Modular Pricing Pipeline Resource Allocation
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Solution Overview
Problem
Existing pricing platforms face challenges in optimizing resource allocation for diverse customer needs, leading to overhead delays in microservices communication, as they struggle to create a single monolithic system tailored to each customer's specific processing requirements.
Innovation Solution
A system and method that creates an instance of the pricing pipeline for each customer with modular stages executed within the same process boundary, allowing for independent configuration of computational resources and generation of performance metrics to optimize resource allocation and reduce communication delays.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a single monolithic pricing system is built to serve all customers, then system simplicity is maintained, but the system cannot be optimized for each customer's specific processing requirements
Solution Approach 1:
The pricing system is divided into multiple independent pricing pipelines, with each pipeline dedicated to a specific customer. Each pipeline contains modular pricing stages that can be independently configured and optimized for that customer's specific requirements, allowing customization without affecting other customers' systems.
Solution Approach 2:
The system allows dynamic configuration of computational resources allocated to each modular pricing stage within a pipeline. Administrators can adjust resource allocation based on performance metrics and changing customer needs, enabling the system to adapt to different processing requirements while maintaining overall system simplicity.
2Adaptability or versatility
If modular services are used to customize pricing for different customers, then adaptability to customer needs is improved, but overhead delays occur between microservices communication
Solution Approach 1:
Multiple modular pricing stages within a single customer's pipeline are merged to execute within the same process boundary. This eliminates inter-service communication overhead by allowing stages to call each other directly within the same process, while still maintaining modularity for independent configuration and optimization.
3Productivity
If computational resources are allocated uniformly across all pricing stages, then system simplicity is maintained, but pricing calculations cannot be optimized for each customer's specific needs
Solution Approach 1:
Each modular pricing stage can be independently configured with specific computational resource allocations tailored to its individual requirements and the customer's pricing calculation needs. This allows optimization of resource distribution across different stages without requiring complex centralized control, as each stage can be adjusted locally based on performance metrics.
Data Source
AI summary
The present disclosure relates to a system, method, and computer program for providing a pricing platform for performing pricing calculations for a plurality of different customers with different types of pricing calculations. An instance of the price-calculation pipeline is created for each of a plurality of customers of the pricing platform. The instances of the price-calculation pipeline are executed to perform pricing calculations for a plurality of different customers with different types of pricing calculations. For each instance of the price-calculation pipeline, a performance metric is generated for each of the modular pricing stages within the instance. The performance metrics are displayed in a user dashboard that provides user controls that enable the user to adjust the computational resources allocated to each of the modular pricing stages executing on the platform. The computational resources allocated to one or more modular pricing stages are adjusted in accordance with received user input.