Move Historical Analysis button to individual pod cards with pod-specific Prometheus queries

app/api/routes.py

@@ -449,6 +449,34 @@ async def get_namespace_historical_analysis(
         logger.error(f"Error getting historical analysis for namespace {namespace}: {e}")
         raise HTTPException(status_code=500, detail=str(e))
 
+@api_router.get("/namespace/{namespace}/pod/{pod_name}/historical-analysis")
+async def get_pod_historical_analysis(
+    namespace: str,
+    pod_name: str,
+    time_range: str = "24h",
+    prometheus_client=Depends(get_prometheus_client)
+):
+    """Get historical analysis for a specific pod"""
+    try:
+        historical_service = HistoricalAnalysisService()
+        
+        # Get historical analysis for the pod
+        analysis = await historical_service.get_pod_historical_analysis(
+            namespace, pod_name, time_range, prometheus_client
+        )
+        
+        return {
+            "namespace": namespace,
+            "pod_name": pod_name,
+            "time_range": time_range,
+            "analysis": analysis,
+            "timestamp": datetime.now().isoformat()
+        }
+        
+    except Exception as e:
+        logger.error(f"Error getting historical analysis for pod {pod_name} in namespace {namespace}: {e}")
+        raise HTTPException(status_code=500, detail=str(e))
+
 @api_router.get("/health")
 async def health_check():
     """API health check"""

