TensorFlow Serving

TensorFlow Serving                         MLOps; Machine Learning

noun phrase

Definition: A flexible, high-performance serving system for machine-learning models designed for production environments, with built-in support for TensorFlow models and APIs for inference, model versioning, and deployment. This wording follows the official TensorFlow Serving documentation and repository description [TensorFlow Documentation].

Example in context: “We implement mCache using Tensorflow Serving as the underlying framework.” [Mo et al. 2025]

Synonym: TensorFlow model server (context-dependent)

Related terms: serving; model deployment; inference serving; TensorFlow Extended (TFX); REST API; gRPC.

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