This experience report explains the techniques applied while building Ocean Guard, an ML-Enabled System (MLES) for anomaly detection in the maritime domain. In particular, it highlights the trade-offs of applying the Ports and Adapters pattern to support building multiple microservices in a monorepo codebase. The paper hopes to inspire software engineers, ML engineers, and data scientists to apply the same practices to build their MLES.