Storage Data Protection via Supplemental Clean List
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Solution Overview
Problem
In object storage systems, when multiple storage failures occur within a short time period, it is possible for all storage targets in an acting set to become unavailable, leading to data loss due to inadequate data protection.
Innovation Solution
A method and system for managing data storage in a data grouping by generating a data storage configuration that includes a first configuration identifying currently allocated storage resources and a second configuration identifying previously allocated storage resources. Eligible storage resources are tracked and updated to maintain a higher data protection level, using a supplemental clean list to ensure data durability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional data protection strategies are used in object storage systems, then the system operates with standard data redundancy, but when multiple storage failures occur within a short time period, all storage targets in an acting set may become unavailable resulting in data loss
Solution Approach 1:
The patent maintains a supplemental clean list that tracks storage targets which were clean at some point in the past but are no longer in the current acting set. This preliminary tracking mechanism is established before failures occur, enabling the system to quickly identify valid storage targets when multiple failures happen simultaneously, thereby improving data protection without requiring complex real-time analysis during failure events.
Solution Approach 2:
The supplemental clean list acts as an intermediary data structure that bridges the gap between the current acting set and historical clean states. This intermediary mechanism allows the system to recover data by referencing previously clean targets without needing to maintain complex real-time state information about all possible failure scenarios, thus improving reliability while managing complexity.
2Reliability
If storage targets are frequently reassigned to new acting sets during multiple failures, then data availability is maintained, but the amount of rebalancing processing increases significantly
Solution Approach 1:
The supplemental clean list is pre-populated with storage targets that have been clean at some point in the past. When failures occur, the system can immediately query this pre-prepared list to identify valid targets for data recovery, avoiding the need to perform extensive rebalancing calculations during the failure event itself. This preliminary preparation significantly reduces the time loss associated with rebalancing operations.
Solution Approach 2:
The system changes the parameter of data recovery by shifting from a dynamic real-time rebalancing approach to a static lookup approach using the supplemental clean list. This parameter change transforms the recovery process from one that requires extensive computation and time to one that can be performed quickly by referencing pre-stored information, thereby reducing rebalancing processing time while maintaining data availability.
3Reliability
If all storage targets in an acting set are reassigned during multiple failures, then data protection is maintained, but the complexity of tracking and managing storage configurations increases
Solution Approach 1:
The patent extracts the historical clean state information from the complex dynamic configuration management and places it into a separate, simplified supplemental clean list. This extraction separates the essential recovery information from the overall configuration complexity, allowing the system to maintain data protection through a simpler, more manageable data structure that can be easily tracked and updated.
Solution Approach 2:
The supplemental clean list serves as an intermediary that simplifies configuration tracking by maintaining only the essential information needed for recovery (previously clean targets) without requiring the system to track and manage the full complexity of all possible configuration states. This intermediary structure reduces configuration tracking complexity while preserving data protection capabilities.
Data Source
AI summary
A method for managing data storage in a data grouping includes generating a data storage configuration specifying the data grouping comprising a first configuration identifying a set of storage resources presently allocated to the data grouping, and a second configuration identifying a set of storage resources previously allocated to the data grouping; storing, in a tracking list, one or more identifiers of storage resources in the first configuration that are eligible to transition to the second configuration; and performing one or more update operations on the first configuration using the tracking list.