#model-serving

Keras Model Serving with TensorFlow Serving: Zero‑Downtime Model Update via Version Alias

Goal Deploy a small Keras image‑classification service behind TensorFlow Serving and update the model to a new version without interrupting incoming inference requests. Constraints The serving instance must continue to accept requests during the swap, and the update mechanism should rely only on TensorFlow Serving’s built‑in version‑alias feature rather than

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model-servingkerastensorflow-serving