Data Storage Optimizer Capacity Reservation for Migration
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Solution Overview
Problem
Current data migration techniques in computer systems lack efficient methods for optimizing data movement between storage tiers based on activity levels and performance classifications, leading to suboptimal storage utilization and performance.
Innovation Solution
A method involving a data storage optimizer that automates data movement by reserving storage capacity, adjusting capacity limits, and relocating data portions based on activity levels and performance classifications across multiple storage tiers, ensuring efficient data migration and storage optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data migration is performed without automated optimization, then data movement between storage tiers occurs, but storage utilization and performance are suboptimal
Solution Approach 1:
The data storage optimizer automatically monitors data activity levels and performs self-directed data movement between storage tiers without manual intervention. The system autonomously identifies candidate data portions, evaluates their activity characteristics, and executes migration decisions based on predefined performance criteria, enabling the storage system to optimize itself
Solution Approach 2:
The system performs preliminary analysis of data activity levels and migration candidate identification before actual data migration occurs. By pre-evaluating which data portions are suitable for migration based on activity thresholds and storage tier characteristics, the system prepares optimization actions in advance, improving overall migration efficiency
2Reliability
If storage capacity is reserved for data migration, then data migration can proceed, but available storage capacity for other operations is reduced
Solution Approach 1:
The capacity limit for the first storage tier is dynamically adjusted during data migration operations. The data storage optimizer temporarily reduces the capacity limit to reserve space for incoming migrated data, then restores it after migration completes. This dynamic adjustment ensures migration reliability while minimizing impact on available storage capacity for other operations
3Productivity
If data portions are moved based on activity levels, then storage performance is optimized, but additional processing overhead is introduced
Solution Approach 1:
The system uses activity level parameters (such as read/write frequency, access patterns, and temporal characteristics) to determine data migration decisions. By monitoring and evaluating these measurable parameters, the data storage optimizer identifies which data portions should be moved between storage tiers, enabling performance optimization through objective parameter-based criteria
Solution Approach 2:
The data storage optimizer continuously monitors data activity levels and uses this feedback to adjust migration decisions. The system evaluates the effectiveness of previous migration actions and adapts its behavior based on observed performance changes, creating a closed-loop optimization process that improves storage performance over time
Data Source
AI summary
When migrating data, a first message is received at a target data storage system from a source data storage system. The target data storage system includes a data storage optimizer that performs automated data movement optimizations. The first message requests a reservation of a first amount of storage on a first storage tier for performing a data migration to migrate data from the source to the target data storage system. A first capacity limit of the first storage tier is reduced by the first amount thereby representing the reservation of the first amount of storage for performing the data migration. If the first storage tier does not include an amount of available storage of at least the first amount, processing is performed to increase the amount of available storage of the first storage tier.