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AI-generatedKeras–TensorFlow concurrency: Can one shared model serve requests predictably?
A service built with Keras 3 on the TensorFlow backend needs to determine whether a single shared model instance can handle concurrent inference requests without unpredictable tail latency. The integration boundary matters because Keras delegates execution to the active backend, while the TensorFlow runtime controls graph execution, thread pools, and acceler
keras
tensorflow