Refactor: group smart recommendations by type and remove redundant View Details button

app/models/resource_models.py

@@ -115,6 +115,7 @@ class SmartRecommendation(BaseModel):
     implementation_steps: Optional[List[str]] = None
     kubectl_commands: Optional[List[str]] = None
     vpa_yaml: Optional[str] = None
+    workload_list: Optional[List[str]] = None  # List of workloads for grouped recommendations
 
 class QoSClassification(BaseModel):
     """QoS (Quality of Service) classification"""

app/services/smart_recommendations.py

@@ -63,7 +63,10 @@ class SmartRecommendationsService:
         categories: List[WorkloadCategory]
     ) -> List[SmartRecommendation]:
         """Generate smart recommendations based on workload analysis"""
-        recommendations = []
+        # Group workloads by recommendation type
+        vpa_workloads = []
+        resource_config_workloads = []
+        ratio_adjustment_workloads = []
         
         for category in categories:
             workload_pods = [p for p in pods if self._extract_workload_name(p.name) == category.workload_name and p.namespace == category.namespace]
@@ -71,17 +74,173 @@ class SmartRecommendationsService:
             if not workload_pods:
                 continue
             
-            # Generate recommendations based on category
+            # Categorize workloads by recommendation type
-            workload_recommendations = await self._generate_workload_recommendations(
+            if category.vpa_candidate:
-                category, workload_pods
+                vpa_workloads.append((category, workload_pods))
-            )
+            elif category.resource_config_status == "missing_requests":
-            recommendations.extend(workload_recommendations)
+                resource_config_workloads.append((category, workload_pods))
+            elif category.resource_config_status == "missing_limits":
+                resource_config_workloads.append((category, workload_pods))
+            elif category.resource_config_status == "suboptimal_ratio":
+                ratio_adjustment_workloads.append((category, workload_pods))
+        
+        # Generate grouped recommendations
+        recommendations = []
+        
+        # VPA Activation group
+        if vpa_workloads:
+            recommendations.append(self._create_grouped_vpa_recommendation(vpa_workloads))
+        
+        # Resource Config group
+        if resource_config_workloads:
+            recommendations.append(self._create_grouped_resource_config_recommendation(resource_config_workloads))
+        
+        # Ratio Adjustment group
+        if ratio_adjustment_workloads:
+            recommendations.append(self._create_grouped_ratio_adjustment_recommendation(ratio_adjustment_workloads))
         
