The Dependency Black Hole

2026-06-24

AI Summary

This study addresses the critical issue of excessive dependency concentration in microservice architectures, where reliance on a few core services violates the principle of loose coupling and impedes independent evolution. For the first time, the authors model microservice dependency networks as black hole structures—comprising singularities, event horizons, and accretion disks—and identify pervasive “dependency black holes” across 267 industrial microservice systems through triangulated validation based on compile-time, runtime, and task-level dependencies. Leveraging network analysis and iterative validation with practitioners, the work formulates and empirically tests three core hypotheses concerning the emergence and evolution of dependency aggregation. The findings elucidate the underlying mechanisms driving this phenomenon and offer both theoretical grounding and practical insights for identifying high-risk services and guiding targeted governance interventions.

Abstract

Microservice architectures promise independent evolution through loose coupling, yet large systems often exhibit strong dependency concentration around a small set of services. In an exploratory industrial case study of a product composed of 267 microservices, we triangulated multiple dependency signals -- compile-time, run-time, and task dependencies -- and iteratively validated our interpretations with practitioners. We observed a recurring macro-structure in the dependency network that resembles a black hole: a dense core of dependency magnets, a transitional region of services increasingly entangled with the core, and an outer region of lightly connected services. Based on these observations, we propose the dependency black hole theory, mapping the network to the black hole anatomy of a singularity, an event horizon, and an accretion disk, and formulating three hypotheses about how dependency concentration emerges and evolves at scale. The theory provides an explanatory lens for reasoning about dependency growth, identifying services at risk of becoming dependency magnets, and motivating governance interventions. We outline practical implications and directions for longitudinal and multi-case validation.

Problem

• microservices
• dependency concentration
• dependency black hole
• loose coupling
• software architecture

Innovation

• dependency black hole
• microservice architecture
• dependency concentration
• software dependency network
• empirical software engineering