Cloud Application Resilience via Dynamic Failure Simulation
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Solution Overview
Problem
Current testing systems for cloud computing environments struggle to accurately simulate production environments and dynamically test multiple components against failure scenarios, making it difficult to evaluate the performance of software applications under various conditions and common failure scenarios.
Innovation Solution
A performance testing system that generates test workflows targeting specific application and infrastructure components, allowing for the simulation of failure scenarios by modifying resources such as network connections or compute instances, and automatically executing tests to identify limitations and build resiliency patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current testing systems are used to evaluate application performance, then testing can be performed, but the testing environment cannot accurately imitate production environment conditions and dynamically simulate failure scenarios
Solution Approach 1:
The testing system dynamically modifies compute resources, network configurations, and container states during test execution to simulate various failure scenarios. The system can spin up additional virtual compute instances, terminate containers, modify network policies, and adjust resource allocations in real-time to recreate production environment conditions and test application resilience.
Solution Approach 2:
The system creates a testing environment that copies the production cloud computing environment's architecture, components, and configurations. By replicating the production environment's structure including virtual machines, containers, networks, and services, the testing system accurately imitates production conditions while allowing controlled failure scenario injection.
2Adaptability or versatility
If multiple components are orchestrated on demand for comprehensive testing, then multiple aspects of application code can be tested, but the system complexity and difficulty of orchestrating components increases
Solution Approach 1:
The system introduces a testing intermediary layer that manages the orchestration of multiple cloud computing components. This intermediary automatically coordinates the provisioning, configuration, and termination of virtual compute instances, containers, networks, and services, simplifying the complexity of orchestrating multiple components while enabling comprehensive multi-aspect application testing.
3Productivity
If additional virtual compute instances are spun up to accommodate peak demand, then the software application can serve more users, but the complexity of managing and testing these dynamic resources increases
Solution Approach 1:
The system performs preliminary provisioning and configuration of virtual compute instances, networks, and services before testing begins. By pre-establishing the infrastructure components and their interconnections, the system reduces the complexity of managing dynamic resources during testing while maintaining the ability to scale to accommodate peak demand scenarios.
Data Source
AI summary
A testing system and method for testing application code against various failure scenarios. The testing system and method generate a test workflow including test source code implementing a series of actions that affect an application component and or an infrastructure component included in application code. The testing system and method execute the test workflow to determine the performance of the application code during one or more failure scenarios caused by the series of actions included in the test workflow. Performance data generated by the test code is analyzed by a performance analysis service or method to identify limitations of the application code and build resiliency patterns that address the limitations and improve the performance of the application code.