Cloud Resource Decommissioning Using Dependency Graph Parallelism
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Decommissioning computing resources, particularly in cloud environments, is challenging due to complex dependencies between resources, which can lead to incomplete deletion and continued charges from cloud providers.
Innovation Solution
A method involving the creation of a directed acyclic graph to identify and transform resource dependencies, collapsing parallel paths into single nodes, and generating a work list for parallel execution of deletion tasks, allowing for efficient and complete decommissioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional sequential deletion methods are used to decommission computing resources, then dependency management is simpler, but decommissioning time and productivity are reduced
Solution Approach 1:
The patent segments the decommissioning process into distinct phases: resource identification, dependency graph construction, parallel path identification, and task generation. By dividing the complex decommissioning workflow into manageable segments, the system can process multiple resource paths simultaneously while maintaining proper dependency management, thereby increasing productivity without overwhelming complexity
Solution Approach 2:
The patent introduces a graphical dimension to represent resource dependencies, transforming the linear sequential process into a multi-dimensional dependency graph structure. This visual representation allows the system to identify parallel paths and execute multiple deletion operations concurrently, effectively adding a temporal parallelism dimension to the decommissioning process
2Productivity
If parallel processing is implemented to speed up decommissioning, then productivity increases, but the risk of incomplete deletion and harmful factors increases
Solution Approach 1:
The patent performs preliminary actions by constructing a complete dependency graph before executing any deletions. The system identifies all parallel paths and generates a comprehensive task list that ensures every resource is accounted for and properly ordered for deletion. This preliminary planning phase guarantees that parallel execution will be both fast and complete, eliminating the reliability risks associated with ad-hoc parallel processing
3Reliability
If comprehensive resource identification is performed to ensure complete deletion, then reliability improves, but time consumption and complexity increase
Solution Approach 1:
The patent balances the thoroughness of resource identification against time consumption by using an efficient graph-based approach. The dependency graph structure allows the system to comprehensively identify all resources and their relationships in a systematic manner, while the parallel path identification algorithm counterweights the time cost by enabling simultaneous processing of multiple deletion tasks, ensuring complete deletion without excessive time loss
Data Source
AI summary
Systems and methods and computer program products support decommissioning resources in a computing system. For instance, a computing system may include a virtual private cloud or other computing system having a multitude of individual resources. A software program may identify the different individual resources, create a first graph based on the individual resources, transform the first graph to reduce a number of nodes in the graph, thereby generating a transformed graph. The software program may further create a work list based on the transformed graph and may perform decommissioning by taking tasks from the work list in parallel.