Client Agent Transaction Simulation for Service Performance Gauging
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Enterprises face challenges in accurately and efficiently gauging performance of services across multiple locations, leading to undetected issues and potential loss of customers due to the inability to gather metrics below the site level, affecting customer satisfaction and pricing agreements.
Innovation Solution
A method involving an agent that simulates transactions on clients over a network, allowing for the collection of metrics at the operation level, which can be mapped to Service-Level Agreements (SLAs) or End-User Performance (EUP) metrics, enabling proactive identification of problems and improved service management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If enterprises use existing mechanisms to determine response times at the site level, then they can monitor overall system availability, but they cannot gather metrics below the site level to individual services and operations
Solution Approach 1:
The patent segments the monitoring system into distributed agents deployed at individual client devices, each capable of independently measuring performance metrics for specific services and operations. This segmentation enables granular measurement at the operation level while distributing the monitoring functionality across multiple independent components rather than requiring a centralized complex system.
Solution Approach 2:
The patent introduces intermediary agents that act as mediators between end-user clients and enterprise services. These agents simulate user interactions and collect performance metrics without requiring direct modification of the services being monitored, thereby enabling detailed measurement while maintaining system independence and reducing complexity.
2Reliability
If enterprises deploy agents on clients to simulate transactions and collect metrics, then they can accurately gauge service performance at the operation level, but the complexity and resource requirements of the monitoring system increase
Solution Approach 1:
The patent uses agents that copy and simulate actual user transactions and interactions with services. By creating virtual copies of user behavior, the system can reliably measure service performance under realistic conditions without requiring physical test equipment or modifying the actual service infrastructure, thereby improving reliability while managing complexity.
3Loss of time
If enterprises rely on site-level performance metrics, then they can maintain overall system availability, but true problems at the service and operation level go undetected for extended periods
Solution Approach 1:
The patent implements preliminary action by having agents continuously simulate transactions and monitor service operations in advance before actual problems affect end users. This proactive monitoring detects performance degradation and issues at the operation level before they escalate, reducing problem detection time while the automated measurement capabilities handle the complexity of service-level monitoring.
4Measurement precision
If enterprises cannot accurately measure service performance metrics, then they cannot properly price services based on SLAs or EUP metrics, but implementing detailed measurement increases system complexity
Solution Approach 1:
The patent enables self-service measurement where distributed agents automatically collect, measure, and report performance metrics for services and operations. The system performs its own measurement and monitoring functions without requiring external intervention or complex centralized management infrastructure, thereby achieving accurate SLA and EUP metric measurement while keeping the system relatively simple through automation.
Data Source
AI summary
Techniques for gauging performance of services are provided. A client agent is configured to process on a client and simulates operations of a transaction as instructed by a server agent. The client agent also gathers metrics for each of the operations as they process on the client and passes the metrics back to the server agent. The server agent analyzes the metrics in accordance with a policy and takes one or more actions in response thereto.