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make vale happy
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doc/source/ray-overview/examples/e2e-timeseries/e2e_timeseries/03-Serving.ipynb

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"## Setting up the environment\n",
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"First, let's import the necessary libraries and set up our environment for Ray Serve deployment:\n"
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"First, import the necessary libraries and set up the environment for Ray Serve deployment:\n"
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"cell_type": "markdown",
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"metadata": {},
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"### Understanding the test results\n",
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"The test demonstrates two important aspects of our Ray Serve deployment:\n",
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"1. **Single Request Processing**: A synchronous request shows how individual time series predictions are handled\n",
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"2. **Concurrent Request Processing**: Asynchronous requests demonstrate Ray Serve's ability to batch multiple requests together for efficient processing\n",
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"The dynamic batching feature automatically groups incoming requests to maximize throughput while maintaining low latency. You'll notice in the logs that Ray Serve combines multiple individual requests into batches (e.g., \"Batch size: 16\") for more efficient model inference.\n",
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"Ray Serve's dynamic batching automatically chunks incoming requests to maximize throughput and hardware utilization while maintaining low latency.\n",
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"<div class=\"alert alert-block alert\"> <b>🔎 Observability for services</b>\n",
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