Storage System Upgrade Scheduling via Workload Segmentation
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Solution Overview
Problem
Upgrading storage systems can impact performance and reliability, with conventional methods causing downtime or prolonged performance degradation due to the need to upgrade multiple components simultaneously, which affects data integrity and service availability.
Innovation Solution
A method that identifies low-workload periods and selects specific components for upgrade, using user information and machine learning models to determine optimal upgrade times and minimize service disruption, allowing for targeted firmware upgrades without affecting ongoing tasks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If firmware upgrade is performed on multiple components simultaneously, then reliability and data integrity are improved, but system performance deteriorates and service availability is reduced
Solution Approach 1:
The patent divides the upgrade process into segments by selecting only certain components for upgrade based on workload thresholds, rather than upgrading all components simultaneously. This segmentation allows the system to maintain reliability improvements while avoiding performance degradation across the entire system.
Solution Approach 2:
The patent implements dynamic component selection by monitoring workload in real-time and adapting the upgrade scope based on current system conditions. The workload threshold mechanism allows the system to dynamically adjust which components are upgraded, balancing reliability improvements with performance maintenance.
2Reliability
If firmware upgrade is performed on multiple components simultaneously, then reliability and data integrity are improved, but service availability is reduced due to downtime
Solution Approach 1:
The patent segments the upgrade operation to affect only a subset of components rather than the entire system. By selecting components based on workload thresholds, the system limits the scope of downtime to minimal necessary components, thereby maintaining service availability while still achieving reliability improvements.
Solution Approach 2:
The patent applies partial action by performing upgrades on only certain components that meet the workload criteria, rather than executing a complete system upgrade. This partial upgrade approach achieves sufficient reliability improvement without incurring the full cost of system-wide downtime.
3Productivity
If workload threshold is set low to maintain service availability, then fewer components are upgraded, but reliability improvement is reduced
Solution Approach 1:
The patent implements a feedback mechanism by continuously monitoring component workloads and using this information to dynamically determine which components should be upgraded. The system adjusts the upgrade scope based on real-time workload data, ensuring that service availability is maintained while still achieving adequate reliability improvement through selective upgrading of appropriate components.
Data Source
AI summary
Embodiments of the present disclosure provide a method, an electronic device, and a computer program product for upgrading a storage system. The method includes: acquiring information about a set of candidate periods related to a workload of a storage system, the storage system having a workload lower than a first predetermined threshold during the set of candidate periods; determining, based on user information of the storage system, a target period for upgrade from the set of candidate periods; and performing an upgrade operation on at least a part of components among multiple components of the storage system during the target period. In this manner, the upgrade operation for the storage system can be improved.