Multi-Tier Storage Deployment Engine for Adaptive Cost Optimization
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Solution Overview
Problem
Existing multi-tier storage systems face challenges in optimizing cost, performance, and endurance due to static initial media type selection and configuration, which fail to account for changing workloads and device prices over time.
Innovation Solution
A storage management engine determines an optimal deployment configuration for multi-tier storage systems by analyzing available persistent memory devices, their characteristics, and user requirements, providing dynamic recommendations for device selection and configuration adjustments based on runtime information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If static initial media type selection and configuration are used, then device complexity is reduced, but storage acquisition cost and total cost of ownership increase due to inability to optimize for changing workloads and device prices
Solution Approach 1:
The patent implements dynamic media type selection and configuration that automatically adapts to changing workloads and device prices over time, transforming the static storage system into a dynamic one that continuously optimizes cost and performance based on current conditions
Solution Approach 2:
The system incorporates feedback mechanisms that monitor workload patterns and device price changes, using this information to automatically adjust media type selections and configurations, enabling continuous optimization without manual intervention
2Reliability
If dynamic media type selection and reconfiguration are implemented, then storage acquisition cost is optimized, but system complexity and computational requirements increase
Solution Approach 1:
The storage system implements self-service capabilities where the management engine automatically performs media type selection, configuration optimization, and reconfiguration based on monitored workload and price data, eliminating the need for complex manual management while achieving cost optimization
Solution Approach 2:
The system performs preliminary analysis of workload patterns and device characteristics to pre-determine optimal configurations, reducing the computational complexity required for real-time decision-making while maintaining optimization effectiveness
Data Source
AI summary
An embodiment of an electronic apparatus may comprise a processor, memory communicatively coupled to the processor, and circuitry communicatively coupled to the processor and the memory to determine a group of available types of persistent memory devices and a set of characteristics associated with each type of persistent memory device of the group of available types of persistent memory devices, determine of a set of requirements for a storage system, and determine a deployment configuration for the storage system with a lowest storage acquisition cost based on the group of available types of persistent memory devices, the sets of characteristics, and the set of requirements. Other embodiments are disclosed and claimed.