app/services/historical_analysis.py

@@ -569,3 +569,140 @@ class HistoricalAnalysisService:
                 'error': str(e),
                 'recommendations': []
             }
+
+    async def get_pod_historical_analysis(self, namespace: str, pod_name: str, time_range: str, prometheus_client):
+        """Get historical analysis for a specific pod"""
+        try:
+            logger.info(f"Getting historical analysis for pod: {pod_name} in namespace: {namespace}")
+            
+            # Query for CPU usage by pod
+            cpu_query = f'''
+            sum(rate(container_cpu_usage_seconds_total{{
+                namespace="{namespace}",
+                pod="{pod_name}",
+                container!="POD",
+                container!=""
+            }}[{time_range}]))
+            '''
+            
+            # Query for memory usage by pod
+            memory_query = f'''
+            sum(container_memory_working_set_bytes{{
+                namespace="{namespace}",
+                pod="{pod_name}",
+                container!="POD",
+                container!=""
+            }})
+            '''
+            
+            # Query for CPU requests by pod
+            cpu_requests_query = f'''
+            sum(kube_pod_container_resource_requests{{
+                namespace="{namespace}",
+                pod="{pod_name}",
+                resource="cpu"
+            }})
+            '''
+            
+            # Query for memory requests by pod
+            memory_requests_query = f'''
+            sum(kube_pod_container_resource_requests{{
+                namespace="{namespace}",
+                pod="{pod_name}",
+                resource="memory"
+            }})
+            '''
+            
+            # Query for container count by pod
+            container_count_query = f'''
+            count(container_memory_working_set_bytes{{
+                namespace="{namespace}",
+                pod="{pod_name}",
+                container!="POD",
+                container!=""
+            }})
+            '''
+            
+            # Execute queries
+            cpu_usage = await self._query_prometheus(cpu_query, 
+                datetime.now() - timedelta(seconds=self.time_ranges[time_range]), 
+                datetime.now(), prometheus_client)
+            memory_usage = await self._query_prometheus(memory_query, 
+                datetime.now() - timedelta(seconds=self.time_ranges[time_range]), 
+                datetime.now(), prometheus_client)
+            cpu_requests = await self._query_prometheus(cpu_requests_query, 
+                datetime.now() - timedelta(seconds=self.time_ranges[time_range]), 
+                datetime.now(), prometheus_client)
+            memory_requests = await self._query_prometheus(memory_requests_query, 
+                datetime.now() - timedelta(seconds=self.time_ranges[time_range]), 
+                datetime.now(), prometheus_client)
+            container_count = await self._query_prometheus(container_count_query, 
+                datetime.now() - timedelta(seconds=self.time_ranges[time_range]), 
+                datetime.now(), prometheus_client)
+            
+            # Calculate utilization percentages
+            cpu_utilization = 0
+            memory_utilization = 0
+            
+            if cpu_usage and cpu_requests and cpu_requests[0][1] != '0':
+                cpu_utilization = (float(cpu_usage[0][1]) / float(cpu_requests[0][1])) * 100
+                
+            if memory_usage and memory_requests and memory_requests[0][1] != '0':
+                memory_utilization = (float(memory_usage[0][1]) / float(memory_requests[0][1])) * 100
+            
+            # Generate recommendations based on utilization
+            recommendations = []
+            
+            if cpu_utilization > 80:
+                recommendations.append({
+                    "type": "cpu_high_utilization",
+                    "severity": "warning",
+                    "message": f"High CPU utilization: {cpu_utilization:.1f}%",
+                    "recommendation": "Consider increasing CPU requests or optimizing application performance"
+                })
+            elif cpu_utilization < 20:
+                recommendations.append({
+                    "type": "cpu_low_utilization", 
+                    "severity": "info",
+                    "message": f"Low CPU utilization: {cpu_utilization:.1f}%",
+                    "recommendation": "Consider reducing CPU requests to optimize resource allocation"
+                })
+                
+            if memory_utilization > 80:
+                recommendations.append({
+                    "type": "memory_high_utilization",
+                    "severity": "warning", 
+                    "message": f"High memory utilization: {memory_utilization:.1f}%",
+                    "recommendation": "Consider increasing memory requests or optimizing memory usage"
+                })
+            elif memory_utilization < 20:
+                recommendations.append({
+                    "type": "memory_low_utilization",
+                    "severity": "info",
+                    "message": f"Low memory utilization: {memory_utilization:.1f}%", 
+                    "recommendation": "Consider reducing memory requests to optimize resource allocation"
+                })
+            
+            return {
+                'namespace': namespace,
+                'pod_name': pod_name,
+                'time_range': time_range,
+                'cpu_usage': float(cpu_usage[0][1]) if cpu_usage else 0,
+                'memory_usage': float(memory_usage[0][1]) if memory_usage else 0,
+                'cpu_requests': float(cpu_requests[0][1]) if cpu_requests else 0,
+                'memory_requests': float(memory_requests[0][1]) if memory_requests else 0,
+                'cpu_utilization': cpu_utilization,
+                'memory_utilization': memory_utilization,
+                'container_count': int(container_count[0][1]) if container_count else 0,
+                'recommendations': recommendations
+            }
+            
+        except Exception as e:
+            logger.error(f"Error getting historical analysis for pod {pod_name} in namespace {namespace}: {e}")
+            return {
+                'namespace': namespace,
+                'pod_name': pod_name,
+                'time_range': time_range,
+                'error': str(e),
+                'recommendations': []
+            }

app/static/index.html

@@ -1042,7 +1042,6 @@
                                 <div class="accordion-stat">${totalValidations} analysis</div>
                                 <div class="accordion-stat" style="color: #dc3545;">${errorCount} errors</div>
                                 <div class="accordion-stat" style="color: #ffc107;">${warningCount} warnings</div>
-                                <button class="btn btn-secondary" style="padding: 0.25rem 0.5rem; font-size: 0.8rem; margin-left: 0.5rem;" onclick="event.stopPropagation(); loadNamespaceHistoricalAnalysis('${namespace.namespace}')">Historical Analysis</button>
                             </div>
                             <div class="accordion-arrow">▶</div>
                         </div>
@@ -1056,7 +1055,10 @@
                             <div class="pod-item">
                                 <div class="pod-header">
                                     <div class="pod-name">${pod.pod_name}</div>
-                                    <div class="pod-validations-count">${pod.validations.length} validations</div>
+                                    <div style="display: flex; align-items: center; gap: 0.5rem;">
+                                        <div class="pod-validations-count">${pod.validations.length} validations</div>
+                                        <button class="btn btn-secondary" style="padding: 0.25rem 0.5rem; font-size: 0.8rem;" onclick="loadPodHistoricalAnalysis('${namespace.namespace}', '${pod.pod_name}')">Historical Analysis</button>
+                                    </div>
                                 </div>
                                 <div class="validation-list">
                         `;
@@ -1356,6 +1358,28 @@
         }
 
