Block Storage I/O Performance Adjustment for Cloud Backup Spikes
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Solution Overview
Problem
Block storage systems in public clouds face performance issues and potential system crashes due to I/O spikes during data backup and recovery tasks, which can be unpredictable and irregular, leading to increased resource consumption and data unavailability when users are forced to upgrade to higher virtual hardware models.
Innovation Solution
A method to monitor and adjust I/O loads in real-time, dynamically increasing or decreasing I/O performance based on predetermined thresholds to handle I/O spikes without interrupting services, thereby preventing system crashes and reducing resource consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the block storage system uses preconfigured predetermined thresholds for I/O load, then the system can maintain stable operation under normal conditions, but the system cannot handle I/O spikes effectively leading to service interruption
Solution Approach 1:
The patent implements dynamic I/O performance adjustment by transitioning from static preconfigured thresholds to real-time monitoring and adjustment mechanisms. The system continuously monitors I/O load metrics and dynamically adjusts performance parameters based on current system conditions, enabling the block storage system to adapt to varying workloads including I/O spikes while maintaining stability during normal operation.
2Reliability
If the system increases I/O performance to handle I/O spikes, then service continuity is maintained, but resource consumption increases significantly
Solution Approach 1:
The system employs dynamic performance adjustment that increases I/O capacity only when and where needed based on real-time load monitoring. This allows the block storage system to maintain service continuity during I/O spikes while avoiding unnecessary resource consumption during normal operation, as performance is scaled dynamically rather than being permanently increased.
Solution Approach 2:
The patent changes performance parameters dynamically based on monitored I/O load conditions. By adjusting parameters such as I/O throughput and operation rates in response to actual system state, the system can handle spikes effectively while minimizing resource usage during periods of lower demand, thus resolving the contradiction between service continuity and resource consumption.
3Loss of energy
If the system uses static I/O performance configuration, then resource consumption is minimized, but the system crashes under heavy I/O loads
Solution Approach 1:
The patent replaces static I/O performance configuration with dynamic adjustment mechanisms that respond to real-time system conditions. The system monitors I/O load metrics and automatically adjusts performance parameters to match actual demand, ensuring system reliability under heavy loads while minimizing resource consumption during normal operation through on-demand performance scaling.
Data Source
AI summary
A method includes monitoring a first input/output (I/O) load set of the block storage system within a first time period and a second I/O load set within a second time period, wherein the block storage system is configured to back up and restore data in a client and has preconfigured predetermined thresholds. The method further includes determining a change of an I/O load of the block storage system based on the first I/O load set and the second I/O load set. The method further includes determining, based on the change of the I/O load, that an I/O load within a third time period reaches a first predetermined threshold. The method further includes adjusting I/O performance of the block storage system based on the I/O load within the third time period in response to determining that the I/O load within the third time period reaches the first predetermined threshold.