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Network Centrality as a New Perspective on Microservice Architecture

Alexander Bakhtin, Matteo Esposito, Valentina Lenarduzzi, Davide Taibi

TL;DR

The paper investigates whether network centrality metrics applied to a microservice SDG provide insights beyond traditional size, complexity, and quality metrics. By reconstructing 53 microservices across 24 OSS Java Spring projects and computing 155 SM/CM metrics, the authors analyze 902 metric correlations, finding 282 significant but generally weak-to-moderate relationships, largely driven by the SDG structure. They observe that centrality correlates with API exposure and tends to align with simpler, well-maintained services, while subgraph centrality shows distinct patterns, including links to security signals. The work proposes centrality as a complementary lens for architectural analysis and anti-pattern detection in MSAs, suggesting ratio-based centralities for robust cross-system thresholds and calling for further study of subgraph centrality’s applicability.

Abstract

Context: Over the past decade, the adoption of Microservice Architecture (MSA) has led to the identification of various patterns and anti-patterns, such as Nano/Mega/Hub services. Detecting these anti-patterns often involves modeling the system as a Service Dependency Graph (SDG) and applying graph-theoretic approaches. Aim: While previous research has explored software metrics (SMs) such as size, complexity, and quality for assessing MSAs, the potential of graph-specific metrics like network centrality remains largely unexplored. This study investigates whether centrality metrics (CMs) can provide new insights into MSA quality and facilitate the detection of architectural anti-patterns, complementing or extending traditional SMs. Method: We analyzed 24 open-source MSA projects, reconstructing their architectures to study 53 microservices. We measured SMs and CMs for each microservice and tested their correlation to determine the relationship between these metric types. Results and Conclusion: Among 902 computed metric correlations, we found weak to moderate correlation in 282 cases. These findings suggest that centrality metrics offer a novel perspective for understanding MSA properties. Specifically, ratio-based centrality metrics show promise for detecting specific anti-patterns, while subgraph centrality needs further investigation for its applicability in architectural assessments.

Network Centrality as a New Perspective on Microservice Architecture

TL;DR

The paper investigates whether network centrality metrics applied to a microservice SDG provide insights beyond traditional size, complexity, and quality metrics. By reconstructing 53 microservices across 24 OSS Java Spring projects and computing 155 SM/CM metrics, the authors analyze 902 metric correlations, finding 282 significant but generally weak-to-moderate relationships, largely driven by the SDG structure. They observe that centrality correlates with API exposure and tends to align with simpler, well-maintained services, while subgraph centrality shows distinct patterns, including links to security signals. The work proposes centrality as a complementary lens for architectural analysis and anti-pattern detection in MSAs, suggesting ratio-based centralities for robust cross-system thresholds and calling for further study of subgraph centrality’s applicability.

Abstract

Context: Over the past decade, the adoption of Microservice Architecture (MSA) has led to the identification of various patterns and anti-patterns, such as Nano/Mega/Hub services. Detecting these anti-patterns often involves modeling the system as a Service Dependency Graph (SDG) and applying graph-theoretic approaches. Aim: While previous research has explored software metrics (SMs) such as size, complexity, and quality for assessing MSAs, the potential of graph-specific metrics like network centrality remains largely unexplored. This study investigates whether centrality metrics (CMs) can provide new insights into MSA quality and facilitate the detection of architectural anti-patterns, complementing or extending traditional SMs. Method: We analyzed 24 open-source MSA projects, reconstructing their architectures to study 53 microservices. We measured SMs and CMs for each microservice and tested their correlation to determine the relationship between these metric types. Results and Conclusion: Among 902 computed metric correlations, we found weak to moderate correlation in 282 cases. These findings suggest that centrality metrics offer a novel perspective for understanding MSA properties. Specifically, ratio-based centrality metrics show promise for detecting specific anti-patterns, while subgraph centrality needs further investigation for its applicability in architectural assessments.
Paper Structure (27 sections, 6 figures, 1 table)

This paper contains 27 sections, 6 figures, 1 table.

Table of Contents

  1. Introduction
  2. Background
  3. Static architecture reconstruction
  4. Size metrics
  5. Complexity metrics
  6. Quality metrics
  7. Centrality metrics
  8. Related work
  9. Empirical study design
  10. Goal, Research Questions, and Hypotheses
  11. Study context
  12. Data collection
  13. Reconstructing the architecture
  14. Calculating the centrality metrics
  15. Keep only the greatest weakly connected component
  16. ...and 12 more sections

Figures (6)

  • Figure 1: Data collection and analysis process.
  • Figure 2: Different categories of collected projects.
  • Figure 3: Heat-map of correlation of microservice centrality with size metrics.
  • Figure 4: Heat-map of correlation of microservice centrality with quality metrics.
  • Figure 5: Heat-map of correlation of microservice centrality with complexity metrics.
  • ...and 1 more figures