Microservice API Evolution in Practice: A Study on Strategies and Challenges
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Abstract (arXiv)
Nowadays, many companies design and develop their software systems as a set of loosely coupled microservices that communicate via their Application Programming Interfaces (APIs). While the loose coupling improves maintainability, scalability, and fault tolerance, it poses new challenges to the API evolution process. Related works identified communication and integration as major API evolution challenges but did not provide the underlying reasons and research directions to mitigate them. In this paper, we aim to identify microservice API evolution strategies and challenges in practice and gain a broader perspective of their relationships. We conducted 17 semi-structured interviews with developers, architects, and managers in 11 companies and analyzed the interviews with open coding used in grounded theory. In total, we identified six strategies and six challenges for REpresentational State Transfer (REST) and event-driven communication via message brokers. The strategies mainly focus on API backward compatibility, versioning, and close collaboration between teams. The challenges include change impact analysis efforts, ineffective communication of changes, and consumer reliance on outdated versions, leading to API design degradation. We defined two important problems in microservice API evolution resulting from the challenges and their coping strategies: tight organizational coupling and consumer lock-in. To mitigate these two problems, we propose automating the change impact analysis and investigating effective communication of changes as open research directions.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). First posted on arXiv 14 Nov 2023.
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Citing papers per year: 2025: 4; 2026: 3.
7 papers.
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- 2026Silent Failures in Agent-Tool Interaction: An Audit of ToolUniverse21 Sep 2026
- 2026ClouDens: Operational Context-Aware Anomaly Detection for Large-scale Cloud System Monitoring20 Jul 2026
- 2026SAGAI-MID: A Generative AI-Driven Middleware for Dynamic Runtime Interoperability30 Mar 2026
- 2025From Specification to Service: Accelerating API-First Development Using Multi-Agent Systems22 Oct 2025
- 2025LLM Agents Are the Antidote to Walled Gardens30 Jun 2025
- 2025Doc2Agent: Scalable Generation of Tool-Using Agents from API Documentation24 Jun 2025
- 2025Explore-Construct-Filter: An Automated Framework for Rich and Reliable API Knowledge Graph Construction19 Feb 2025