Application Resource Quota Forecasting to Prevent Service Interruptions
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Solution Overview
Problem
Existing computing environments face challenges in managing resource utilization limits, leading to potential interruptions in application access due to exceeded quota limits, and existing methods lack predictability and effective mitigation strategies.
Innovation Solution
A method involving a resource manager that identifies system resources and quota limits, forecasts utilization, determines potential limit exceedance, and either migrates applications to suitable environments or reserves additional quota to prevent exceedance, thereby maintaining seamless operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If quota limits are strictly enforced to prevent resource overconsumption, then resource utilization efficiency is improved, but application service continuity deteriorates when limits are exceeded
Solution Approach 1:
The system performs preliminary forecasting of resource utilization to predict future quota exceedance before it occurs. By identifying potential limit violations in advance, the system can proactively migrate applications or alert users, preventing service interruptions and maintaining continuity while still enforcing quota limits effectively.
2Reliability
If quota limits are increased to accommodate growing application needs, then service continuity is maintained, but resource utilization efficiency deteriorates due to over-provisioning
Solution Approach 1:
The system dynamically adjusts quota limits based on forecasted resource utilization patterns and actual application needs. Rather than statically increasing quotas to prevent any potential exceedance, the system uses forecasting data to make informed, dynamic adjustments that maintain service continuity while avoiding unnecessary over-provisioning and preserving resource utilization efficiency.
3Productivity
If applications are migrated between environments to balance resource usage, then resource allocation efficiency is improved, but system complexity increases due to migration management
Solution Approach 1:
The system implements automated migration management that operates autonomously based on forecasted resource utilization. The migration process is self-managed through automated decision-making algorithms that evaluate forecasting data and execute migrations without requiring complex manual coordination, thereby improving resource allocation efficiency while keeping system complexity manageable.
4Loss of time
If forecasting is performed to predict resource utilization, then proactive resource management is improved, but measurement precision requirements increase
Solution Approach 1:
The forecasting system performs resource utilization prediction at strategic intervals and for critical applications rather than continuously monitoring all resources with maximum precision. This partial forecasting approach provides sufficient proactive management capability for decision-making without requiring excessively precise measurements across the entire system, thus reducing the burden of measurement precision requirements.
Data Source
AI summary
A method for managing resource utilization includes identifying a quota limit of an environment, performing a forecast of system resource utilization for an application running on the environment, making a determination that the forecast of system resource utilization would cause the quota limit to be exceeded, and increasing the quota limit based on the determination.