37a31a51a4
Refactor OPC metrics to use unpacking for CORE_LABELS in metrics.py - Updated the definition of prediction OPC writing metrics to utilize unpacking for CORE_LABELS, enhancing code clarity and maintainability.
42 lines
1.2 KiB
Python
42 lines
1.2 KiB
Python
from prometheus_client import Gauge, Counter, Histogram
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APP_UP = Gauge(
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"app_up",
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"Indicates if the application is running (1) or shutting down (0)",
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["pod_id"],
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)
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CORE_LABELS = ["pod_id", "model_name", "pipeline_name"]
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PREDICTIONS_WRITTEN_COUNT = Counter(
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"laborious_predictions_written_count",
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"Number of predictions written to the database table predictions",
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CORE_LABELS,
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)
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PREDICTION_CONFIDENCE_MONITOR = Gauge(
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"laborious_prediction_confidence_monitor",
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"Current confidence of each prediction",
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CORE_LABELS,
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)
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PREDICTION_RESPONSE_TIME_MONITOR = Histogram(
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"laborious_prediction_response_time_monitor",
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"Current response time of each prediction",
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CORE_LABELS,
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buckets=[0.01, 0.05, 0.1, 0.2, 0.5, 1.0, 2.0, 5.0, 10.0]
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)
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PREDICTION_OPC_WRITING_COUNT = Counter(
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"laborious_prediction_opc_writing_count",
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"Number of predictions written to the OPC server",
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[*CORE_LABELS, "opc_server_id"],
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)
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PREDICTION_OPC_WRITING_RESPONSE_TIME_MONITOR = Histogram(
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"laborious_prediction_opc_writing_response_time_monitor",
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"Current response time of each prediction written to the OPC server",
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[*CORE_LABELS, "opc_server_id"],
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buckets=[0.01, 0.05, 0.1, 0.2, 0.5, 1.0, 2.0, 5.0, 10.0]
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)
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