MLOps with Microservices: A Case Study on the Maritime Domain
Ferreira,Renato Cordeiro Trapmann,Rowanne van den Heuvel,Willem-Jan
Ferreira,Renato Cordeiro
Trapmann,Rowanne
van den Heuvel,Willem-Jan
Abstract
This case study describes challenges and lessons learned on building Ocean Guard: a Machine Learning–Enabled System (MLES) for anomaly detection in the maritime domain. First, the paper presents the system’s specification, and architecture. Ocean Guard was designed with a microservices’ architecture to enable multiple teams to work on the project in parallel. Then, the paper discusses how the developers adapted contract-based design to MLOps for achieving that goal. As a MLES, Ocean Guard employs code, model, and data contracts to establish guidelines between its services. This case study hopes to inspire software engineers, machine learning engineers, and data scientists to leverage similar approaches for their systems.
Description
Date
2025-06-16
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Research Projects
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Keywords
Microservices, MLOps, Software Architecture, Machine Learning Enabled Systems, Maritime Domain, Case Study
Citation
Ferreira, R C, Trapmann, R & van den Heuvel, W-J 2025, MLOps with Microservices : A Case Study on the Maritime Domain. in Service-Oriented Computing : 19th Symposium and Summer School, SummerSOC 2025, Crete, Greece, June 16–21, 2025, Revised Selected Papers. vol. 2602, Communications in Computer and Information Science, vol. 2602, pp. 3-15. https://doi.org/10.1007/978-3-032-07313-6_1