatory examples provide context for policy development; choosing a schedule still depends on the applicable business and compliance requirements.

Operational reviews include monthly selective recovery tests, quarterly disaster recovery drills, and an annual policy review. This makes retention review part of recovery readiness rather than merely a check that old files disappeared.

Inputs are the recovery objectives, classification of the data, backup frequency, storage environment, and retention obligations. Outputs include a documented retention schedule and implementation examples for moving or removing backups at the appropriate age.

The documentation template includes classification targets, a backup-type schedule, storage tiers, and compliance requirements. Cost optimization guidance covers deduplication, compression, cloud tier transitions, policy audits, selective cross-region replication, and automated cleanup to reduce policy drift.

AWS S3 lifecycle examples transition objects through STANDARD_IA, GLACIER, and DEEP_ARCHIVE before expiration. Azure Backup examples use PowerShell retention and schedule objects for virtual machine backups. Local rotation examples use Bash to remove expired daily and weekly archives and move monthly files into cloud storage.

PostgreSQL guidance covers WAL archiving and point-in-time recovery, while MySQL examples address binary log expiration and consistent database dumps. A boto3 validation example checks S3 objects against the configured retention period.

SET GLOBAL binlog_expire_logs_seconds = 604800; -- 7 days