Cloud Computing System Automates Maintenance Task Dependencies
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Solution Overview
Problem
Manual operations for different maintenance tasks in cloud computing environments, such as software upgrading and topology changing, lead to low efficiency due to the need for separate manual processes for each operation type and the complexity of managing dependencies across multiple virtual machines.
Innovation Solution
A cloud computing system that automatically determines operation tasks and dependencies based on user input, allowing for sequential execution of these tasks to improve maintenance efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual operations are performed separately for different maintenance tasks (software upgrading, topology changing), then each operation can be executed with precise control, but the overall maintenance efficiency is low due to repeated manual processes
Solution Approach 1:
The patent combines multiple separate maintenance operations (software upgrading, topology changing, configuration management) into a single unified automated workflow. The system integrates these distinct operations into one coordinated process that can be triggered by a single user request, eliminating the need to manually execute each operation separately and thereby improving maintenance efficiency while reducing operational complexity.
Solution Approach 2:
The patent creates a universal maintenance operation system that can handle multiple types of maintenance tasks through a single platform. The system is designed to perform diverse functions including software upgrades, topology changes, and configuration management within one unified framework, allowing it to adapt to different maintenance needs without requiring separate manual processes for each task type.
2Reliability
If multiple maintenance operations are performed on multiple virtual machines, then comprehensive maintenance coverage is achieved, but the management complexity increases significantly
Solution Approach 1:
The patent segments the complex maintenance task management into hierarchical components: individual operation tasks for each virtual machine, dependency relationships between tasks, and grouped maintenance workflows. This segmentation allows the system to manage multiple virtual machines by breaking down overall maintenance into manageable atomic operations that can be independently tracked and executed, reducing the perceived complexity while maintaining comprehensive coverage.
Solution Approach 2:
The patent introduces an automated task management system as an intermediary between user requests and actual maintenance operations across multiple virtual machines. This intermediary automatically determines task dependencies, schedules execution order, and coordinates operations across the infrastructure, thereby reducing the management complexity that would otherwise require direct human coordination of numerous individual tasks.
3Productivity
If automated task determination is implemented, then maintenance efficiency is greatly improved, but the system complexity increases
Solution Approach 1:
The patent implements preliminary action by pre-defining operation templates and dependency relationships for common maintenance scenarios. The system prepares maintenance workflows in advance with predetermined task sequences and dependency rules, allowing automated determination to function based on pre-established logic rather than requiring complex real-time decision-making, thereby improving efficiency while controlling system complexity.
Data Source
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AI summary
The present invention provides a business operation method and apparatus, and a cloud computing system. The method includes: receiving an operation target of a business, and determining, based on the operation target of the business and current running data of the business, an operation task that needs to be executed to implement the operation target of the business, where the operation target of the business is used for indicating a target topology and/or target software of the business, and the current running data of the business includes a current topology of the business and currently running software; and if there are a plurality of operation tasks, determining dependencies between the operation tasks, and executing the operation tasks based on the dependencies between the operation tasks. The method implements automatic execution of a business maintenance operation and greatly improves efficiency of the business maintenance operation.