Integration Flow Load Distribution Across Worker Sets
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Solution Overview
Problem
Current systems face challenges in efficiently managing load distribution for integration flows, leading to issues such as overloading and resource sharing problems due to the physical limitations of worker sets, which can result in out-of-memory exceptions and sub-optimal resource utilization.
Innovation Solution
The implementation of a computer-implemented method that deploys integration flows across multiple worker sets based on complexity metrics, using autoscaling and redistribution algorithms to balance load, identify and move flows to new worker sets, and manage resource allocation dynamically to prevent overloading and optimize resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If integration flows are deployed to a single worker set, then device complexity is reduced and ease of operation is improved, but load balancing deteriorates and reliability worsens due to overloading and out-of-memory exceptions
Solution Approach 1:
The patent segments integration flows into different groups and distributes them across multiple worker sets based on complexity metrics. This segmentation prevents any single worker set from becoming overloaded, thereby maintaining system reliability while preserving operational simplicity through automated distribution mechanisms.
Solution Approach 2:
The patent implements dynamic load balancing by continuously monitoring worker set performance and automatically redistributing flows in real-time. This dynamic adjustment ensures that flows are always distributed optimally across available worker sets, preventing overloading and maintaining high reliability without requiring manual intervention.
2Reliability
If integration flows are distributed across multiple worker sets, then load balancing is improved and reliability increases, but device complexity increases and resource sharing problems worsen
Solution Approach 1:
The patent enables worker sets to self-manage their own flow assignments by implementing autonomous load balancing algorithms. Each worker set can independently evaluate its own capacity and request additional flows or shed excess loads, eliminating the need for complex centralized management while maintaining reliable distribution across multiple worker sets.
Solution Approach 2:
The patent changes the operational parameters of worker sets by introducing complexity metrics and dynamic threshold adjustments. By monitoring parameters such as memory usage, CPU load, and flow execution time, the system automatically adjusts distribution parameters to maintain optimal reliability without requiring complex manual configuration.
3Productivity
If flows are redistributed based on complexity metrics, then productivity is improved and resource utilization is optimized, but measurement precision requirements increase and difficulty of detecting and measuring worsens
Solution Approach 1:
The patent replaces manual complexity assessment with automated computational metrics. Instead of requiring manual analysis of flow complexity, the system uses algorithmic metrics that automatically calculate and compare flow complexities, enabling high-productivity redistribution without requiring complex measurement capabilities from operators.
Solution Approach 2:
The patent creates universal complexity metrics that can be applied to all integration flows regardless of their specific functionality. These multi-functional metrics evaluate various aspects of flow complexity (number of steps, resource requirements, execution time) through a single standardized framework, simplifying the measurement process while enabling optimized productivity-based redistribution.
Data Source
AI summary
The disclosure generally describes methods, software, and systems for handling integration flows. A set of flows is initially deployed to a single worker set. A load balancing issue is identified that is associated with initial runtime interactions by workers with the single worker set. In response to identifying the load balancing issue, the load balancing issue is analyzed to determine whether to autoscale or generate a new worker set. Load balancing is performed to initiate at least one new worker set. At least one flow to be moved to the at least one new worker set is identified. Movement of the identified at least one flow from a current worker set to a new worker set is performed.