Implement OpenShift Console exact queries for CPU and Memory Usage

- Add get_workload_cpu_summary() and get_workload_memory_summary() methods
- Use exact OpenShift Console PromQL queries for data consistency
- Update historical analysis API endpoints to include real CPU/Memory data
- Document all OpenShift Console queries in AIAgents-Support.md
- Fix CPU Usage and Memory Usage columns showing N/A in Historical Analysis

app/api/routes.py

@@ -1419,15 +1419,33 @@ async def get_historical_analysis(
                 }
             workloads[workload_name]['pods'].append(pod)
         
-        # Convert to list and add basic info
+        # Convert to list and add basic info with real CPU/Memory data
         workload_list = []
+        historical_service = HistoricalAnalysisService()
+        
         for workload_name, workload_data in workloads.items():
+            # Get current CPU and Memory usage using OpenShift Console queries
+            try:
+                cpu_usage = await historical_service.get_workload_cpu_summary(workload_data['namespace'], workload_name)
+                memory_usage = await historical_service.get_workload_memory_summary(workload_data['namespace'], workload_name)
+                
+                # Format CPU usage (cores)
+                cpu_display = f"{cpu_usage:.3f} cores" if cpu_usage > 0 else "N/A"
+                
+                # Format memory usage (MB)
+                memory_display = f"{memory_usage / (1024 * 1024):.1f} MB" if memory_usage > 0 else "N/A"
+                
+            except Exception as e:
+                logger.warning(f"Error getting summary for {workload_name}: {e}")
+                cpu_display = "N/A"
+                memory_display = "N/A"
+            
             workload_list.append({
                 'name': workload_name,
                 'namespace': workload_data['namespace'],
                 'pod_count': len(workload_data['pods']),
-                'cpu_usage': 'N/A',  # Will be populated by Prometheus queries
+                'cpu_usage': cpu_display,
-                'memory_usage': 'N/A',  # Will be populated by Prometheus queries
+                'memory_usage': memory_display,
                 'last_updated': datetime.now().isoformat()
             })
         
@@ -1468,8 +1486,8 @@ async def get_workload_historical_details(
         cpu_data = await historical_service.get_cpu_usage_history(namespace, workload, time_range)
         memory_data = await historical_service.get_memory_usage_history(namespace, workload, time_range)
         
-        # Generate recommendations
+        # Generate recommendations and get workload summary
-        recommendations = await historical_service.generate_recommendations(namespace, workload, time_range)
+        recommendations, workload_summary = await historical_service.generate_recommendations(namespace, workload, time_range)
         
         return {
             "workload": workload,
@@ -1477,6 +1495,7 @@ async def get_workload_historical_details(
             "cpu_data": cpu_data,
             "memory_data": memory_data,
             "recommendations": recommendations,
+            "workload_summary": workload_summary,
             "timestamp": datetime.now().isoformat()
         }
         

app/services/historical_analysis.py

@@ -1448,6 +1448,82 @@ class HistoricalAnalysisService:
                 "error": str(e)
             }
 
+    async def get_workload_cpu_summary(self, namespace: str, workload: str) -> float:
+        """Get current CPU usage summary for a workload using OpenShift Console query"""
+        try:
+            # Use exact OpenShift Console query for CPU usage per pod
+            cpu_query = f'''
+            sum(
+                node_namespace_pod_container:container_cpu_usage_seconds_total:sum_irate{{
+                    cluster="", 
+                    namespace="{namespace}"
+                }}
+              * on(namespace,pod)
+                group_left(workload, workload_type) 
+                namespace_workload_pod:kube_pod_owner:relabel{{
+                    cluster="", 
+                    namespace="{namespace}", 
+                    workload="{workload}", 
+                    workload_type=~".+"
+                }}
+            ) by (pod)
+            '''
+            
+            # Query Prometheus for current value
+            data = await self._query_prometheus(cpu_query, 
+                datetime.utcnow() - timedelta(seconds=300),  # Last 5 minutes
+                datetime.utcnow())
+            
+            if data and len(data) > 0:
+                # Sum all pod values for the workload
+                total_cpu = sum(self._safe_float(point[1]) for point in data if point[1] != 'NaN')
+                return total_cpu
+            
+            return 0.0
+            
+        except Exception as e:
+            logger.error(f"Error getting CPU summary for {workload}: {e}")
+            return 0.0
+
+    async def get_workload_memory_summary(self, namespace: str, workload: str) -> float:
+        """Get current memory usage summary for a workload using OpenShift Console query"""
+        try:
+            # Use exact OpenShift Console query for memory usage per pod
+            memory_query = f'''
+            sum(
+                container_memory_working_set_bytes{{
+                    cluster="", 
+                    namespace="{namespace}", 
+                    container!="", 
+                    image!=""
+                }}
+              * on(namespace,pod)
+                group_left(workload, workload_type) 
+                namespace_workload_pod:kube_pod_owner:relabel{{
+                    cluster="", 
+                    namespace="{namespace}", 
+                    workload="{workload}", 
+                    workload_type=~".+"
+                }}
+            ) by (pod)
+            '''
+            
+            # Query Prometheus for current value
+            data = await self._query_prometheus(memory_query, 
+                datetime.utcnow() - timedelta(seconds=300),  # Last 5 minutes
+                datetime.utcnow())
+            
+            if data and len(data) > 0:
+                # Sum all pod values for the workload
+                total_memory = sum(self._safe_float(point[1]) for point in data if point[1] != 'NaN')
+                return total_memory
+            
+            return 0.0
+            
+        except Exception as e:
+            logger.error(f"Error getting memory summary for {workload}: {e}")
+            return 0.0
+
     async def generate_recommendations(self, namespace: str, workload: str, time_range: str = "24h") -> List[Dict[str, Any]]:
         """Generate recommendations based on historical data"""
         try:
@@ -1455,6 +1531,10 @@ class HistoricalAnalysisService:
             cpu_data = await self.get_cpu_usage_history(namespace, workload, time_range)
             memory_data = await self.get_memory_usage_history(namespace, workload, time_range)
             
+            # Get current summary values for the workload
+            current_cpu_usage = await self.get_workload_cpu_summary(namespace, workload)
+            current_memory_usage = await self.get_workload_memory_summary(namespace, workload)
+            
             recommendations = []
             
             # Analyze CPU data
@@ -1505,7 +1585,16 @@ class HistoricalAnalysisService:
                             "recommendation": "Increase memory limits to handle peak usage"
                         })
             
-            return recommendations
+            # Add workload summary data to recommendations
+            workload_summary = {
+                "workload": workload,
+                "namespace": namespace,
+                "cpu_usage": current_cpu_usage,
+                "memory_usage": current_memory_usage / (1024 * 1024),  # Convert bytes to MB
+                "time_range": time_range
+            }
+            
+            return recommendations, workload_summary
             
         except Exception as e:
             logger.error(f"Error generating recommendations: {str(e)}")
@@ -1514,4 +1603,4 @@ class HistoricalAnalysisService:
                 "severity": "error",
                 "message": f"Error generating recommendations: {str(e)}",
                 "recommendation": "Check Prometheus connectivity and workload configuration"
-            }]
+            }], None