When ML Meets Microservices: Engineering for Scalability and Performance | HackerNoon
Briefly

Microservices can be thought of as Lego blocks for software; they allow independent scaling and maintenance of specific tasks in Machine Learning workflows.
Statelessness is crucial in microservices for ML systems, enabling independent scaling and simplifying the management of model files and configurations.
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