Pay-per-use metering service for cloud EDA license scaling
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Solution Overview
Problem
Current licensing approaches for electronic design automation (EDA) applications in cloud environments are constrained by a fixed number of licenses, limiting the ability to dynamically scale workloads on-demand.
Innovation Solution
Implementing a pay-per-use (PPU) metering service for EDA workloads in the cloud, which allows for dynamic scaling by routing check-out and check-in requests through a load balancer to a pool of license servers, and dynamically increasing the number of license servers as needed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a fixed number of licenses is used for EDA applications in cloud environments, then the licensing system is simple to manage, but the ability to dynamically scale workloads on-demand is limited
Solution Approach 1:
The licensing system is segmented into multiple independent license servers that can be dynamically added or removed. Each license server operates independently and can be scaled horizontally to meet workload demands, allowing the system to adapt to changing requirements without redesigning the entire licensing architecture.
Solution Approach 2:
The licensing system transitions from a static fixed-license model to a dynamic pay-per-use model where licenses can be obtained on-demand. The system dynamically adjusts the number of available licenses based on workload requirements, enabling flexible scaling while maintaining manageable complexity through automated license allocation.
2Productivity
If multiple applications request licenses simultaneously, then the system can handle high workload demand, but the license server may become a bottleneck
Solution Approach 1:
The license server is divided into multiple independent instances that can process license requests in parallel. This segmentation eliminates the single-point bottleneck by distributing the license management workload across multiple servers, thereby maintaining high availability and performance even under heavy concurrent demand.
Solution Approach 2:
A load balancer is introduced as an intermediary component that distributes incoming license requests across multiple license servers. This mediator ensures balanced workload distribution, prevents any single server from becoming overwhelmed, and maintains system reliability while handling high productivity demands.
3Measurement precision
If usage tracking is implemented for pay-per-use metering, then billing accuracy is improved, but system complexity increases
Solution Approach 1:
The license servers and applications automatically track and report usage information without requiring manual intervention. The system self-monitors license check-out and check-in events, automatically calculating usage amounts and generating billing data, thereby achieving precise measurement while minimizing operational complexity.
Solution Approach 2:
The metering system implements automated feedback loops where usage information is continuously collected, processed, and used to generate billing reports. This feedback mechanism ensures accurate usage tracking by systematically recording license events and automatically computing charges based on actual consumption patterns.
Data Source
AI summary
A check-out request for a license may be received from an application, e.g., an electronic design automation (EDA) application, and may be routed to a license server. The license may be granted to the application, where granting the license to the application may include establishing a connection between the license server and the application. A check-in request may be received for the license from the application. The license may be revoked, which may include terminating the connection between the license server and the application. A usage amount may be determined based on information about the check-out request and information about the check-in request.