Real-time Sense Data Querying for Storage Error Handling
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Solution Overview
Problem
Conventional data storage systems lack the ability to associate specific sense data with particular IO requests that triggered errors, leading to inefficient error handling and data retrieval.
Innovation Solution
Implementing real-time sense data querying within the IO stack, where clients buffer context information for IO requests and send targeted queries to drivers, allowing for precise retrieval of sense data specific to error-causing operations before IO completion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If the upper level component sends a general request for sense data to the SAS HBA driver, then the driver provides all available sense data, but the upper level component cannot identify which sense data corresponds to the specific IO request that triggered the error
Solution Approach 1:
The system performs preliminary actions by having the client buffer context information for each IO request before the operation completes. This buffered context (including timestamps, device identifiers, and operation types) is then used to query the driver for specific sense data, ensuring the correct sense data is retrieved without needing to request all available sense data.
Solution Approach 2:
The system implements feedback by having the driver return IO status communications to the client, which then uses this feedback to determine whether to send a sense data query. The client sends targeted queries only when errors are detected, and the driver returns sense data that corresponds specifically to the queried IO operation, creating a closed-loop feedback system.
2Reliability
If the system retrieves all sense data from the driver, then complete sense data is available, but the process is inefficient and time-consuming
Solution Approach 1:
The system extracts only the specific sense data needed for the error condition by having the client send targeted queries to the driver. Instead of retrieving all sense data, the client uses buffered context information to query for sense data corresponding only to the specific IO operation that encountered an error, thereby extracting precisely the information needed without unnecessary overhead.
Solution Approach 2:
The system changes the parameter of sense data retrieval from a general, broad request to a specific, targeted request. By modifying the query parameters to include buffered context information (timestamps, device identifiers, operation types), the system transforms the retrieval process to obtain only the relevant sense data, improving both efficiency and accuracy.
3Reliability
If the system waits for IO completion to retrieve sense data, then all data is available, but real-time error handling is delayed
Solution Approach 1:
The system performs preliminary actions by buffering context information for each IO request as it is issued, rather than waiting for IO completion. This pre-buffered context enables the client to immediately query the driver for sense data when an error is detected, without waiting for the IO operation to complete, thereby reducing error handling time while maintaining accurate error detection.
Data Source
AI summary
A technique is directed to handling a storage device error within storage equipment that includes a client and a driver. The technique involves providing an IO status communication from the driver to the client. The IO status communication indicates status of an IO operation performed by a storage device coupled with the driver. The technique further involves, in response to the IO status communication indicating that an error occurred while the storage device performed the IO operation, providing a query communication from the client to the driver. The query communication requests sense data corresponding to the IO operation. The technique further involves, in response to the query communication, providing the sense data corresponding to the IO operation from the driver to the client.