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paperarXiv (systems, data, ML)·22 Oct 2026·Anatoly A. Krasnovsky

Procrustes-Bering-Sheaft: Automated Model Discovery and Virtual Crash Tests for Microservices

Automates model discovery and virtual crash tests to estimate microservice availability.

Abstract

Procrustes-Bering-Sheaft automates lightweight model discovery and virtual crash tests for microservices. Each test estimates operation availability by Monte Carlo sampling of service and communication failures. Procrustes checks deployment and tracing evidence; Bering discovers dependencies and incorporates replica declarations; Sheaft evaluates declared operation-success conditions. Independent command-line interfaces exchange reusable, versioned artifacts. The toolchain extends an earlier graph-based approach with mandatory-call contracts, failure-tolerance sweeps, baseline comparison, component-importance analysis, and CI/CD gates. We demonstrate the workflow on one HTTP operation. Six controlled execution states exposed two mismatches between reachability and observed success; an explicit required-call predicate matched all six. Two modelled one-replica additions produced different decisions: recommendation retained an availability-target violation, whereas catalog restored the baseline estimate of 0.979900 and grid tolerance of 0.12. Analytical oracles and controlled tests verify the implementation; archived replay checks numerical continuity with two earlier studies.