Dynamic Service Provider Selection for SaaS Applications
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Solution Overview
Problem
Current methods for selecting network service providers for software-as-a-service (SaaS) applications rely on manual expertise and one-time connectivity measurements, leading to inconsistent user experiences across different applications and service providers, with no guarantee of optimal performance for varying applications.
Innovation Solution
A device generates a predictive model based on application experience metrics to rank and select the best network service provider for SaaS applications, dynamically switching between providers to maximize user experience by forecasting application traffic and performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If manual expertise and one-time connectivity measurements are used to select network service providers, then initial configuration is simple, but application experience consistency across different applications and providers cannot be guaranteed
Solution Approach 1:
The system performs self-configuration by automatically discovering available SaaS applications, measuring connectivity metrics across multiple service providers, and dynamically selecting optimal providers based on real-time performance. This eliminates manual configuration while ensuring consistent application experience through automated, data-driven decision-making.
Solution Approach 2:
The system continuously monitors connectivity metrics (latency, loss, bandwidth) and application experience across different service providers, using this feedback to dynamically adjust routing decisions. This closed-loop feedback mechanism ensures consistent application experience by adapting to changing network conditions and provider performance.
2Device complexity
If a single network service provider is selected for all SaaS applications, then configuration is simplified, but optimal performance cannot be guaranteed for varying applications
Solution Approach 1:
The system implements dynamic service provider selection that adapts to different SaaS applications and changing network conditions. Instead of static configuration, the system continuously measures connectivity metrics and automatically routes each application through the optimal service provider, enabling performance optimization without requiring complex manual configuration for each application.
Solution Approach 2:
The system changes routing parameters (service provider selection) based on application-specific requirements and real-time network conditions. By dynamically adjusting which service provider handles which application traffic based on measured metrics like latency, loss, and bandwidth, the system achieves optimal performance across varying applications without increasing configuration complexity.
3Loss of time
If one-time connectivity measurements are used for service provider selection, then initial setup is quick, but performance adaptation to changing network conditions is lost
Solution Approach 1:
The system maintains continuous connectivity measurements and performance monitoring across all service providers and SaaS applications. Instead of one-time measurements, the system continuously gathers metrics data and uses this ongoing information to dynamically adjust routing decisions, ensuring adaptation to changing network conditions while maintaining quick initial setup through automated processes.
Solution Approach 2:
The system performs preliminary discovery and measurement of all available service providers and SaaS applications automatically during initial setup, establishing a baseline for dynamic selection. This preliminary action captures provider capabilities without manual intervention, then the system continuously adapts based on ongoing measurements, combining quick setup with continuous adaptation.
Data Source
AI summary
In one embodiment, a device receives application experience metrics for a software-as-a-service application. The device generates, based on the application experience metrics, a predictive model that predicts application experience scores for a plurality of network service providers that provide connectivity to the software-as-a-service application. The device selects a particular network service provider for use by a location, based on an application experience score predicted by the predictive model. The device sends an indication of the particular network service provider to the location.