Service Optimization System for Distributed Architecture Bottlenecks
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Solution Overview
Problem
The complexity of managing and optimizing distributed systems with service-oriented architecture has increased due to their scale and scope, leading to challenges in provisioning, administering, and optimizing resources effectively, particularly in terms of performance and cost.
Innovation Solution
A system and method that monitors interactions between services in a distributed system, generates trace data, and uses performance metrics and call graphs to optimize service configurations, including service relocation, instance modification, and request routing, to improve performance and reduce costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If distributed systems are scaled up to provide more computing resources and services, then the system capacity and service scope are improved, but the complexity of provisioning, administering, and managing resources increases
Solution Approach 1:
The patent introduces an optimization system as an intermediary between service providers and service consumers in distributed systems. This mediator automatically monitors service interactions, collects trace data, analyzes performance metrics, and optimizes service configurations without requiring direct human intervention in the complex distributed system management, thereby resolving the contradiction between system capacity and management complexity
Solution Approach 2:
The patent implements a feedback mechanism where the optimization system continuously monitors service interactions, collects trace data from service endpoints, analyzes performance metrics, and uses this feedback to automatically adjust and optimize service configurations. This closed-loop feedback system enables autonomous management of scaled distributed systems, addressing the management complexity issue while maintaining high system capacity
2Adaptability or versatility
If more services are added to the distributed system to expand functionality, then the service scope is improved, but the difficulty of optimizing resources effectively increases
Solution Approach 1:
The patent enables services to self-report their interactions and performance metrics through automated trace data collection at service endpoints. Services automatically participate in the optimization process by providing the necessary data without external intervention, allowing the system to effectively optimize resources across expanded service scopes without increasing optimization difficulty
Solution Approach 2:
The patent replaces manual resource optimization processes with an automated optimization system that uses algorithmic analysis of trace data and performance metrics. This substitution of mechanical/manual optimization with automated computational optimization makes it feasible to effectively manage and optimize resources in systems with expanded service scopes
3Adaptability or versatility
If service-oriented architecture is used to implement business processes, then the system flexibility and service reusability are improved, but the network latency and performance optimization challenges increase
Solution Approach 1:
The patent performs preliminary actions by pre-analyzing service interaction patterns and performance metrics to identify optimization opportunities before they become critical performance issues. The system proactively adjusts service configurations and resource allocations based on predicted performance needs, reducing network latency and performance challenges while maintaining service flexibility
Solution Approach 2:
The patent dynamically changes system parameters such as service configuration, resource allocation, and routing based on analyzed performance metrics and trace data. By adjusting these parameters in response to actual system behavior, the optimization system reduces network latency and performance issues while preserving the flexibility benefits of service-oriented architecture
Data Source
AI summary
Methods, systems, and computer-readable media for implementing global optimization of a service-oriented system are disclosed. Trace data is collected for a plurality of service interactions between services in a service-oriented system. Respective costs are determined for a plurality of configuration options in the service-oriented system. An optimized configuration for the service-oriented system is determined based on the respective costs and the trace data. The optimized configuration comprises a selection of one or more of the configuration options. The optimized configuration is deployed to the service-oriented system.