         // Historical Analysis Modal Functions
+        async function loadPodHistoricalAnalysis(namespace, podName) {
+            showLoading();
+            
+            try {
+                const timeRange = '24h'; // Default time range
+                const response = await fetch(`/api/v1/namespace/${namespace}/pod/${podName}/historical-analysis?time_range=${timeRange}`);
+                
+                if (!response.ok) {
+                    throw new Error(`HTTP ${response.status}: ${response.statusText}`);
+                }
+                
+                const data = await response.json();
+                displayPodHistoricalAnalysis(data);
+                showHistoricalModal(`${namespace}/${podName}`);
+                
+            } catch (error) {
+                showError('Error loading historical analysis: ' + error.message);
+            } finally {
+                hideLoading();
+            }
+        }
+
         async function loadNamespaceHistoricalAnalysis(namespace) {
             showLoading();
             
@@ -1378,6 +1402,84 @@
             }
         }
 
+        function displayPodHistoricalAnalysis(data) {
+            const container = document.getElementById('historicalModalBody');
+            
+            if (data.analysis.error) {
+                container.innerHTML = `
+                    <div class="error">
+                        <h3>Error loading historical data</h3>
+                        <p>${data.analysis.error}</p>
+                    </div>
+                `;
+                return;
+            }
+
+            const analysis = data.analysis;
+            const recommendations = analysis.recommendations || [];
+            
+            let html = `
+                <div class="historical-summary">
+                    <h3>Pod: ${analysis.pod_name}</h3>
+                    <p><strong>Namespace:</strong> ${analysis.namespace}</p>
+                    <p><strong>Time Range:</strong> ${analysis.time_range}</p>
+                    <p><strong>Containers:</strong> ${analysis.container_count}</p>
+                </div>
+                
+                <div class="historical-stats">
+                    <div class="historical-stat">
+                        <h4>CPU Usage</h4>
+                        <div class="value">${analysis.cpu_usage.toFixed(3)} cores</div>
+                    </div>
+                    <div class="historical-stat">
+                        <h4>Memory Usage</h4>
+                        <div class="value">${(analysis.memory_usage / (1024*1024*1024)).toFixed(2)} GiB</div>
+                    </div>
+                    <div class="historical-stat">
+                        <h4>CPU Utilization</h4>
+                        <div class="value" style="color: ${analysis.cpu_utilization > 80 ? '#dc3545' : analysis.cpu_utilization < 20 ? '#28a745' : '#007bff'}">${analysis.cpu_utilization.toFixed(1)}%</div>
+                    </div>
+                    <div class="historical-stat">
+                        <h4>Memory Utilization</h4>
+                        <div class="value" style="color: ${analysis.memory_utilization > 80 ? '#dc3545' : analysis.memory_utilization < 20 ? '#28a745' : '#007bff'}">${analysis.memory_utilization.toFixed(1)}%</div>
+                    </div>
+                </div>
+            `;
+
+            if (recommendations.length > 0) {
+                html += `
+                    <div class="historical-summary">
+                        <h3>Recommendations</h3>
+                `;
+                
+                recommendations.forEach(rec => {
+                    const severityClass = rec.severity;
+                    html += `
+                        <div class="historical-validation ${severityClass}">
+                            <div class="validation-header">
+                                <span class="severity-badge severity-${severityClass}">${severityClass}</span>
+                                ${rec.message}
+                            </div>
+                            <div class="validation-recommendation">
+                                <strong>Recommendation:</strong> ${rec.recommendation}
+                            </div>
+                        </div>
+                    `;
+                });
+                
+                html += `</div>`;
+            } else {
+                html += `
+                    <div class="historical-summary">
+                        <h3>Recommendations</h3>
+                        <p>No specific recommendations at this time. Resource utilization appears to be within normal ranges.</p>
+                    </div>
+                `;
+            }
+
+            container.innerHTML = html;
+        }
+
         function displayNamespaceHistoricalAnalysis(data) {
             const container = document.getElementById('historicalModalBody');