Fault Injection Orchestration for Service Resilience Assessment
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Solution Overview
Problem
Existing fault injection methods for software services are tedious and require significant human intervention, lacking centralized mechanisms for injecting faults and analyzing the behavior of distributed services, especially in cloud environments, and do not provide insights into mean time to recover or anomalies.
Innovation Solution
A fault injection architecture with an orchestration platform that automates the injection of faults into services across different environments, collects pre-and post-injection metrics, and performs analyses such as SQL, connection, lock, and correlation analysis to identify anomalies and measure mean time to recover, using a unified platform with minimal human intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual fault injection methods are used, then fault injection can be performed, but significant human intervention is required making the process tedious
Solution Approach 1:
The system performs self-testing through automated fault injection and resilience assessment. The orchestration platform automatically injects faults, collects metrics, performs analyses, and generates reports without requiring manual intervention, enabling the system to assess its own resilience properties.
Solution Approach 2:
An orchestration platform acts as an intermediary between the fault injection system and the services being tested. This platform coordinates fault injection across multiple services, manages metric collection, and orchestrates the analysis process, automating what would otherwise require significant human coordination.
2Productivity
If distributed services are used, then system scalability and development speed improve, but debugging and ensuring services work together correctly becomes more complex
Solution Approach 1:
The system is divided into independent microservices that can be developed, deployed, and scaled separately. Each service maintains its own resilience properties, and the orchestration platform coordinates testing across these segmented services, managing complexity through structured decomposition.
Solution Approach 2:
The system implements continuous feedback loops where metrics are collected before and after fault injection, analyses are performed on the results, and resilience assessments are generated. This feedback mechanism automatically detects issues in distributed service interactions without requiring manual debugging.
3Reliability
If comprehensive service interaction testing is performed, then reliability improves, but the number of possible combinations and interactions makes testing difficult to account for all cases
Solution Approach 1:
The system focuses on injecting specific, targeted faults that are most likely to reveal resilience issues rather than attempting to test all possible service interaction combinations. This selective approach efficiently assesses reliability without requiring exhaustive testing of every scenario.
Solution Approach 2:
The orchestration platform provides a universal framework that can test multiple services across different environments using the same coordinated approach. The system handles topology discovery, metric collection, and analysis in a unified manner that works across diverse service architectures.
4Measurement precision
If automated fault injection and analysis is implemented, then resilience assessment capability improves, but system infrastructure complexity increases
Solution Approach 1:
The orchestration platform serves as an intermediary layer that manages the complexity of automated fault injection and analysis. It coordinates between fault injection systems, service environments, and analysis tools, providing precise resilience measurements without exposing the underlying infrastructure complexity to users.
Solution Approach 2:
The system automatically performs topology discovery, metric collection, and resilience analysis without requiring manual configuration. The automated processes assess resilience properties precisely while the system self-manages the infrastructure complexity required to enable these measurements.
Data Source
AI summary
A computer system receives a fault injection payload that conforms to a template and identifies one or more faults to inject into a set of services of one or more target environments identified in the fault injection payload. The computer system performs a set of iterations to inject the one or more faults. A particular iteration includes the computer system identifying, for a particular fault, a fault injection system capable of injecting the particular fault. Based on the fault injection payload, the computer system generates and provides a payload ingestible by the identified fault injection system to cause the identified fault injection system to inject the fault. After performing the set of iterations to inject the one or more faults, the computer system performs a set of analyses to determine whether one or more anomalies occurred as a result of the one or more injected faults.