초기화

server/monitoring/metrics.py

@@ -0,0 +1,48 @@
+from dataclasses import dataclass, field
+from datetime import datetime
+import logging
+from typing import List
+
+logger = logging.getLogger("metrics")
+
+@dataclass
+class MessageMetrics:
+    topic: str
+    processing_time_ms: float
+    error: bool = False
+    error_msg: str = ""
+    timestamp: datetime = field(default_factory=datetime.now)
+
+message_metrics: List[MessageMetrics] = []
+
+def record_metric(topic: str, processing_time_ms: float, error: bool = False, error_msg: str = ""):
+    metric = MessageMetrics(
+        topic=topic,
+        processing_time_ms=processing_time_ms,
+        error=error,
+        error_msg=error_msg
+    )
+    message_metrics.append(metric)
+    if len(message_metrics) > 1000:
+        message_metrics.pop(0)
+    
+    if error:
+        logger.error(f"[METRIC ERROR] {topic}: {error_msg} ({processing_time_ms:.1f}ms)")
+    elif processing_time_ms > 100:
+        logger.warning(f"[METRIC SLOW] {topic}: {processing_time_ms:.1f}ms (>100ms)")
+
+def get_metrics_summary() -> dict:
+    if not message_metrics:
+        return {"message": "No metrics recorded yet"}
+    
+    total_count = len(message_metrics)
+    error_count = sum(1 for m in message_metrics if m.error)
+    avg_time = sum(m.processing_time_ms for m in message_metrics) / total_count
+    
+    return {
+        "total_messages": total_count,
+        "error_count": error_count,
+        "error_rate": error_count / total_count if total_count > 0 else 0.0,
+        "avg_processing_time_ms": round(avg_time, 2),
+        "last_update": message_metrics[-1].timestamp.isoformat()
+    }