Resiliency Analyzer for Distributed Systems
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Solution Overview
Problem
Distributed systems face challenges in managing and ensuring resilience against complex failure scenarios, as existing fault injection methods fail to capture the intricacies of real-world outages, leading to potential system-wide outages and performance degradation.
Innovation Solution
An automated resiliency analyzer that models complex failure scenarios by injecting multiple state changes across multiple components, allowing for accurate resiliency testing and providing recommendations for system architecture changes to mitigate vulnerabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing fault injection methods are used to test distributed systems, then testing can be performed, but the methods fail to capture the intricacies of real-world outages leading to insufficient resiliency assessment
Solution Approach 1:
The system performs preliminary analysis of system architecture to identify computing resources and their relationships before conducting resiliency tests. This preliminary action enables the creation of accurate failure scenario models that reflect real-world conditions, thereby improving both measurement precision and reliability assessment
Solution Approach 2:
The system dynamically generates and executes multiple failure scenarios by injecting different failure conditions into identified computing resources. This dynamic approach allows the system to capture complex real-world outage patterns rather than using static, predetermined test cases, improving the accuracy of resiliency assessment
2Measurement precision
If manual resiliency testing is performed to assess system vulnerabilities, then detailed analysis can be conducted, but the process is time-consuming and prone to human error
Solution Approach 1:
The system automatically analyzes system architecture, identifies computing resources, determines their relationships, and executes failure scenarios without continuous human intervention. This self-service capability maintains high measurement precision while dramatically reducing the time required for resiliency testing compared to manual methods
Solution Approach 2:
The system automatically processes test results and generates resiliency reports with actionable recommendations. This feedback loop eliminates manual analysis time while maintaining assessment accuracy, as the automated system systematically evaluates test outcomes and produces comprehensive vulnerability assessments
3Reliability
If complex failure scenarios are modeled with multiple state changes across multiple components, then accurate resiliency testing is achieved, but the complexity of the testing system increases
Solution Approach 1:
The system segments the complex task of resiliency testing into distinct modules: architecture analysis, resource identification, relationship determination, failure scenario generation, test execution, and result analysis. This segmentation manages system complexity by organizing functions into manageable components while maintaining the ability to model complex failure scenarios
Solution Approach 2:
The system employs a unified automated framework that handles multiple functions including architecture parsing, resource identification, relationship mapping, and failure injection through a single integrated platform. This multi-functional approach reduces overall system complexity compared to using separate tools for each testing function
Data Source
AI summary
Methods, systems, and computer-readable media for automated resiliency analysis in distributed systems are disclosed. A resiliency analyzer determines a plurality of computing resources associated with a system architecture. The resiliency analyzer determines one or more similar system architectures with respect to the system architecture. The resiliency analyzer determines one or more anticipated behaviors associated with the system architecture based at least in part on the plurality of computing resources and the one or more similar system architectures. The resiliency analyzer generates one or more resiliency tests associated with the one or more anticipated behaviors. The one or more resiliency tests are performed on the system architecture to determine one or more effects of the behaviors on a resiliency of the system architecture.