Storage Topology Selection for Network Protection Policy Changes
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Solution Overview
Problem
Existing data storage systems face challenges in efficiently changing protection levels for datasets due to the manual and resource-intensive process of reconfiguring storage object relationships, which can lead to inadequate protection and performance issues during disaster recovery, especially when switching from backup to mirroring protocols.
Innovation Solution
A method and system that provide a topology set for storage administrators to select a new protection policy, automatically generating and prioritizing topology options based on performance penalties, such as rebaseline requirements, to facilitate efficient data replication and minimize network disruption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual reconfiguration of storage object relationships is performed to change protection policy, then protection level can be changed, but the process becomes resource-intensive and time-consuming
Solution Approach 1:
The system pre-generates multiple candidate topology configurations before the actual protection policy change is needed. These topologies are prepared in advance with different storage object relationships, allowing the administrator to quickly select and apply a pre-configured topology instead of manually reconfiguring during the policy change process.
Solution Approach 2:
The system automatically generates and evaluates candidate topology configurations using algorithms that assess performance penalties and rebaseline requirements. This automation eliminates the need for manual analysis and configuration by administrators, allowing the system to self-determine optimal topology options based on the new protection policy requirements.
2Adaptability or versatility
If storage object relationships are manually reconfigured to implement new protection policy, then protection policy can be changed, but performance penalties and network disruption occur
Solution Approach 1:
The system evaluates each candidate topology configuration by calculating performance penalties and rebaseline requirements as feedback metrics. This feedback mechanism allows the system to assess the impact of each topology option on network performance and data protection reliability, enabling informed selection of the optimal configuration that minimizes disruption.
Solution Approach 2:
The system changes key parameters of the topology configurations, such as storage object relationships and replication paths, to optimize performance. By adjusting these parameters in pre-generated topologies, the system can find configurations that achieve the new protection policy while minimizing performance penalties and network disruption.
3Reliability
If comprehensive topology analysis is performed to select optimal configuration, then data loss risk is reduced, but computational complexity increases
Solution Approach 1:
The system segments the comprehensive topology analysis into distinct evaluation criteria, such as performance penalty assessment and rebaseline requirement analysis. By dividing the complex analysis into separate manageable components, the system can evaluate each aspect independently and combine the results to determine the optimal topology configuration.
Solution Approach 2:
The system introduces an intermediary evaluation layer that assesses candidate topologies based on predefined criteria. This intermediary analysis mechanism acts as a mediator between the raw topology configurations and the final selection, providing structured evaluation that reduces data loss risk without requiring the entire system to become more complex.
4Ease of operation
If multiple topology options are generated and evaluated, then optimal configuration can be selected, but processing time and resources increase
Solution Approach 1:
The system generates and evaluates multiple candidate topology configurations, which is more than the single configuration approach. By providing multiple options with evaluated performance characteristics, the system enables more accurate selection while the automated evaluation process maintains efficiency, balancing selection accuracy with configuration speed.
Data Source
AI summary
Embodiments of the present invention provide a method and system for providing, in a network storage system, a topology set to a storage administrator for selection of a topology to implement a new protection policy for a dataset. A topology includes a mapping between storage objects participating to effectuate an existing protection policy and storage objects participating to effectuate the new protection policy. When a storage administrator selects a new protection policy, a storage manager automatically generates a number of topology options including a storage object participating in the existing protection policy. According to a priority rule, the storage manager determines the priority of the topologies by computing a priority indicator for each of the topologies. In certain embodiments, the topology set is displayed to a storage administrator including the priority indicator for each topology for informing the storage administrator the relative preference of each topology. The storage administrator thereby selects a topology for configuring storage objects to participate in effectuating the new protection policy.