Incremental Backup
An incremental backup is a backup strategy that captures only the data that has changed or been added since the *last* backup of *any type* (full or incremental). In the mainframe z/OS environment, this method is employed to efficiently back up datasets, databases, or file systems by minimizing the amount of data transferred and stored.
Key Characteristics
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- Efficiency: Significantly reduces backup time and storage space requirements compared to full backups, as only modified data blocks or records are copied.
- Dependency: A complete restore operation requires the initial full backup and all subsequent incremental backups applied in chronological order.
- Change Tracking: Relies on system-level mechanisms (e.g.,
VSAMupdate flags,DB2log records,IMSchange accumulation,DFSMSdsschange indicators) to identify changed data. - Utilities: Implemented using specialized z/OS utilities such as
DFSMSdss(Data Set Services),DFSMShsm(Hierarchical Storage Manager),DB2utilities (COPY),IMSutilities, or third-party backup software likeTSM(Tivoli Storage Manager, now Spectrum Protect). - Granularity: Can operate at the dataset, volume, file, or database object level, depending on the specific utility and configuration.
Use Cases
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- Daily Backups: Often used for daily backup cycles after a weekly or monthly full backup to capture ongoing changes with minimal impact on system performance.
- High-Volume Transaction Systems: Ideal for backing up frequently updated
CICSorIMSdatabases andVSAMdatasets where a full backup every day would be impractical. - Disaster Recovery: Forms a critical component of a comprehensive disaster recovery strategy, enabling frequent capture of recent data changes to minimize data loss (
RPO). - Database Point-in-Time Recovery: In conjunction with database logging, incremental backups facilitate recovery to a specific point in time by applying changes from the logs.
Related Concepts
Incremental backups are fundamentally linked to Full Backups, which serve as the baseline from which all subsequent incremental changes are tracked. They differ from Differential Backups, which capture all changes since the *last full backup*, leading to larger backup sets but potentially faster restores than a long chain of incrementals. Database Journaling or Logging (DB2 logs, IMS logs) are crucial for tracking changes at a granular level, enabling accurate incremental backups and point-in-time recovery.
- Regular Full Backups: Periodically perform full backups to reset the incremental chain, simplifying recovery and reducing the number of incremental sets needed for a restore.
- Test Recovery Procedures: Regularly test the full recovery process, including applying all necessary incremental backups, to ensure data integrity and validate recovery time objectives (
RTO). - Retention Policies: Implement clear retention policies for both full and incremental backups, balancing storage costs with recovery needs.
- Performance Monitoring: Monitor the performance of incremental backup jobs to ensure they complete within their allocated windows and do not impact online operations.
- Offsite Storage: Store critical incremental backup copies offsite to protect against site-wide disasters and ensure business continuity.