End-to-End Throttle Controller for IT Bottleneck Resolution
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Solution Overview
Problem
Current enterprise systems face inefficiencies due to resource bottlenecks during business process execution, leading to degraded system performance and inefficient utilization of system assets, as they lack end-to-end oversight and control across multiple disparate system assets.
Innovation Solution
Implementing a method for IT operational controls that monitors load across multiple system layers, determines necessary throttling adjustments, and sends updates to throttle agents to optimize end-to-end throughput, using existing system assets and making real-time decisions to avoid bottlenecks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If enterprise systems execute business processes with multiple disparate system assets, then system functionality and business process support are improved, but resource bottlenecks and system performance degradation occur
Solution Approach 1:
The system implements continuous monitoring of load conditions across multiple system layers (network, system, application, process, object/entity) and uses this feedback to dynamically adjust throttling policies. The end-to-end throttle controller receives load data from each layer, determines necessary policy adjustments, and sends updated throttling policies to throttle agents, creating a closed-loop feedback mechanism that optimizes system performance while maintaining functionality.
Solution Approach 2:
The throttling policies are made dynamic rather than static, allowing the system to adapt load distribution in real-time based on current conditions. The end-to-end throttle controller continuously evaluates layer load data and adjusts throttling parameters dynamically, enabling the system to respond to changing workloads and prevent bottlenecks before they degrade performance.
2Ease of operation
If traditional throttling approaches control individual system assets independently, then local resource management is simplified, but end-to-end process optimization is lost
Solution Approach 1:
The end-to-end throttle controller serves multiple functions simultaneously: it monitors load conditions across all system layers, determines optimal throttling policies for each layer, and coordinates adjustments across the entire system. This universal controller integrates what were previously separate local control functions, enabling both simplified local management and optimized end-to-end performance through a single coordinated system.
3Reliability
If real-time load monitoring is implemented across multiple layers, then bottleneck detection capability is improved, but system complexity and monitoring overhead increase
Solution Approach 1:
The monitoring system is segmented into distinct components: individual monitoring points at each system layer (network, system, application, process, object/entity levels) that collect local load data, and a central end-to-end throttle controller that aggregates and analyzes this data. This segmentation allows distributed data collection with centralized intelligence, improving detection capability while managing complexity through modular architecture.
Data Source
AI summary
A system and method for controlling business processes through information technology operational controls are disclosed. The method includes: receiving a business process; monitoring a load at each of multiple layers of the system; sending, to an end-to-end throttle controller, for each layer of the multiple layers, layer load data corresponding to the load at the layer, wherein each layer load data contains data related to a single layer; determining whether any adjustments should be made to throttling policies corresponding to the multiple layers based on the multiple layer load data; sending any adjustments that should be made to throttle agents of one or more layers; updating the throttling policies of one or more layers based on the adjustments; and, continuing executing the business process based on the updated throttling policies.