Update app.py

app.py

@@ -4,7 +4,7 @@ import numpy as np
 import gradio as gr
 import requests
 import pandas as pd
-import datetime  # ← THIS WAS MISSING
+import datetime
 from typing import List, Dict, Any
 import hashlib
 
@@ -67,25 +67,34 @@ class BusinessImpactCalculator:
         self.revenue_per_request = revenue_per_request
     
     def calculate_impact(self, event: ReliabilityEvent, duration_minutes: int = 5) -> Dict[str, Any]:
-        """Calculate business impact of an anomaly"""
+        """Enhanced business impact calculation"""
         
-        # Estimate throughput reduction (simplified)
-        normal_throughput = 1000  # This should come from historical baseline
-        throughput_reduction = max(0, 1 - (event.throughput / normal_throughput))
+        # More realistic impact calculation
+        base_revenue_per_minute = 100  # Base revenue per minute for the service
         
-        # Revenue impact
-        revenue_loss = (event.throughput * throughput_reduction * 
-                       self.revenue_per_request * (duration_minutes / 60))
+        # Calculate impact based on severity of anomalies
+        impact_multiplier = 1.0
         
-        # User impact
-        affected_users = event.user_impact or int(event.throughput * duration_minutes * 0.1)
+        if event.latency_p99 > 300:
+            impact_multiplier += 0.5  # High latency impact
+        if event.error_rate > 0.1:
+            impact_multiplier += 0.8  # High error rate impact
+        if event.cpu_util and event.cpu_util > 0.9:
+            impact_multiplier += 0.3  # Resource exhaustion impact
+        
+        revenue_loss = base_revenue_per_minute * impact_multiplier * (duration_minutes / 60)
+        
+        # More realistic user impact
+        base_users_affected = 1000  # Base user count
+        user_impact_multiplier = (event.error_rate * 10) + (max(0, event.latency_p99 - 100) / 500)
+        affected_users = int(base_users_affected * user_impact_multiplier)
         
         # Severity classification
-        if revenue_loss > 1000 or affected_users > 10000:
+        if revenue_loss > 500 or affected_users > 5000:
             severity = "CRITICAL"
         elif revenue_loss > 100 or affected_users > 1000:
             severity = "HIGH"
-        elif revenue_loss > 10 or affected_users > 100:
+        elif revenue_loss > 50 or affected_users > 500:
             severity = "MEDIUM"
         else:
             severity = "LOW"
@@ -94,7 +103,7 @@ class BusinessImpactCalculator:
             'revenue_loss_estimate': round(revenue_loss, 2),
             'affected_users_estimate': affected_users,
             'severity_level': severity,
-            'throughput_reduction_pct': round(throughput_reduction * 100, 1)
+            'throughput_reduction_pct': round(min(100, user_impact_multiplier * 100), 1)
         }
 
 business_calculator = BusinessImpactCalculator()
@@ -285,7 +294,7 @@ def submit_event(component, latency, error_rate, throughput, cpu_util, memory_ut
         
         if result["business_impact"]:
             impact = result["business_impact"]
-            output_msg += f"\n💰 Business Impact: ${impact['revenue_loss_estimate']} | 👥 {impact['affected_users_estimate']} users"
+            output_msg += f"\n💰 Business Impact: ${impact['revenue_loss_estimate']} | 👥 {impact['affected_users_estimate']} users | 🚨 {impact['severity_level']}"
         
         if result["healing_actions"]:
             actions = ", ".join(result["healing_actions"])