Server Resource Orchestration via Priority Dispatching
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Solution Overview
Problem
Current application server environments face inefficiencies in resource allocation and management, particularly during peak usage times, leading to resource shortages, lack of responsiveness, and suboptimal use of resources due to the lack of application-level priority awareness in traditional systems.
Innovation Solution
A centralized orchestration layer is introduced to dynamically manage and balance resources across applications based on their priority levels, using algorithms such as suspend-resume, fixed-sharing, and dynamic-sharing strategies to allocate resources efficiently and ensure higher priority applications receive necessary resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional resource allocation methods are used in application server environments, then system simplicity is maintained, but resource allocation efficiency deteriorates during peak usage times
Solution Approach 1:
A centralized orchestration layer is introduced as an intermediary between applications and application servers. This orchestration layer receives application requests, determines priority levels, and dynamically allocates server resources accordingly. The mediator resolves the contradiction by implementing sophisticated resource allocation algorithms without requiring changes to individual applications or servers, thus improving productivity while managing complexity through centralized control.
2Reliability
If equal resource allocation is provided to all applications, then system fairness is maintained, but responsiveness to high-priority applications deteriorates
Solution Approach 1:
The system implements local quality by allocating different resource priorities to different applications based on their specific needs and importance. The orchestration layer assigns priority levels to individual applications or tasks, allowing critical applications to receive preferential resource allocation while less critical applications receive standard allocation. This resolves the contradiction by maintaining fairness at the system level while providing differentiated responsiveness at the application level.
3Productivity
If more server resources are allocated to handle peak demand, then system capacity increases, but resource utilization efficiency during low-demand periods deteriorates
Solution Approach 1:
The system implements dynamic resource allocation where the orchestration layer continuously monitors application priorities and adjusts server resource allocation in real-time. During peak demand periods, more resources are dynamically assigned to high-priority applications; during low-demand periods, resources are released or reallocated. This dynamic approach resolves the contradiction by maintaining high system capacity when needed while optimizing resource utilization efficiency during off-peak times, eliminating the need for permanently over-provisioned resources.
Data Source
AI summary
The present disclosure involves systems, software, and computer implemented methods for resource allocation and management. One example method includes receiving a request to run a first task for a first application, the request including a first application priority. At least one second application priority of at least one currently running application is identified. A dispatching algorithm is executed, to dispatch the first task to a first application server based on the first application priority and the at least one second application priority. Destination information is returned, in response to the request, for the first application server, for execution of the first task for the first application, at the first application server, using the first resources.