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SoK: Microservice Architectures from a Dependability Perspective

Dāvis Kažemaks, Jérémie Decouchant

TL;DR

This paper surveys runtime faults and vulnerabilities in microservice architectures, emphasizing runtime detection and recovery over offline mitigation. It systematically maps literature from 2019–2024, using a structured methodology and threat-modeling lens to classify faults into performance, architecture, component, and security categories. The meta-analysis shows rapid growth with a stronger focus on detection than recovery, and highlights the promise of multi-modal, graph-based localization approaches, while noting gaps in service registry/monitoring fault coverage and the lack of standardized datasets. The work provides a practical overview for risk analysis and a roadmap for future empirical comparisons and comprehensive runtime resilience, guiding both researchers and practitioners toward more robust MSAs.

Abstract

The microservice software architecture leverages the idea of splitting large monolithic applications into multiple smaller services that interact using lightweight communication schemes. While the microservice architecture has proven its ability to support modern business applications, it also introduces new possible weak points in a system. Some scientific literature surveys have already addressed fault tolerance or security concerns but most of them lack analysis on the fault and vulnerability coverage that is introduced by microservice architectures. We explore the known faults and vulnerabilities that microservice architecture might suffer from, and the recent scientific literature that addresses them. We emphasize runtime detection and recovery mechanisms instead of offline prevention and mitigation mechanisms to limit the scope of this document.

SoK: Microservice Architectures from a Dependability Perspective

TL;DR

This paper surveys runtime faults and vulnerabilities in microservice architectures, emphasizing runtime detection and recovery over offline mitigation. It systematically maps literature from 2019–2024, using a structured methodology and threat-modeling lens to classify faults into performance, architecture, component, and security categories. The meta-analysis shows rapid growth with a stronger focus on detection than recovery, and highlights the promise of multi-modal, graph-based localization approaches, while noting gaps in service registry/monitoring fault coverage and the lack of standardized datasets. The work provides a practical overview for risk analysis and a roadmap for future empirical comparisons and comprehensive runtime resilience, guiding both researchers and practitioners toward more robust MSAs.

Abstract

The microservice software architecture leverages the idea of splitting large monolithic applications into multiple smaller services that interact using lightweight communication schemes. While the microservice architecture has proven its ability to support modern business applications, it also introduces new possible weak points in a system. Some scientific literature surveys have already addressed fault tolerance or security concerns but most of them lack analysis on the fault and vulnerability coverage that is introduced by microservice architectures. We explore the known faults and vulnerabilities that microservice architecture might suffer from, and the recent scientific literature that addresses them. We emphasize runtime detection and recovery mechanisms instead of offline prevention and mitigation mechanisms to limit the scope of this document.

Paper Structure

This paper contains 44 sections, 4 figures, 6 tables.

Table of Contents

  1. Introduction
  2. Related work
  3. Background
  4. The microservice architecture
  5. Dependability
  6. Threat modeling
  7. Microservice faults
  8. Methodology
  9. Search queries
  10. Inclusion/exclusion criteria
  11. Forward snowballing
  12. Data extraction
  13. Meta analysis
  14. Publications per year
  15. Keyword
  16. ...and 29 more sections

Figures (4)

  • Figure 1: An example of a microservice architecture with a centralized service registry and API endpoints for communication
  • Figure 2: Method followed to identify primary literature
  • Figure 3: Number of selected publications per year
  • Figure 4: Evolution of the ranking of the 10 most important keywords ranking depending on the year using TF-IDF