Multi-tenant Cloud Metering via Segmented Microservices
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Metering for multi-tenant, microservice architecture-based integration services in cloud computing environments is complex, error-prone, and often manual, especially when dealing with a large number of users, tenants, and microservices, requiring an automated and efficient solution.
Innovation Solution
Implementing an independent usage measurement component that periodically calculates measurable meter units, such as static analysis of integration artifacts and message bandwidth, and a central cloud performance metering service that generates billing data based on these calculations, ensuring secure, automatic, and efficient metering.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual metering process is used, then simplicity of implementation is maintained, but accuracy and reliability of billing data deteriorates due to errors
Solution Approach 1:
The metering system is segmented into independent microservices (usage measurement component, central cloud performance metering service, billing service) that can be developed, deployed, and scaled independently. This segmentation improves reliability through fault isolation while managing complexity through modular architecture.
Solution Approach 2:
The usage measurement component automatically collects, calculates, and reports metering data without manual intervention. The system performs self-service metering operations, eliminating manual errors while maintaining consistent and accurate billing data through automated processes.
2Productivity
If automated metering process is implemented, then billing accuracy is improved, but system complexity increases
Solution Approach 1:
The central cloud performance metering service acts as a universal coordinator that handles multiple metering operations for different tenants and microservices through a single service layer. This multi-functionality approach improves processing efficiency while managing architectural complexity through consolidation.
Solution Approach 2:
The central cloud performance metering service serves as an intermediary between the usage measurement components and the billing service. This mediator pattern simplifies the overall architecture by providing a standardized interface for data exchange, reducing direct complexity between components while maintaining high processing efficiency.
3Adaptability or versatility
If multi-tenant metering is implemented, then service versatility is improved, but measurement precision deteriorates due to resource sharing challenges
Solution Approach 1:
Each usage measurement component is configured with tenant-specific metrics and parameters tailored to individual tenant requirements. This local quality approach enables precise metering for each tenant while maintaining the ability to serve multiple tenants through the same infrastructure, thus improving both versatility and measurement precision.
Data Source
AI summary
According to some embodiments, methods and systems may be associated with a cloud computing environment having a plurality of integration tenants. An independent usage measurement component (e.g., a microservice or module) may periodically calculate measurable meter units for a particular integration tenant of the cloud computing environment. Examples of measurable meter units include a static analysis of integration artifacts, outbound calls from components, message bandwidth, a number of messages, a static count of integration content connections, etc. A central cloud performance metering service may receive the calculated measurable meter units from the independent usage measurement component and arrange for billing data to be generated based on the calculated measurable meter units in connection with creation of a plurality of components resulting in implementation of an integration service for the particular integration tenant.