Request Manager Framework for Storage Node Capacity Management
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Solution Overview
Problem
Existing clustered storage systems face challenges in managing concurrent data protection operations, such as backup, recovery, and replication, which can overwhelm storage node capacity due to overlapping time intervals for executing data protection rules, and typical throttling techniques fail to address operation type-specific needs.
Innovation Solution
Implementing a request manager framework with capacity manager plugins and sequencing request repositories to manage storage node operations based on operation types, allowing for type-specific throttling, limiting, and prioritization, ensuring that storage node capacity is utilized efficiently by postponing non-essential operations when capacity is not available.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If typical throttling or limiting techniques are employed to manage storage node capacity, then storage node capacity overload is prevented, but operation type-specific data protection needs cannot be satisfied
Solution Approach 1:
The patent segments the generic throttling mechanism into operation-type-specific capacity managers, where each capacity manager (backup capacity manager, replication capacity manager, migration capacity manager) handles specific operation types with dedicated rules and parameters. This segmentation allows each operation type to have customized throttling behavior while maintaining overall system capacity control.
Solution Approach 2:
The patent implements dynamic capacity management by allowing capacity rules to be defined and adjusted for different operation types. The system dynamically selects and applies appropriate capacity rules based on the incoming operation type, enabling flexible adaptation to varying data protection requirements without sacrificing capacity control.
2Productivity
If multiple data protection operations are executed concurrently to meet RPOs, then data protection coverage is improved, but storage node capacity is overwhelmed
Solution Approach 1:
The patent implements feedback mechanisms where capacity managers continuously monitor storage node capacity utilization and adjust operation execution accordingly. When capacity thresholds are approached, the system provides feedback to postpone or reject new operations, ensuring capacity limits are maintained while still maximizing data protection coverage within available resources.
Solution Approach 2:
The system employs periodic capacity checks and operation scheduling, where capacity is evaluated at defined intervals and operations are executed in periodic batches rather than continuously. This periodic action allows the system to meet RPO requirements through regular operations while preventing capacity overload by spacing out execution timing.
3Ease of operation
If a generic priority schema is used for throttling operations, then simple capacity management is maintained, but operation type-specific prioritization requirements are not met
Solution Approach 1:
The patent applies local quality by implementing different priority schemas and capacity rules tailored to each operation type. Instead of a uniform approach, each capacity manager can define local prioritization strategies appropriate to its operation type (e.g., backup operations may have different priorities than replication operations), allowing customized quality of service while maintaining manageable complexity through modular design.
Data Source
AI summary
Techniques for managing sequencing requests for storage node operations based on types of operations being sequenced. The techniques manage sequencing requests for different types of operations, such as backup and recovery operations, replication operations, migration operations, and so on, in a manner that avoids overwhelming storage node capacity. The techniques include receiving a sequencing request for an operation of a specified operation type at a request manager of a storage node and determining whether a capacity of the storage node is available for running the operation by a capacity manager for the specified operation type, in which the capacity manager is provided by a storage client and implemented on the storage node separate from the request manager. In this way, throttling, limiting, and/or prioritization requirements of the operation of the specified operation type can be defined by the storage client in a manner agnostic to the request manager.