Application Manifest for Dynamic Resource Provisioning
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Solution Overview
Problem
Complex applications require efficient management of various resources for operation, including databases, web servers, and computing infrastructure, which existing technologies struggle to provision and scale dynamically in response to changing demands.
Innovation Solution
An application manifest is used to define logical resource requirements, which are mapped to physical components, enabling dynamic provisioning and scaling through a Platform as a Service (PaaS) system, including analytics for real-time resource allocation and root cause analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual provisioning and management of application resources is used, then control and customization are improved, but time consumption and operational complexity increase
Solution Approach 1:
The patent implements pre-defined resource templates and deployment packages that contain pre-configured resource allocations. When an application is deployed, the system automatically selects and applies appropriate templates, eliminating the need for manual resource provisioning steps and significantly reducing deployment time.
Solution Approach 2:
The system enables automated self-provisioning of resources through deployment packages that automatically request and allocate required resources. The platform autonomously manages resource allocation, scaling, and deprovisioning based on application requirements, reducing manual operational overhead while maintaining control.
2Adaptability or versatility
If static resource allocation is used, then system simplicity is improved, but adaptability to changing demands deteriorates
Solution Approach 1:
The patent implements dynamic resource allocation where resource assignments are not fixed but can automatically adjust based on application performance metrics and demand. The system continuously monitors resource utilization and automatically scales resources up or down, enabling adaptability while managing complexity through automated control mechanisms.
Solution Approach 2:
The system incorporates continuous monitoring of application performance and resource utilization, using this feedback to automatically adjust resource allocation. This closed-loop control enables the system to adapt to changing demands dynamically while maintaining manageable complexity through rule-based automated responses.
3Reliability
If comprehensive resource monitoring is implemented, then system reliability is improved, but computational overhead increases
Solution Approach 1:
The patent implements selective monitoring that focuses computational resources on critical performance indicators and key resource allocations rather than comprehensive monitoring of all system parameters. This approach maintains system reliability by monitoring essential metrics while reducing unnecessary computational overhead from excessive monitoring.
Data Source
AI summary
Systems and methods are disclosed for provisioning resources for an application according to an application manifest. The resources may include database, network, and processing resources. The application manifest may be organized as a manifest tree with provisioned resources having their own application manifests for provisioning sub-resources. The application manifest may also define provisioning and de-provisioning of the application in response to loading of the application. Root cause analysis may be performed in accordance with the manifest tree. Also disclosed are systems and methods for rolling out an upgrade across a node cluster. Systems and methods are disclosed for routing traffic to different workflow paths in order to implement an overloaded path and evaluate performance of the overloaded path.