         # Sort by priority
         recommendations.sort(key=lambda x: self._get_priority_score(x.priority), reverse=True)
         
         return recommendations
     
+    def _create_grouped_vpa_recommendation(self, vpa_workloads: List[tuple]) -> SmartRecommendation:
+        """Create grouped VPA activation recommendation"""
+        # Sort workloads by priority
+        vpa_workloads.sort(key=lambda x: self._get_priority_score(x[0].estimated_impact), reverse=True)
+        
+        # Get highest priority
+        highest_priority = vpa_workloads[0][0].estimated_impact
+        
+        # Create workload list
+        workload_list = []
+        for category, _ in vpa_workloads:
+            workload_list.append(f"{category.workload_name} ({category.namespace}) - {category.estimated_impact.upper()}")
+        
+        # Generate consolidated VPA YAML
+        vpa_yaml = self._generate_consolidated_vpa_yaml(vpa_workloads)
+        
+        return SmartRecommendation(
+            workload_name="Multiple Workloads",
+            namespace="Multiple",
+            recommendation_type="vpa_activation",
+            priority=highest_priority,
+            title="Activate VPA for Workloads",
+            description=f"Enable VPA for {len(vpa_workloads)} workloads to get automatic resource recommendations based on usage patterns.",
+            confidence_level=0.8,
+            estimated_impact=highest_priority,
+            implementation_steps=[
+                "Create VPA resources for all workloads",
+                "Set updateMode to 'Off' for recommendation-only mode",
+                "Monitor VPA recommendations for 24-48 hours",
+                "Apply recommended values when confident"
+            ],
+            kubectl_commands=[
+                "oc apply -f vpa-workloads-batch.yaml"
+            ],
+            vpa_yaml=vpa_yaml,
+            workload_list=workload_list
+        )
+    
+    def _create_grouped_resource_config_recommendation(self, resource_workloads: List[tuple]) -> SmartRecommendation:
+        """Create grouped resource configuration recommendation"""
+        # Sort workloads by priority
+        resource_workloads.sort(key=lambda x: self._get_priority_score(x[0].estimated_impact), reverse=True)
+        
+        # Get highest priority
+        highest_priority = resource_workloads[0][0].estimated_impact
+        
+        # Create workload list
+        workload_list = []
+        for category, _ in resource_workloads:
+            workload_list.append(f"{category.workload_name} ({category.namespace}) - {category.estimated_impact.upper()}")
+        
+        return SmartRecommendation(
+            workload_name="Multiple Workloads",
+            namespace="Multiple",
+            recommendation_type="resource_config",
+            priority=highest_priority,
+            title="Configure Resource Requests/Limits",
+            description=f"Define proper resource requests and limits for {len(resource_workloads)} workloads to ensure QoS and prevent resource conflicts.",
+            confidence_level=0.9,
+            estimated_impact=highest_priority,
+            implementation_steps=[
+                "Analyze current resource usage for all workloads",
+                "Set CPU requests based on P95 usage + 20% buffer",
+                "Set memory requests based on P95 usage + 20% buffer",
+                "Set limits with 3:1 ratio to requests",
+                "Update deployments with new resource configuration"
+            ],
+            kubectl_commands=[
+                "oc patch deployment <workload-name> -n <namespace> -p '{\"spec\":{\"template\":{\"spec\":{\"containers\":[{\"name\":\"<container-name>\",\"resources\":{\"requests\":{\"cpu\":\"200m\",\"memory\":\"512Mi\"},\"limits\":{\"cpu\":\"600m\",\"memory\":\"1536Mi\"}}}]}}}}'"
+            ],
+            workload_list=workload_list
+        )
+    
+    def _create_grouped_ratio_adjustment_recommendation(self, ratio_workloads: List[tuple]) -> SmartRecommendation:
+        """Create grouped ratio adjustment recommendation"""
+        # Sort workloads by priority
+        ratio_workloads.sort(key=lambda x: self._get_priority_score(x[0].estimated_impact), reverse=True)
+        
+        # Get highest priority
+        highest_priority = ratio_workloads[0][0].estimated_impact
+        
+        # Create workload list
+        workload_list = []
+        for category, _ in ratio_workloads:
+            workload_list.append(f"{category.workload_name} ({category.namespace}) - {category.estimated_impact.upper()}")
+        
+        return SmartRecommendation(
+            workload_name="Multiple Workloads",
+            namespace="Multiple",
+            recommendation_type="ratio_adjustment",
+            priority=highest_priority,
+            title="Optimize Resource Ratios",
+            description=f"Optimize CPU and memory limit:request ratios for {len(ratio_workloads)} workloads to follow best practices (3:1 ratio).",
+            confidence_level=0.8,
+            estimated_impact=highest_priority,
+            implementation_steps=[
+                "Analyze current resource ratios for all workloads",
+                "Adjust limits to maintain 3:1 ratio with requests",
+                "Test with updated ratios in staging environment",
+                "Apply changes to production"
+            ],
+            kubectl_commands=[
+                "oc patch deployment <workload-name> -n <namespace> -p '{\"spec\":{\"template\":{\"spec\":{\"containers\":[{\"name\":\"<container-name>\",\"resources\":{\"requests\":{\"cpu\":\"200m\",\"memory\":\"512Mi\"},\"limits\":{\"cpu\":\"600m\",\"memory\":\"1536Mi\"}}}]}}}}'"
+            ],
+            workload_list=workload_list
+        )
+    
+    def _generate_consolidated_vpa_yaml(self, vpa_workloads: List[tuple]) -> str:
+        """Generate consolidated VPA YAML for multiple workloads"""
+        yaml_parts = []
+        
+        for category, _ in vpa_workloads:
+            yaml_parts.append(f"""---
+apiVersion: autoscaling.k8s.io/v1
+kind: VerticalPodAutoscaler
+metadata:
+  name: {category.workload_name}-vpa
+  namespace: {category.namespace}
+spec:
+  targetRef:
+    apiVersion: apps/v1
+    kind: Deployment
+    name: {category.workload_name}
+  updatePolicy:
+    updateMode: "Off"  # Recommendation only
+  resourcePolicy:
+    containerPolicies:
+    - containerName: {category.workload_name}
+      maxAllowed:
+        cpu: 2
+        memory: 4Gi
+      minAllowed:
+        cpu: 100m
+        memory: 128Mi""")
+        
+        return "\n".join(yaml_parts)
+    
     def _group_pods_by_workload(self, pods: List[PodResource]) -> Dict[str, List[PodResource]]:
         """Group pods by workload (deployment) name"""
         workloads = {}

app/static/index.html

@@ -1569,6 +1569,9 @@
                         'low': '⚪'
                     }[rec.priority] || '⚪';
 
