Network-Informed Policy Creator for Backup Optimization
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Solution Overview
Problem
Current backup software treats all stages of data backup as a single process, leading to unpredictable load distribution and potential backup failures due to overloaded systems, as it lacks the ability to determine the best time and path for data transfer based on network conditions and historical data.
Innovation Solution
A network-informed policy creator that connects with network devices to monitor data flow, gather historical data, and recommend optimal transfer times and paths, decoupling backup stages and optimizing data transfers by determining the best time to transfer data based on available bandwidth and resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If backup software treats all stages as a single process, then the backup operation is simplified to one unified process, but the system becomes unpredictable and prone to overload during data transfers
Solution Approach 1:
The backup process is divided into distinct stages: snapshot creation, data transfer, and storage. Each stage can be independently managed and optimized, allowing the system to handle load dynamically at each phase rather than as a monolithic process, thereby improving reliability without excessive complexity.
Solution Approach 2:
The system dynamically adjusts backup operations based on real-time network conditions and system load. By monitoring network bandwidth and system resources during each stage, the backup process can adapt its timing and resource allocation, preventing overload while maintaining operational simplicity.
2Ease of operation
If backup operations are performed without considering network conditions, then the backup process is straightforward and simple, but backup failures occur due to overloaded systems and missed service level objectives
Solution Approach 1:
The system continuously monitors network conditions, system load, and backup progress, using this feedback to dynamically adjust backup operations. This automated feedback loop maintains simplicity for the user while improving productivity by preventing failures due to overloaded systems.
Solution Approach 2:
The backup system automatically monitors its own performance and network conditions, making real-time decisions about when and how to perform backups without user intervention. This self-service capability maintains operational simplicity while ensuring backups complete successfully by avoiding system overload.
3Device complexity
If network tools only monitor quality metrics like latency and packet loss, then the monitoring system remains simple, but the system cannot determine the best time or path for data transfer
Solution Approach 1:
The system performs preliminary monitoring of network conditions and historical performance data before initiating backup transfers. By gathering this advance information about network quality and system load, the system can proactively select optimal transfer times and paths, reducing actual transfer time without requiring complex real-time decision-making during the transfer itself.
Data Source
AI summary
Embodiments for optimizing multiple backup operations for a data protection system, by determining a size of a dataset to be saved in each backup operation and an available bandwidth in each transfer window of a plurality of transfer windows for transfer data between a source and destination; then determining an order of the backup operations based on first ordering the backups based on decreasing dataset size and second ordering the transfer windows in order of decreasing bandwidth, and matching the backups to the transfer windows in accordance with the first ordering and second ordering. The optimum time represents a time to initiate the backup operation that results in a shortest data transfer time over all of the transfer windows from as compared to other possible transfer windows in a defined backup period.