Fault Injection Testing for Compute Infrastructure Resilience
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Solution Overview
Problem
Existing systems with compute capabilities often fail to operate effectively under various scenarios due to physical constraints, limiting application performance and reliability, necessitating thorough testing before implementation.
Innovation Solution
A method involving intentional fault injection in a compute infrastructure, with weighted fault analysis to identify and prevent application failures, and recommend necessary changes to enhance resilience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If fault injection testing is performed on compute infrastructure, then system reliability is improved, but testing complexity and time consumption increase
Solution Approach 1:
The patent applies preliminary action by performing fault injection testing before the application is deployed to production environments. The testing framework proactively identifies potential failure modes and vulnerabilities in the compute infrastructure before they can impact real-world operations, allowing developers to fix issues in advance rather than reacting to production failures.
Solution Approach 2:
The testing framework implements self-service by automatically generating test cases, executing fault injection scenarios, analyzing results, and providing actionable recommendations without requiring manual intervention. The system autonomously manages the entire testing lifecycle, from configuring test parameters to generating reports, reducing the burden on developers and testers.
2Reliability
If comprehensive fault injection testing is conducted, then application performance under diverse conditions is improved, but testing time and computational resources increase
Solution Approach 1:
The patent applies partial action by implementing a tiered testing approach that focuses on the most critical fault scenarios first. The system prioritizes testing based on risk assessment, concentrating computational resources on high-impact failure modes while using lighter testing for less critical areas. This allows comprehensive coverage of essential scenarios without the excessive time cost of testing every possible fault condition in equal detail.
Solution Approach 2:
The testing framework implements periodic action by enabling scheduled testing at different stages of the development lifecycle. Rather than requiring exhaustive testing before every deployment, the system performs targeted fault injection tests periodically during development, staging, and pre-production phases, allowing continuous validation without complete re-testing of all scenarios each time.
3Measurement precision
If detailed fault analysis and weighting is performed, then identification of error-prone areas is improved, but computational overhead increases
Solution Approach 1:
The patent applies local quality by implementing weighted fault analysis that focuses computational effort on identifying and analyzing the most critical error-prone areas. Rather than uniformly analyzing all faults with equal detail, the system assigns weights to different fault types based on their potential impact, concentrating analytical resources on high-weight scenarios that pose the greatest risk to system reliability.
Solution Approach 2:
The testing framework applies parameter changes by dynamically adjusting the depth and granularity of fault analysis based on preliminary results and risk assessments. The system modifies analytical parameters such as trace depth, log detail level, and correlation scope according to the severity and frequency of observed faults, reducing computational overhead for low-priority areas while maintaining detailed analysis for critical issues.
Data Source
AI summary
A computer-implemented method, according to one embodiment, includes: intentionally causing faults to be injected in a compute infrastructure, and determining whether the injected faults cause application failures. Weights are also assigned to the injected faults based on severity of the respective application failures. The weighted faults are compared, and changes to the compute infrastructure are recommended based on the comparison. Moreover, the changes that are recommended are configured to prevent the application failures. Other systems, methods, and computer program products are described in additional embodiments.