Multi-Tenant Billing Microservices for Scalable Custom Charge Models
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Solution Overview
Problem
Conventional billing systems are not efficiently scalable and lack customization for tenant-specific requirements, failing to accurately calculate billing for subscription-based services and often rely on monolithic applications.
Innovation Solution
A multi-tenant computing system implements a scalable microservice-based extensible billing system that allows tenant users to create custom charge models using self-describing model definition languages, enabling data and logic definitions tailored to their needs, and scales to handle billions of calculations in real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a monolithic billing system is used, then the system structure is simple, but the system is not efficiently scalable and cannot handle high computational loads
Solution Approach 1:
The billing system is divided into multiple independent microservices including a usage microservice for collecting usage data, a rating microservice for calculating charges, and a provisioning microservice for managing service configurations. This segmentation enables each service to be independently scaled and optimized based on its specific computational requirements, resolving the contradiction between productivity and complexity.
2Adaptability or versatility
If a standardized billing system is used, then the system is easy to operate, but it cannot accommodate tenant-specific customization requirements
Solution Approach 1:
The system implements a universal charge model framework that can accommodate multiple billing scenarios including pay-as-you-go, subscription-based, and custom tenant-specific models. The provisioning microservice allows tenants to configure their own charge models using a domain-specific language, enabling customization while maintaining a unified system architecture that simplifies operation.
3Productivity
If computational resources are allocated statically, then resource allocation is simple, but the system cannot dynamically handle varying computational loads
Solution Approach 1:
The system implements dynamic resource allocation where the provisioning microservice can adjust computational resources in real-time based on demand. The microservice architecture allows individual services to be scaled independently, and resources can be dynamically allocated to handle billing calculations, usage event processing, and rating operations according to actual workload requirements.
Data Source
AI summary
Receive, by a price calculation microservice, tenant user input from a particular tenant of a multi-tenant system. Generate, by the price calculation microservice, a particular charge model based on the tenant user input. Detect, by a usage microservice, a usage event associated with a customer of the particular tenant of the multi-tenant system. Receive, by a rating microservice, a rating request, the rating request being received in response to the detecting the usage event. Calculate, by the price calculation microservice in response to the receiving the rating request, a usage charge for the usage event based on the particular charge model. Store, by the rating microservice, the usage charge. Generate an invoice based on the usage charge stored by the rating microservice. Provide the invoice to the customer of the particular tenant of the multi-tenant system.