+                    // Check if this is a grouped recommendation
+                    const isGrouped = rec.workload_name === "Multiple Workloads" && rec.workload_list;
+                    
                     html += `
                         <div class="recommendation-card" data-priority="${rec.priority}" data-type="${rec.recommendation_type}" 
                              style="border: 1px solid #ddd; border-radius: 8px; margin-bottom: 1rem; overflow: hidden; background: white;">
@@ -1576,9 +1579,13 @@
                                 <div>
                                     <h3 style="margin: 0 0 0.5rem 0; color: #2c3e50;">${priorityIcon} ${rec.title}</h3>
                                     <p style="margin: 0; color: #7f8c8d; font-size: 0.9rem;">
-                                        <strong>Workload:</strong> ${rec.workload_name} | 
+                                        ${isGrouped ? 
-                                        <strong>Namespace:</strong> ${rec.namespace} | 
+                                            `<strong>Workloads:</strong> ${rec.workload_list.length} workloads | 
-                                        <strong>Type:</strong> ${rec.recommendation_type.replace('_', ' ').toUpperCase()}
+                                             <strong>Type:</strong> ${rec.recommendation_type.replace('_', ' ').toUpperCase()}` :
+                                            `<strong>Workload:</strong> ${rec.workload_name} | 
+                                             <strong>Namespace:</strong> ${rec.namespace} | 
+                                             <strong>Type:</strong> ${rec.recommendation_type.replace('_', ' ').toUpperCase()}`
+                                        }
                                     </p>
                                 </div>
                                 <div style="text-align: right;">
@@ -1591,6 +1598,15 @@
                             <div class="recommendation-body" style="padding: 1rem;">
                                 <p style="margin: 0 0 1rem 0; color: #2c3e50;">${rec.description}</p>
                                 
+                                ${isGrouped && rec.workload_list ? `
+                                    <div style="margin-bottom: 1rem;">
+                                        <h4 style="color: #2c3e50; margin-bottom: 0.5rem; font-size: 1rem;">Affected Workloads:</h4>
+                                        <ul style="margin: 0; padding-left: 1.5rem; color: #555;">
+                                            ${rec.workload_list.map(workload => `<li style="margin-bottom: 0.25rem;">${workload}</li>`).join('')}
+                                        </ul>
+                                    </div>
+                                ` : ''}
+                                
                                 ${rec.implementation_steps ? `
                                     <div style="margin-bottom: 1rem;">
                                         <h4 style="color: #2c3e50; margin-bottom: 0.5rem; font-size: 1rem;">Implementation Steps:</h4>
@@ -1610,14 +1626,10 @@
                                 ` : ''}
 
                                 <div style="display: flex; gap: 0.5rem; margin-top: 1rem;">
-                                    <button onclick="showRecommendationDetails(${index})" 
-                                            style="padding: 0.5rem 1rem; background: #3498db; color: white; border: none; border-radius: 4px; cursor: pointer; font-size: 0.9rem;">
-                                        📋 View Details
-                                    </button>
                                     ${rec.vpa_yaml ? `
                                         <button onclick="showVPAYaml(${index})" 
                                                 style="padding: 0.5rem 1rem; background: #9b59b6; color: white; border: none; border-radius: 4px; cursor: pointer; font-size: 0.9rem;">
-                                            📄 VPA YAML
+                                            📄 Generate VPA YAML
                                         </button>
                                     ` : ''}
                                 </div>
@@ -2036,62 +2048,6 @@
             loadSmartRecommendations();
         }
 
