Dynamic Hybrid Cloud Flow Splitting for Scalability
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Solution Overview
Problem
Existing hybrid cloud environments face challenges in efficiently deploying and optimizing application flows across on-premise and off-premise platforms, requiring advanced preparation and developer/administrator intervention for scalability and performance.
Innovation Solution
A method and system that dynamically splits application flows into sub-flows, redistributes them across multiple servers based on performance characteristics, and optimizes their execution without modifying the flow's behavior, enabling automatic optimization and scalability without requiring developer or administrator involvement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If application flows are deployed in hybrid cloud environments using traditional methods, then deployment is straightforward, but scalability and performance optimization require advanced preparation and developer/administrator intervention
Solution Approach 1:
The system enables self-service automation by implementing self-monitoring components that automatically detect performance bottlenecks and self-adjusting mechanisms that dynamically redistribute flow executions across cloud environments without requiring developer or administrator intervention. The flow engine autonomously optimizes deployment based on real-time performance metrics.
2Productivity
If application flows are statically deployed across hybrid cloud environments, then deployment is simple, but scalability and performance are limited
Solution Approach 1:
The system implements dynamic deployment by continuously monitoring performance metrics and automatically adjusting flow execution distribution across on-premise and off-premise environments. The flow engine adapts to changing conditions in real-time, optimizing resource utilization and execution efficiency without requiring manual reconfiguration.
Solution Approach 2:
The system segments application flows into independent executable units that can be dynamically distributed across multiple flow engines in hybrid cloud environments. This segmentation enables granular control and flexible allocation of flow executions to appropriate environments based on performance requirements and resource availability.
3Adaptability or versatility
If flows are distributed across multiple flow engines, then scalability improves, but coordination and routing complexity increases
Solution Approach 1:
The system introduces a flow engine as an intermediary component that manages the distribution and coordination of flow executions across multiple flow engines in hybrid cloud environments. This intermediary abstracts the complexity of routing and coordination, providing a simplified interface while enabling scalable distribution across on-premise and off-premise platforms.
Data Source
AI summary
A computer-implemented method for deploying an application between an on-premise server and an off-premise server includes identifying a plurality of nodes in a flow of an application deployed on the on-premise server. The computer-implemented method further includes splitting the flow at the plurality of nodes to form a plurality of sub-flows of the application. The computer-implemented method further includes routing a flow execution workload of the application to the plurality of sub-flows of the application.