Maintenance Window Tool for Interconnected System Patching
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Solution Overview
Problem
Current methods for patching systems in complex webs of interconnected systems often destabilize the network, lead to service degradation, and fail to inform administrators about ideal downtime windows, resulting in potential quality of service issues and unawareness of software patch availability.
Innovation Solution
An enterprise-level software tool that determines a 'maintenance window' based on computational resource demands and system activity, disconnects systems during low-demand periods to apply patches without disrupting the network, and dynamically reschedules maintenance to ensure minimal operational impact.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If system administrators manually take systems offline to apply patches, then security is improved, but quality of service degrades and system stability is compromised
Solution Approach 1:
The patent applies preliminary action by proactively identifying optimal maintenance windows before system downtime is required. The system analyzes historical data, current system states, and interdependencies to predict the best time to take systems offline, ensuring patches are applied during periods of minimal impact on quality of service
Solution Approach 2:
The patent implements feedback mechanisms by continuously monitoring system performance, user activity patterns, and operational metrics. This real-time feedback allows the system to dynamically adjust maintenance scheduling, reschedule patch applications if conditions change, and learn from past maintenance outcomes to improve future scheduling decisions
2Productivity
If multiple systems are taken offline simultaneously for patching, then security updates are applied efficiently, but the complex web becomes destabilized
Solution Approach 1:
The patent applies segmentation by dividing the complex web of interconnected systems into smaller groups or clusters based on interdependencies and functional relationships. This allows the maintenance management system to schedule and control offline operations at a granular level, preventing cascading failures and maintaining overall network stability while still achieving efficient batch patching within each segment
3Ease of operation
If system administrators manually search for software patches, then patch application is controlled, but time is lost and administrators may be unaware of available patches
Solution Approach 1:
The patent implements self-service by enabling the maintenance management system to automatically discover, evaluate, and schedule software patches without requiring manual administrator intervention. The system autonomously monitors for available patches, assesses their compatibility and impact, and integrates them into the maintenance scheduling process, freeing administrators from time-consuming manual searches while maintaining controlled patch deployment
4Device complexity
If maintenance windows are fixed and predetermined, then scheduling is simple, but the system cannot adapt to changing operational demands or events
Solution Approach 1:
The patent applies dynamics by transforming fixed, predetermined maintenance windows into flexible, adaptive schedules. The system continuously monitors operational conditions, user activity patterns, and external events, dynamically adjusting maintenance window timing and duration to balance scheduling simplicity with responsiveness to changing demands, allowing rescheduling when critical events are detected
Data Source
AI summary
Systems and methods the improve operation and security of large complex webs of 200,000 to 2,000,000 interconnected systems are provided. Systems and methods may dynamically schedule downtime for target systems within the complex. The schedule downtime may not impact operations stability of the complex web. Based on computational resource constraints, systems and methods may provide dynamic rescheduling of system downtime. Systems and methods may provide dynamic computational capacity management by adding capacity and/or reorganizing systems within the complex web.