Design, Monitoring, and Testing of Microservices Systems: The Practitioners' Perspective
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Abstract (arXiv)
Context: Microservices Architecture (MSA) has received significant attention in the software industry. However, little empirical evidence exists on design, monitoring, and testing of microservices systems. Objective: This research aims to gain a deep understanding of how microservices systems are designed, monitored, and tested in the industry. Method: A mixed-methods study was conducted with 106 survey responses and 6 interviews from microservices practitioners. Results: The main findings are: (1) a combination of domain-driven design and business capability is the most used strategy to decompose an application into microservices, (2) over half of the participants used architecture evaluation and architecture implementation when designing microservices systems, (3) API gateway and Backend for frontend patterns are the most used MSA patterns, (4) resource usage and load balancing as monitoring metrics, log management and exception tracking as monitoring practices are widely used, (5) unit and end-to-end testing are the most used testing strategies, and (6) the complexity of microservices systems poses challenges for their design, monitoring, and testing, for which there are no dedicated solutions. Conclusions: Our findings reveal that more research is needed to (1) deal with microservices complexity at the design level, (2) handle security in microservices systems, and (3) address the monitoring and testing challenges through dedicated solutions.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). First posted on arXiv 7 Aug 2021.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 0; 2024: 1; 2025: 1; 2026: 3.
6 papers.
- 2025Adaptive Root Cause Localization for Microservice Systems with Multi-Agent Recursion-of-Thoughtcited by 13
- 2026Agentic Memory Enhanced Recursive Reasoning for Root Cause Localization in Microservicescited by 9
- 2026Hypothesize-Then-Verify: Speculative Root Cause Analysis for Microservices with Pathwise Parallelismcited by 8
- 2021Using sequential drift detection to test the API economycited by 0
- 2024Automated Test-Case Generation for REST APIs Using Model Inference Search Heuristiccited by 0
- 2026Actionable Meta-Requirements for AI Robustness Auditingcited by 0
- 2026Actionable Meta-Requirements for AI Robustness Auditing9 Oct 2026
- 2026Hypothesize-Then-Verify: Speculative Root Cause Analysis for Microservices with Pathwise Parallelism6 Jan 2026
- 2026Agentic Memory Enhanced Recursive Reasoning for Root Cause Localization in Microservices6 Jan 2026
- 2025Adaptive Root Cause Localization for Microservice Systems with Multi-Agent Recursion-of-Thought28 Aug 2025
- 2024Automated Test-Case Generation for REST APIs Using Model Inference Search Heuristic4 Dec 2024
- 2021Using sequential drift detection to test the API economy9 Nov 2021