Mainframe Batch Job Snapshot Backup and Replication
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In mainframe computing environments, it is challenging to determine which datasets are utilized by batch jobs and create timely snapshots, especially when replication processes result in outdated copies, making it difficult to restart jobs after interruptions.
Innovation Solution
A method is introduced to identify critical datasets for a job, create current snapshot backups, and replicate these snapshots offsite before the batch job commences, using a processor-based system that inserts additional job steps or utilizes user exits to ensure dataset backup and replication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If replication processes are used to create copies of datasets, then data redundancy is improved, but the copies become outdated and lose consistency with the source data
Solution Approach 1:
The system creates snapshots of datasets at specific points in time before batch jobs execute, ensuring that the snapshot captures the exact state of data needed for job restart. This preliminary action prevents the consistency loss that occurs with continuous replication by freezing the data state at a known good point.
Solution Approach 2:
Instead of using continuous replication that creates outdated copies, the system creates discrete snapshot copies of datasets at predetermined times. These snapshot copies maintain consistency with the source data at the moment of creation, allowing accurate job restart without the consistency degradation inherent in continuous replication.
2Reliability
If snapshots are created before batch jobs commence, then job restart capability is improved, but the time and resources required for backup increase
Solution Approach 1:
The system schedules snapshot creation to occur automatically before batch jobs commence, performing the backup action in advance. This eliminates the need for time-consuming backup operations during job restart scenarios, as the snapshots are already available when needed.
Solution Approach 2:
The system automatically manages snapshot creation and maintenance without requiring manual intervention for each backup operation. The snapshot process is integrated into the batch job scheduling infrastructure, allowing the system to service its own backup needs efficiently.
3Productivity
If critical datasets are identified and backed up selectively, then backup efficiency is improved, but the complexity of identifying critical datasets increases
Solution Approach 1:
The system automatically identifies critical datasets by analyzing batch job definitions and dependencies, without requiring manual specification. The infrastructure itself performs the identification task by examining job control language and data set relationships, eliminating the need for complex external analysis tools.
Solution Approach 2:
The system uses feedback from batch job execution patterns and data set usage information to automatically determine which datasets are critical. By monitoring which datasets are actually used by batch jobs, the system refines its identification of critical data, improving backup efficiency without increasing complexity.
Data Source
Figure 1
Figure 2
Figure 2A
AI summary
A system determines the datasets to be utilized by a batch job prior to- commencement of the batch job. A snapshot of each dataset to be utilized is created. The created snapshot is replicated and a record related to the snapshot is created in a backup table. In the event of disruption of the batch job during processing, each replicated snapshot can be restored and the batch job restarted.