Adaptive API Call Sequence Detection for Production Simulation
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Solution Overview
Problem
Existing production systems lack accurate simulation methods to determine optimal API call sequences, leading to inefficient resource utilization and increased client latency due to imprecise modeling of API call interactions.
Innovation Solution
Adaptive API call sequence detection generates precise API call sequences based on response and gap times, allowing for more accurate simulation and reconfiguration of production systems to optimize resource utilization and reduce latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional simulation methods are used to model API call interactions, then the simulation process is simpler to implement, but the accuracy of modeling API call interactions is insufficient leading to imprecise production system models
Solution Approach 1:
The system performs preliminary detection of API call sequences in the production system before simulation. By pre-identifying and recording actual API call sequences, response times, and gap times, the system prepares accurate input data for simulation, thereby improving modeling accuracy without adding complexity to the simulation process itself
Solution Approach 2:
The system creates copies of actual API call sequences detected from the production system and uses these copies as input for simulation. This copying approach preserves the accuracy of real API interactions while allowing the simulation to run on replicated data, separating the complexity of detection from the simulation process
2Productivity
If API call sequences are not accurately detected, then the system operation is simpler, but the resource utilization becomes inefficient and client latency increases
Solution Approach 1:
The system implements feedback by detecting actual API call sequences and their performance characteristics (response times, gap times) from the production system, then using this feedback information to generate accurate test input data. This closed-loop approach ensures that simulation inputs reflect real-world patterns, improving resource utilization efficiency and reducing client latency through accurate modeling
Solution Approach 2:
The system replaces manual or simplistic assumptions about API call patterns with automated detection mechanisms that observe and record actual API sequences. This substitution of mechanical detection for manual configuration automatically captures accurate timing and sequence information, leading to improved productivity and reduced latency
3Reliability
If precise API call sequences are generated through detection, then the simulation accuracy is improved, but the detection and processing complexity increases
Solution Approach 1:
The system segments the complex task of accurate simulation into distinct phases: detection of API call sequences, recording of response times and gap times, generation of test input data, and execution of simulation. By segmenting the process, each component can be optimized independently, improving overall simulation accuracy while managing complexity through modular organization
Data Source
AI summary
One or more computing devices, systems, and/or methods for adaptive API call sequence detection are provided. A series of API calls and gap times between API calls of the series of API calls are recorded. The API calls are received and processed by a production system. The API calls are assigned into API call sequences. An end of an API call sequence is detected based upon a minimum response time and the gap times between the API calls. The API call sequences are utilized to simulate execution of the production system. A configuration is generated and applied to the production system based upon a result of the simulation.