Storage Array Error Filtering and Triage
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Solution Overview
Problem
Conventional storage arrays unnecessarily burden customer service organizations with low-priority error reports, wasting resources and reducing system throughput by automatically establishing transmission links for all errors, including benign ones, which clogs the queue and delays higher priority issues.
Innovation Solution
The storage array filters and triages errors internally, categorizing and responding to errors by either resolving them proactively or collecting data for deeper analysis, thereby preventing unnecessary transmission links and reducing resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the storage array automatically establishes a transmission link to report all errors to the customer service organization, then complete error information is provided for analysis, but low-priority errors clog the queue and waste resources at the customer service center
Solution Approach 1:
The storage array performs preliminary error analysis and categorization before transmitting error information to the customer service organization. The system pre-processes errors by comparing them against a database of known errors and determining priority levels, so that only relevant errors requiring external assistance are transmitted. This preliminary action prevents queue clogging at the customer service center while ensuring complete information is provided for errors that do require external analysis.
2Measurement precision
If the storage array collects and transmits multi-mega-byte error data files to the customer service center, then comprehensive error analysis is enabled, but system throughput is reduced during data collection and transmission
Solution Approach 1:
The storage array extracts only the essential error information needed for analysis rather than collecting and transmitting complete multi-mega-byte data files. The system identifies and transmits only the specific error codes, relevant log entries, and diagnostic data necessary for customer service analysis, leaving out redundant information. This extraction approach maintains error analysis accuracy while dramatically reducing the time and resources required for data collection and transmission.
3Reliability
If all errors are forwarded to the customer service center for analysis, then no errors are missed, but higher priority errors are delayed due to queue congestion from low-priority errors
Solution Approach 1:
The storage array applies different processing qualities to different errors based on their priority and type. Critical errors are immediately transmitted to the customer service center with high priority marking, while low-priority errors are either filtered out or batched for later transmission. This local quality approach ensures that critical errors receive immediate attention without being delayed by lower-priority errors, while still maintaining complete detection of all errors.
4Reliability
If the storage array establishes a transmission link for every error including benign parity errors, then all errors are reported, but resources are wasted analyzing errors that require no action
Solution Approach 1:
The storage array discards benign errors such as single parity errors that do not require external analysis or action. The system identifies these errors through comparison with a database of known benign error patterns and filters them out before transmission to the customer service organization. This discarding approach conserves customer service resources by preventing unnecessary analysis of errors that will not require intervention, while the system recovers by maintaining the error filtering capability for future use.
Data Source
AI summary
The system and method filters out benign errors and triaging errors that are not filtered. The errors that are not filtered are triaged by categorizing the error and in response to the categorized error either resolving the error by executing code to proactively test the error and repair it; or collect the data necessary to perform deeper analysis by the customer service center and forwarding the collected data to the customer service center.