Serverless Performance Testing Framework
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Solution Overview
Problem
Conventional performance testing techniques are complex, time-consuming, error-prone, and not user-friendly, requiring manual configuration and disrupting application services during testing, while analysis and reporting are tedious and non-intuitive.
Innovation Solution
A serverless performance testing framework that allows users to specify parameters for testing within a cloud-based computing environment, generating serverless functions for executing performance tests without disrupting the application service, enabling real-time data storage and analysis, and providing user-friendly self-service capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional performance testing techniques are used, then testing can be performed, but the process becomes complex and time-consuming requiring manual configuration
Solution Approach 1:
The system performs self-configuration by automatically generating performance test scripts from user-defined parameters and templates. The framework autonomously sets up testing environments, configures test scenarios, and manages execution without requiring manual intervention, thereby reducing complexity while maintaining testing reliability
Solution Approach 2:
The system pre-configures performance testing templates and configurations in advance. Common test scenarios are prepared beforehand with default settings, allowing users to quickly initiate testing by simply selecting from pre-defined templates rather than configuring everything from scratch, thus reducing both complexity and time requirements
2Reliability
If conventional performance testing techniques are used, then testing can be performed, but it is not user-friendly and error-prone
Solution Approach 1:
The framework automatically generates test configurations and scripts based on user inputs, eliminating the need for users to manually write complex test code. The system self-corrects configuration errors and validates parameters, making the process accessible to non-technical users while maintaining high reliability
Solution Approach 2:
The system introduces an intermediary layer between the user and the complex testing infrastructure. This abstraction layer translates simple user requirements into detailed test configurations, shielding users from complexity while ensuring accurate and reliable test execution
3Reliability
If conventional performance testing techniques are used, then testing can be performed, but analysis and reporting are tedious and time-consuming
Solution Approach 1:
The system performs data collection, analysis, and report generation continuously throughout the testing process. Instead of separate sequential steps, the framework continuously aggregates test data, analyzes performance metrics in real-time, and updates reports dynamically, eliminating idle time between testing and analysis phases
Solution Approach 2:
The system implements automated feedback loops where test results are immediately analyzed and fed back into the reporting system. Performance metrics are continuously monitored and automatically interpreted, with insights fed back to users in real-time, dramatically reducing the time required for manual analysis and report generation
4Reliability
If conventional performance testing techniques are used, then testing can be performed, but application services are disrupted during testing
Solution Approach 1:
The system segments the testing process into isolated virtual environments and containers. Performance tests are executed in separate, sandboxed instances that do not interfere with the production application services. This segmentation allows concurrent operation of testing and production systems without mutual disruption
Solution Approach 2:
The framework introduces intermediary components that act as buffers between the performance testing process and the application services. These intermediaries manage test traffic, isolate test impacts, and ensure that testing operations do not propagate harmful effects to the production system, maintaining service continuity
Data Source
AI summary
Techniques for serverless performance testing of applications are provided. A user can indicate an application to test within a serverless computing framework. The user can specify parameters for testing the application. A performance test execution file can be generated based on the indicated application and the specified testing parameters. Serverless functions for implementing the testing of the application can be generated based on the performance test execution file. The serverless functions can be executed to implement the testing of the application code on a cloud-based computing resource. Test outputs can be generated and stored for review and analysis in real-time during the testing and after the testing is concluded.


