Resource Dependency Manager for Software-Defined Data Centers
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Solution Overview
Problem
In software-defined data centers, resource deployments often fail due to undetermined resource dependencies, leading to errors and inconsistencies, as prior techniques lack effective dependency management, making it difficult for users to ensure correct deployment order, especially with complex and dynamic resource configurations.
Innovation Solution
A resource dependency manager is introduced to analyze resource requests, generate dependency graphs, and determine a feasible deployment order, verifying the order in real-time and adjusting deployment timing or updating the dependency graph to ensure resource dependencies are satisfied, thereby preventing errors and ensuring successful deployments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If resource deployment is performed without dependency management, then deployment speed is improved, but deployment reliability deteriorates due to undetermined resource dependencies causing errors and inconsistencies
Solution Approach 1:
The system performs preliminary analysis of resource requests to generate dependency graphs before deployment execution. This preliminary action identifies all resource dependencies in advance, allowing the system to determine a feasible deployment order that satisfies all dependencies, thereby ensuring deployment reliability without sacrificing speed
Solution Approach 2:
A resource dependency manager is introduced as an intermediary component between the deployment system and resource-based services. This intermediary automatically analyzes dependencies, generates dependency graphs, determines deployment orders, and verifies timing constraints, eliminating the need for manual dependency management while ensuring reliable deployments
2Manufacturing precision
If manual dependency management is implemented, then deployment accuracy is improved, but device complexity increases due to the need for manual intervention and tracking
Solution Approach 1:
The resource dependency manager implements self-service by automatically analyzing resource requests, generating dependency graphs, determining deployment orders, and verifying timing constraints without requiring manual intervention. The system manages its own dependency tracking and deployment coordination, achieving high deployment accuracy while maintaining low system complexity
Solution Approach 2:
The resource dependency manager serves as an intermediary that automates the entire dependency management process. It receives resource requests, performs automated dependency analysis, generates deployment orders, and coordinates with resource-based services, thereby achieving deployment accuracy equivalent to manual management without the complexity of human intervention
3Reliability
If real-time verification of deployment order is performed, then deployment reliability is improved, but processing time increases due to continuous monitoring and adjustment
Solution Approach 1:
The system performs preliminary determination of a feasible deployment order that satisfies all resource dependencies before deployment execution. This preliminary action includes generating the dependency graph and calculating the optimal deployment sequence in advance, allowing real-time verification to proceed efficiently by simply checking against the pre-determined order rather than performing continuous complex analysis
Solution Approach 2:
The resource dependency manager implements dynamic verification by monitoring deployment progress in real-time and adjusting the deployment process based on actual resource availability and dependency satisfaction. The system can dynamically pause deployments, adjust timing, or update the dependency graph as resources are provisioned, ensuring reliability while minimizing processing time through adaptive control
Data Source
AI summary
An example apparatus includes a dependency graph generator to generate a dependency graph based on a resource request file specifying a first resource and a second resource to deploy to a resource-based service, the dependency graph representative of the first resource being dependent on a second resource, a verification controller to generate a status indicator after a determination that a time-based ordering of a first request relative to a second request satisfies the dependency graph, and a resource controller to cause transmission of the first request and the second request to the resource-based service based on the dependency graph, and, after determining that the time-based ordering of the first request relative to the second request satisfies the dependency graph, cause transmission of the status indicator to a user device.