Storage Tier Migration Using Workload-Aware Data Placement
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Solution Overview
Problem
Conventional information lifecycle management (ILM) schemes are ineffective in managing the distribution of data in clustered filesystems, particularly when data is striped across different storage portions, leading to increased latency and inefficiencies in data access operations.
Innovation Solution
A computer-implemented method that analyzes workload characteristics of data in a clustered filesystem with shared and shared nothing nodes to generate suggestions for data placement and transfer between tiers, utilizing special purpose hardware to enhance data transfer speeds and reduce latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data is striped across different portions of storage in clustered filesystems, then storage capacity and data throughput increase, but conventional ILM schemes become ineffective and data access latency increases
Solution Approach 1:
The system monitors workload characteristics of striped data and uses this feedback to dynamically generate placement suggestions. The ILM policy evaluator continuously assesses data access patterns and adjusts migration decisions based on observed performance, creating a closed-loop control system that adapts to changing workload conditions and optimizes data placement in real-time
Solution Approach 2:
The patent implements dynamic data migration by transitioning from static ILM policies to adaptive ones that respond to changing workload characteristics. Data placement suggestions are generated based on current workload analysis, allowing the system to dynamically adjust which striped data portions should be migrated between storage tiers to optimize performance under varying conditions
2Device complexity
If conventional ILM schemes are used for striped data, then implementation simplicity is maintained, but data distribution management becomes ineffective
Solution Approach 1:
The patent introduces an intermediary layer between the clustered filesystem and underlying storage that generates placement suggestions without requiring fundamental changes to either system. This intermediary analyzes workload characteristics and provides migration recommendations, effectively bridging the gap between simple ILM implementation and sophisticated data distribution management needs
Solution Approach 2:
The system segments the data distribution management function into distinct components: workload characteristic analysis, placement suggestion generation, and migration execution. This segmentation allows conventional ILM schemes to remain simple while adding sophisticated management capabilities through modular components that can be independently implemented and maintained
Data Source
AI summary
A computer-implemented method, according to one embodiment, includes: receiving one or more suggestions which correspond to placement of data in storage. The one or more suggestions are used to identify portions of actual data stored in actual storage which correspond to the one or more suggestions. The first tier is configured to stripe data across the two or more shared nodes. For each of the identified portions of the actual data stored in the first tier, the one or more suggestions is further used to determine whether to transfer the given identified portion of the actual data to the second tier. Moreover, in response to a determination to transfer at least one of the identified portions of the actual data to the second tier, one or more instructions are sent to transfer the at least one of the identified portions of the actual data from the first tier to the second tier.