Storage Processor Profiling for Faulty Disk Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In dual-channel data storage systems, IO errors are not effectively isolated to identify faulty hardware components, leading to repeated attempts on potentially faulty paths, which decreases performance and can result in downtime due to unaddressed hardware issues.
Innovation Solution
The method involves analyzing IO error statistics and leveraging storage processor and physical data path redundancies to determine whether a storage processor, disk drive, or connection is faulty, and switching operations to a redundant path to prevent service disruption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If error recovery operations are performed to recover IO operations, then IO operations can be recovered, but all IO operations are blocked during recovery and the faulty hardware component is not isolated
Solution Approach 1:
The system segments the storage system into multiple independent paths with separate storage processors and disk drives. When an IO error occurs, the system can isolate the faulty component to a specific path and continue operations on other paths, preventing complete blockage of IO operations while maintaining recovery capability.
Solution Approach 2:
The system changes the state of IO operations from blocked to redirected by detecting error patterns and identifying faulty hardware components. When a faulty component is identified, the system redirects subsequent IO operations to alternative paths, changing the operational parameter from failure to continued service.
2Reliability
If the storage system uses redundant paths and storage processors, then hardware failure tolerance is improved, but the complexity of the system increases
Solution Approach 1:
The system implements self-diagnosis and self-isolation capabilities by automatically detecting IO error patterns, identifying faulty hardware components, and redirecting operations without requiring manual intervention. This self-service approach manages the complexity of redundant architectures automatically, allowing the system to maintain reliability while reducing operational complexity.
Solution Approach 2:
The system continuously monitors IO error statistics and uses this feedback to identify patterns indicating faulty hardware components. By analyzing error rates across different paths and storage processors, the system dynamically adjusts operation routing, managing system complexity through intelligent decision-making based on real-time performance data.
3Reliability
If the system retries IO operations on the same path multiple times, then recovery attempts are made, but application performance decreases due to latency
Solution Approach 1:
The system performs preliminary analysis of error patterns and identification of faulty hardware components before retrying IO operations. By pre-determining the cause of errors and isolating faulty paths, the system avoids unnecessary retry cycles on failing paths, reducing application latency while maintaining reliable recovery attempts on healthy paths.
Data Source
AI summary
One embodiment is related to a method for determining a faulty hardware component within a data storage system, comprising: collecting data relating to a plurality of input/output (IO) errors associated with a first storage processor within the data storage system; compiling IO error statistics based on the data relating to the plurality of IO errors; and determining a faulty hardware component based on the IO error statistics, wherein the determining of the faulty hardware component comprises utilizing a second storage processor of the data storage system independent from the first storage processor.