Theme and Topics

Transitioning to microservices-based architectures is crucial for companies in highly competitive markets, where the agility and flexibility of software systems are essential. Microservices as an architectural style facilitate agility, streamline integration and enable more flexible solutions. However, an adoption also increases complexity and requires novel software construction techniques and advanced agile engineering practices. Especially since the rise of large language models (LLMs), development practices increasingly incorporate AI tools, opening a new field of challenges and opportunities for microservices programming.

The AMP workshop aims to collect experiences on microservice adoption and reporting best practices, as well as failure cases, to build community knowledge based on past mistakes and successes. We seek to collect original work on the science and engineering of programming microservices, including but not limited to evolutionary and agile architectures, methods and tools, patterns, operational practices and DevOps, agile teams, programming languages and techniques for microservices, software quality aspects, metrics and software analytics, verification, test-driven approaches and testing, architectural refactoring, empirical studies, and experience reports on microservices adoption and teaching. We also emphasize the current trend towards AI-driven software engineering practices and the development of data-intensive applications. The workshop seeks for solutions and experiences both on AI-assisted tooling, and building data-intensive applications and LLMs using microservices. The workshop is open to experience reports from practitioners and academics. We seek to collect original work on the science and engineering of programming microservices, including but not limited to the following topics:

Software engineering methods and tools for microservices
Enable an evolutionary and agile architecture with microservices
Microservices in the context of AI-based data-intensive applications and LLMs
Microservices for machine learning model operation management (MLOps)
AI-enhanced development and refactoring of microservices-based systems
Programming languages, techniques, and design patterns for microservices
Operations practices for microservices and DevOps support
Organizational dynamics and practices of agile teams working with microservices
Software Quality, metrics, and analytics in microservice architectures
Testing, verification, and test-driven development for microservices
Architecture recovery and documentation strategies for microservices
Refactoring in the context of microservice architectures
Empirical studies and experience reports on microservices
Teaching and learning microservices: education strategies and experiences

AMP 2025 is organized with the official support of the Microservices Community, an international non-profit organization interested in sharing knowledge and fostering collaborations about the paradigm of microservices.