Microservice Configuration Failure Detection Before Canary Deployment

The system performs preliminary analysis of configuration changes before deployment by creating a dependency graph that maps relationships between microservices and their configurations. This pre-deployment analysis identifies potential configuration failures before they affect production, resolving the contradiction by detecting issues early without delaying the deployment process.

The patent segments the microservices architecture into a dependency graph where individual microservices and their configuration dependencies are separated into discrete nodes and edges. This segmentation enables targeted analysis of specific configuration changes and their impact, allowing efficient detection without analyzing the entire system, thus maintaining fast deployment times while improving detection accuracy.

The dependency graph serves as a universal data structure that handles multiple analysis functions simultaneously - it maps microservice relationships, tracks configuration dependencies, identifies affected services, and supports impact analysis. This multi-functionality reduces the need for separate complex analysis systems, achieving high detection accuracy without proportionally increasing system complexity.

The patent introduces an intermediary analysis system that sits between configuration changes and deployment execution. This intermediary creates and analyzes the dependency graph to detect configuration failures before deployment, providing a structured approach that manages complexity by isolating the analysis logic from both configuration management and deployment execution.

The system applies local quality analysis by examining only the specific portions of the configuration space that are relevant to each change. The dependency graph enables targeted analysis of local configurations and their direct dependencies rather than analyzing the entire configuration space, maintaining detection efficiency while preserving necessary configuration context through the graph's structured representation.

The patent extracts only the essential configuration dependencies and relationships into the dependency graph, separating relevant information from unnecessary configuration details. This extraction process reduces the search space by focusing analysis on extracted dependency relationships while preserving the critical configuration context needed for accurate detection, achieving both efficiency and completeness.