Automated Instance Management via Classification Metrics
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Solution Overview
Problem
Current cloud computing systems face inefficiencies in managing application instances, leading to suboptimal resource allocation, high human resource utilization, and poor compliance with operational expectations due to the lack of automated and efficient instance management.
Innovation Solution
The implementation of a classification-based automated instance management system that automatically commissions, monitors, and decommissions application instances using a processor configured to execute instructions based on classification metrics, thereby optimizing resource allocation and reducing human intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated instance management is implemented, then productivity is improved, but device complexity increases
Solution Approach 1:
The system segments instance management into distinct automated phases: commissioning, monitoring, and decommissioning. Each phase is handled by specific automated rules and policies, dividing the complex management task into manageable, independent components that can be executed automatically without human intervention.
Solution Approach 2:
The instance management system performs self-service through automated decision-making algorithms that evaluate instance status, classification metrics, and policies to automatically commission, monitor, and decommission instances without requiring human operators. The system serves itself by making management decisions based on predefined rules and real-time data.
2Productivity
If classification-based automation is used, then human resource utilization is reduced, but measurement precision requirements increase
Solution Approach 1:
The system uses classification metrics as key parameters to automatically determine instance management actions. By changing the parameter set from manual assessment to structured classification metrics (such as instance type, workload, resource usage), the system enables automated decision-making with high precision, reducing reliance on human judgment while improving consistency and accuracy.
3Loss of time
If automated monitoring and decommissioning is implemented, then loss of time is reduced, but device complexity increases
Solution Approach 1:
The system performs preliminary actions by pre-defining commissioning, monitoring, and decommissioning policies before instances are created or managed. Classification rules and management policies are established in advance, allowing the system to automatically execute the appropriate sequence of actions based on instance classification, reducing the time required for manual decision-making and execution.
Data Source
AI summary
Systems, apparatuses, and methods for classification based automated instance management are disclosed. Classification based automated instance management may include automatically commissioning an application instance based on a plurality of classification metrics, and automatically monitoring the application instance based on the plurality of classification metrics. Automatically monitoring the application instance may include identifying a plurality of instance monitoring policies associated with the application instance based on the plurality of classification metrics. Automatically monitoring the application instance may include automatically suspending the application instance plurality of instance monitoring policies and automatically decommissioning the application based on the plurality of instance monitoring policies.