Policy-Based Storage Management for Proactive Resource Control
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Solution Overview
Problem
Current system management techniques lack a flexible and efficient mechanism for proactive management of data storage systems, particularly in handling key performance indicators, time-based criteria, and events, which can lead to suboptimal resource utilization and service quality issues.
Innovation Solution
A policy-based management system that receives and defines policies with criteria and actions, allowing for automatic processing based on key performance indicators, time-based criteria, and event-based conditions, enabling actions such as storage capacity expansion, notifications, and data management tasks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional system management techniques are used for data storage systems, then basic I/O operations can be performed, but the system lacks flexible and efficient proactive management mechanisms for key performance indicators, time-based criteria, and events, leading to suboptimal resource utilization and service quality issues
Solution Approach 1:
The system implements dynamic policy-based management where management actions are automatically adjusted based on real-time evaluation of criteria such as key performance indicators, time-based conditions, and events. Policies are evaluated continuously and actions are triggered dynamically when conditions are met, enabling the system to adapt to changing storage system states and optimize resource utilization proactively
Solution Approach 2:
The system changes management parameters by introducing configurable policy criteria including key performance indicator thresholds, time-based conditions, and event triggers. These parameter changes enable flexible definition of management conditions and automatic triggering of appropriate actions based on evaluated criteria, transforming static management into adaptive, condition-driven management
2Reliability
If manual management approaches are used for storage systems, then simple operations can be performed, but proactive response to performance issues and events is delayed, resulting in suboptimal service quality
Solution Approach 1:
The system performs preliminary actions by proactively evaluating multiple criteria (key performance indicators, time-based conditions, events) before problems occur. Policies are configured in advance with defined criteria and actions, enabling the system to detect and respond to conditions proactively rather than reactively, improving service quality and reducing response time
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring key performance indicators, events, and time-based conditions, evaluating them against defined policy criteria, and automatically triggering actions when conditions are met. This closed-loop feedback enables proactive response to performance issues and maintains optimal service quality
Data Source
AI summary
Described are techniques for performing system management. A first policy definition of a first policy is received. The first policy definition includes information identifying a first criterion, a first resource of the system, and a first action to be taken. It is determined whether a condition of the first policy is met. The condition includes the first criterion. Responsive to determining that the condition is met, first processing is performed that includes performing the first action.