-        function showRecommendationDetails(index) {
-            const rec = window.currentRecommendations[index];
-            if (!rec) return;
-            
-            let modalContent = `
-                <div class="modal-header" style="background: #f8f9fa; color: #2c3e50; padding: 2rem; position: relative; border-bottom: 1px solid #dee2e6;">
-                    <h2 style="margin: 0; font-size: 1.5rem; font-weight: 600;">📋 Recommendation Details</h2>
-                    <span class="close" onclick="closeModal()">&times;</span>
-                </div>
-                <div class="modal-body" style="padding: 2rem; max-height: 70vh; overflow-y: auto;">
-                    <div style="margin-bottom: 2rem;">
-                        <h3 style="color: #2c3e50; margin-bottom: 1rem;">${rec.title}</h3>
-                        <div style="background: #f8f9fa; padding: 1rem; border-radius: 8px; margin-bottom: 1rem;">
-                            <p><strong>Workload:</strong> ${rec.workload_name}</p>
-                            <p><strong>Namespace:</strong> ${rec.namespace}</p>
-                            <p><strong>Type:</strong> ${rec.recommendation_type.replace('_', ' ').toUpperCase()}</p>
-                            <p><strong>Priority:</strong> <span style="background: ${getPriorityColor(rec.priority)}; color: white; padding: 0.25rem 0.5rem; border-radius: 4px; font-size: 0.8rem;">${rec.priority.toUpperCase()}</span></p>
-                            ${rec.confidence_level ? `<p><strong>Confidence:</strong> ${Math.round(rec.confidence_level * 100)}%</p>` : ''}
-                        </div>
-                        
-                        <h4 style="color: #2c3e50; margin-bottom: 1rem;">Description</h4>
-                        <p style="margin-bottom: 2rem; color: #555;">${rec.description}</p>
-                        
-                        ${rec.implementation_steps ? `
-                            <h4 style="color: #2c3e50; margin-bottom: 1rem;">Implementation Steps</h4>
-                            <ol style="margin-bottom: 2rem; padding-left: 1.5rem; color: #555;">
-                                ${rec.implementation_steps.map(step => `<li style="margin-bottom: 0.5rem;">${step}</li>`).join('')}
-                            </ol>
-                        ` : ''}
-
-                        ${rec.kubectl_commands && rec.kubectl_commands.length > 0 ? `
-                            <h4 style="color: #2c3e50; margin-bottom: 1rem;">OpenShift Commands</h4>
-                            <div style="background: #f8f9fa; border: 1px solid #dee2e6; border-radius: 4px; padding: 1rem; margin-bottom: 2rem; font-family: 'Courier New', monospace; font-size: 0.9rem;">
-                                ${rec.kubectl_commands.map(cmd => `<div style="margin-bottom: 0.5rem;">${cmd}</div>`).join('')}
-                            </div>
-                            <div style="background: #e3f2fd; border: 1px solid #2196f3; border-radius: 4px; padding: 1rem; margin-bottom: 2rem;">
-                                <p style="margin: 0; color: #1565c0; font-size: 0.9rem;">
-                                    <strong>💡 Note:</strong> To get the VPA YAML file, click the "📄 VPA YAML" button in the recommendation card.
-                                </p>
-                            </div>
-                        ` : ''}
-
-                        <div style="text-align: center; margin-top: 2rem;">
-                            <button onclick="copyRecommendationCommands(${index})" style="padding: 0.75rem 1.5rem; background: #28a745; color: white; border: none; border-radius: 4px; cursor: pointer; margin-right: 1rem;">
-                                📋 Copy Commands
-                            </button>
-                            <button onclick="closeModal()" style="padding: 0.75rem 1.5rem; background: #6c757d; color: white; border: none; border-radius: 4px; cursor: pointer;">
-                                Close
-                            </button>
-                        </div>
-                    </div>
-                </div>
-            `;
-            
-            showModal(modalContent);
-        }
 
         function showVPAYaml(index) {
             const rec = window.currentRecommendations[index];
@@ -2123,13 +2079,6 @@ ${rec.vpa_yaml}
             showModal(modalContent);
         }
 
-        function copyRecommendationCommands(index) {
-            const rec = window.currentRecommendations[index];
-            if (!rec || !rec.kubectl_commands) return;
-            
-            const commands = rec.kubectl_commands.join('\n');
-            copyToClipboard(commands);
-        }
 
         function copyVPAYaml(index) {
             const rec = window.currentRecommendations[index];