Dynamic Workflow Throttling via API Response Headers
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Solution Overview
Problem
In cloud computing environments, especially in iPaaS platforms, external systems throttle incoming requests to prevent over-utilization, leading to incomplete or inconsistent automated business workflows and potential penalties, such as blocking the source application, which can cause invocation failures.
Innovation Solution
The integration cloud platform enforces fixed limits for workflows and dynamically adjusts these limits based on responses from target applications, using documented headers in their responses to control the execution of integration flows and prevent over-utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If external systems enforce fixed API limits to prevent over-utilization, then system stability is improved, but workflow completion rate deteriorates due to throttling of incoming requests
Solution Approach 1:
The patent implements dynamic throttling limits that adjust based on external system responses. The integration cloud service monitors response messages from target applications and dynamically modifies execution parameters for integration flows, transitioning from fixed static limits to adaptive dynamic limits that prevent over-utilization while maintaining workflow completion.
Solution Approach 2:
The system employs feedback mechanisms by monitoring response messages from target applications and using this information to adjust throttling limits. The integration cloud service reads response codes and headers, updates execution parameters accordingly, and applies these adjusted parameters to subsequent workflow executions, creating a closed-loop control system.
2Loss of energy
If external systems impose strict throttling limits, then resource over-utilization is prevented, but workflow consistency deteriorates due to incomplete or failed automated business workflows
Solution Approach 1:
The system performs preliminary actions by setting initial throttling limits before workflow execution and proactively adjusting these limits based on external system responses. By updating execution parameters in advance based on monitored responses, the system prevents workflow failures before they occur rather than reacting after failures happen.
Solution Approach 2:
The patent changes execution parameters dynamically by reading response codes and headers from target applications and modifying throttling limits accordingly. The system updates parameters such as rate limits, retry counts, and execution timing based on external system feedback, allowing adaptive parameter adjustment to maintain both resource protection and workflow reliability.
3Quantity of substance
If fixed throttling limits are enforced on integration flows, then API fair usage is ensured, but adaptability to external system capabilities deteriorates
Solution Approach 1:
The integration cloud service performs self-service by automatically monitoring external system responses and adjusting its own throttling limits without manual intervention. The system reads response messages, determines appropriate parameter adjustments, and applies these changes autonomously, enabling the platform to adapt to external system capabilities while maintaining fair API usage control.
Data Source
AI summary
Embodiments described herein are generally related to cloud computing environments, and are particularly directed to systems and methods for dynamic throttling of workflows based on integrated applications. An integration cloud or platform-as-a-service (iPaaS) platform can enforce fixed limits for flows, and evolve the limits behavior based on responses from target applications, for example as sent within documented headers in their responses.