Logical Storage Pool Provisioning With Real-Time SLA Feedback
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Solution Overview
Problem
Manual configuration of storage devices for provisioning in computing environments leads to inefficient resource allocation, reduced performance, and cumbersome selection efforts, as storage administrators struggle to meet service level agreements due to increases in data and workload.
Innovation Solution
Dynamically provisioning a logical storage pool of storage devices based on real-time performance statistics and service level agreements, automatically selecting and replacing devices to ensure performance metrics are met, reducing manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If manual configuration of storage devices is used, then storage administrators can provision storage based on theoretical data and personal experience, but resource allocation becomes inefficient and performance degrades over time
Solution Approach 1:
The system performs self-provisioning by automatically selecting storage devices based on real-time performance statistics and service level agreements, eliminating the need for manual administrator intervention in the actual storage device selection and configuration process
Solution Approach 2:
The system continuously collects real-time performance statistics from storage devices and uses this feedback to dynamically adjust storage provisioning decisions, replacing static theoretical data with live performance information to optimize resource allocation
2Ease of operation
If manual configuration of storage devices is used, then administrators can control the provisioning process, but the process becomes cumbersome and imprecise
Solution Approach 1:
The storage system autonomously performs provisioning operations including device selection, configuration, and performance monitoring, eliminating the time-consuming manual configuration process while maintaining operational control through automated decision-making
Solution Approach 2:
The system pre-configures storage devices based on predicted performance requirements and service level agreements before actual use, performing setup actions in advance to eliminate time-consuming manual configuration during operation
3Reliability
If storage devices are provisioned manually, then administrators can select devices based on theoretical specifications, but performance degrades as data and workload increase
Solution Approach 1:
The system dynamically adjusts storage provisioning based on real-time performance statistics and changing workload conditions, transitioning from static theoretical specifications to dynamic performance-based allocation that adapts to increasing data and workload
Solution Approach 2:
The system continuously monitors actual storage performance and uses this feedback to adjust provisioning decisions, ensuring performance consistency as data capacity increases by comparing actual performance against service level agreements
4Adaptability or versatility
If manual storage provisioning is used, then administrators can configure storage based on personal experience, but reconfiguration requires taking applications offline and migrating data
Solution Approach 1:
The system autonomously handles reconfiguration by automatically selecting new storage devices and migrating data without requiring administrator intervention or application downtime, performing the reconfiguration process self-service style
Solution Approach 2:
The system pre-prepares new storage devices and establishes migration pathways before actual reconfiguration is needed, enabling seamless transitions that eliminate downtime by having replacement storage ready in advance
Data Source
AI summary
One or more techniques and/or systems are provided for dynamically provisioning logical storage pools of storage devices for applications. For example, a logical storage pool, of one or more storage devices, may be constructed based upon a service level agreement for an application (e.g., an acceptable latency, an expected throughput, etc.). Real-time performance statistics of the logical storage pool may be collected and evaluated against the service level agreement to determine whether a storage device does not satisfy the service level agreement. For example, a latency of a storage device within the logical storage pool may increase overtime as log files and/or other data of the application increase. Accordingly, a new logical storage pool may be automatically and dynamically defined and provisioned for the application to replace the logical storage pool. The new logical storage pool may comprise storage devices expected to satisfy the storage level agreement.


