Backup Job Scheduling with Dynamic Priority Queuing
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Solution Overview
Problem
Current data protection systems struggle to guarantee the Recover Point Objective (RPO) due to unpredictable backup job durations, leading to postponed backups and potential failure in protecting important data, as existing solutions cannot effectively manage system resources to meet scheduled backup times.
Innovation Solution
A method for scheduling backup jobs by determining and setting execution priorities based on predetermined information such as priority, execution interval, and waiting time, allowing more important assets to be protected by sorting and queuing jobs accordingly, ensuring better resource utilization and adherence to Service Level Agreements (SLA).
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If backup jobs are scheduled according to administrator-specified time only, then scheduling simplicity is maintained, but backup completion reliability deteriorates due to unpredictable job durations and system workload
Solution Approach 1:
The system dynamically changes the scheduling parameter from fixed administrator-specified time to a calculated start time based on multiple factors including job duration, system workload, and priority levels. This allows the scheduler to adapt to varying conditions while maintaining automated operation.
Solution Approach 2:
The system performs preliminary calculation of the earliest possible start time for backup jobs by analyzing job duration, system workload, and priority before actually scheduling the job. This advance planning ensures that backup jobs can be completed reliably while maintaining operational simplicity.
2Device complexity
If backup jobs are executed without priority differentiation, then system resource management is simple, but critical data protection reliability deteriorates
Solution Approach 1:
The system applies different priority levels to different backup jobs based on their importance and RPO requirements. Critical data protection jobs receive higher priority and are scheduled with more favorable parameters, while less critical jobs are scheduled with standard parameters, ensuring reliable protection of important assets.
3Reliability
If backup jobs are run until finished without scheduling optimization, then data protection completeness is maintained, but time efficiency deteriorates and RPO cannot be guaranteed
Solution Approach 1:
The system dynamically adjusts backup job scheduling based on real-time conditions including system workload, job duration estimates, and priority levels. This dynamic approach ensures that critical backup jobs are completed within required timeframes while maintaining data protection completeness.
Solution Approach 2:
The system uses feedback from job duration analysis and system workload monitoring to continuously optimize backup scheduling. By analyzing actual job completion times and system conditions, the scheduler adjusts future job start times to ensure RPO requirements are met while maintaining efficient resource utilization.
Data Source
AI summary
Embodiments of the present disclosure relate to a method, device, and computer program product for scheduling backup jobs. There is provided a method of scheduling backup jobs, comprising: in response to detecting that a target backup job is generated, obtaining predetermined execution information of the target backup job; determining an execution priority of the target backup job based on the predetermined execution information of the target backup job; determining an execution priority of an existing backup job in a waiting queue; and adding the target backup job to the waiting queue based on the execution priority of the existing backup job and the execution priority of the target backup job. Through embodiments of the present disclosure, it enables better utilization of system resources to achieve the Recover Point Objective for important data, ensuring a Service Level Agreement.