Development Pipeline Resource Allocation Using Usage Prediction
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Solution Overview
Problem
Existing development systems face delays and resource inefficiencies due to inadequate allocation and reservation of computing resources across different stages of the development pipeline, leading to wasted resources and prolonged development cycles.
Innovation Solution
A resource component analyzes historical usage data to predict and estimate resource requirements for subsequent stages, allowing for proactive allocation and reservation of computing resources, thereby reducing delays and optimizing resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If computing resources are allocated when the stage is reached, then resource allocation simplicity is maintained, but development pipeline delays occur
Solution Approach 1:
The system performs preliminary resource allocation and reservation before the development pipeline stage is reached. The resource component analyzes historical usage data and predicts future resource requirements, allocating resources in advance to prevent pipeline delays while maintaining efficient resource utilization.
2Productivity
If computing resources are allocated in advance, then pipeline delays are reduced, but resource waste increases
Solution Approach 1:
The system dynamically adjusts resource allocation based on predicted usage patterns. The resource component continuously monitors historical data, updates predictions, and modifies resource reservations accordingly, ensuring resources are allocated in advance when needed while releasing or reducing reservations when not required, thus preventing both delays and waste.
Solution Approach 2:
The system implements feedback mechanisms where the resource component analyzes actual resource usage against predictions, continuously improving future predictions. This feedback loop ensures that advance resource allocation is optimized based on real performance data, reducing both pipeline delays and resource waste over time.
3Device complexity
If resource allocation is done manually, then system complexity is reduced, but resource management efficiency decreases
Solution Approach 1:
The system implements self-service resource management where the resource component automatically performs resource allocation, monitoring, and optimization without manual intervention. The system uses historical data to autonomously predict and allocate resources, reducing the need for complex manual management processes while significantly improving resource management efficiency.
Data Source
AI summary
Managing resources used during a development pipeline. A method of the disclosure includes analyzing historical resource usage of an application development system during different stages of a development pipeline for an application. The application development system includes a set of computing resources. The method also includes configuring the set of computing resources of the application development system for a later stage of the development pipeline based on an estimated resource usage.


