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Initial commit: add CloudPilot project
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build/lib/cloudpilot/scaling.py

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@@ -61,14 +61,3 @@ def recommend_scaling(cpu_util, mem_util, request_rate, network_latency, user_de
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scaler = RLScaler() # Loads the TorchScript model or uses dummy.
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action = scaler.get_action(state)
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return f"RL-based Recommendation: {action}"
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# For testing purposes, you can uncomment the block below:
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# if __name__ == "__main__":
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# # Example state values.
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# cpu_util = 75.0 # e.g., 75% CPU usage.
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# mem_util = 65.0 # e.g., 65% memory usage.
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# request_rate = 0.8 # e.g., normalized value for high load.
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# network_latency = 120 # e.g., 120ms average latency.
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# user_demand = 0.9 # e.g., high user demand.
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# print(recommend_scaling(cpu_util, mem_util, request_rate, network_latency, user_demand))

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