Move Historical Analysis button to individual pod cards with pod-specific Prometheus queries
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@@ -449,6 +449,34 @@ async def get_namespace_historical_analysis(
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logger.error(f"Error getting historical analysis for namespace {namespace}: {e}")
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raise HTTPException(status_code=500, detail=str(e))
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@api_router.get("/namespace/{namespace}/pod/{pod_name}/historical-analysis")
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async def get_pod_historical_analysis(
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namespace: str,
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pod_name: str,
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time_range: str = "24h",
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prometheus_client=Depends(get_prometheus_client)
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):
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"""Get historical analysis for a specific pod"""
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try:
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historical_service = HistoricalAnalysisService()
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# Get historical analysis for the pod
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analysis = await historical_service.get_pod_historical_analysis(
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namespace, pod_name, time_range, prometheus_client
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)
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return {
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"namespace": namespace,
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"pod_name": pod_name,
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"time_range": time_range,
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"analysis": analysis,
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"timestamp": datetime.now().isoformat()
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}
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except Exception as e:
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logger.error(f"Error getting historical analysis for pod {pod_name} in namespace {namespace}: {e}")
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raise HTTPException(status_code=500, detail=str(e))
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@api_router.get("/health")
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async def health_check():
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"""API health check"""
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@@ -569,3 +569,140 @@ class HistoricalAnalysisService:
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'error': str(e),
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'recommendations': []
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}
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async def get_pod_historical_analysis(self, namespace: str, pod_name: str, time_range: str, prometheus_client):
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"""Get historical analysis for a specific pod"""
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try:
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logger.info(f"Getting historical analysis for pod: {pod_name} in namespace: {namespace}")
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# Query for CPU usage by pod
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cpu_query = f'''
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sum(rate(container_cpu_usage_seconds_total{{
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namespace="{namespace}",
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pod="{pod_name}",
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container!="POD",
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container!=""
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}}[{time_range}]))
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'''
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# Query for memory usage by pod
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memory_query = f'''
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sum(container_memory_working_set_bytes{{
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namespace="{namespace}",
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pod="{pod_name}",
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container!="POD",
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container!=""
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}})
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'''
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# Query for CPU requests by pod
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cpu_requests_query = f'''
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sum(kube_pod_container_resource_requests{{
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namespace="{namespace}",
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pod="{pod_name}",
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resource="cpu"
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}})
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'''
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# Query for memory requests by pod
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memory_requests_query = f'''
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sum(kube_pod_container_resource_requests{{
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namespace="{namespace}",
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pod="{pod_name}",
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resource="memory"
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}})
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'''
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# Query for container count by pod
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container_count_query = f'''
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count(container_memory_working_set_bytes{{
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namespace="{namespace}",
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pod="{pod_name}",
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container!="POD",
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container!=""
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}})
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'''
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# Execute queries
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cpu_usage = await self._query_prometheus(cpu_query,
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datetime.now() - timedelta(seconds=self.time_ranges[time_range]),
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datetime.now(), prometheus_client)
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memory_usage = await self._query_prometheus(memory_query,
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datetime.now() - timedelta(seconds=self.time_ranges[time_range]),
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datetime.now(), prometheus_client)
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cpu_requests = await self._query_prometheus(cpu_requests_query,
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datetime.now() - timedelta(seconds=self.time_ranges[time_range]),
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datetime.now(), prometheus_client)
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memory_requests = await self._query_prometheus(memory_requests_query,
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datetime.now() - timedelta(seconds=self.time_ranges[time_range]),
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datetime.now(), prometheus_client)
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container_count = await self._query_prometheus(container_count_query,
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datetime.now() - timedelta(seconds=self.time_ranges[time_range]),
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datetime.now(), prometheus_client)
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# Calculate utilization percentages
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cpu_utilization = 0
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memory_utilization = 0
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if cpu_usage and cpu_requests and cpu_requests[0][1] != '0':
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cpu_utilization = (float(cpu_usage[0][1]) / float(cpu_requests[0][1])) * 100
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if memory_usage and memory_requests and memory_requests[0][1] != '0':
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memory_utilization = (float(memory_usage[0][1]) / float(memory_requests[0][1])) * 100
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# Generate recommendations based on utilization
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recommendations = []
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if cpu_utilization > 80:
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recommendations.append({
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"type": "cpu_high_utilization",
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"severity": "warning",
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"message": f"High CPU utilization: {cpu_utilization:.1f}%",
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"recommendation": "Consider increasing CPU requests or optimizing application performance"
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})
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elif cpu_utilization < 20:
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recommendations.append({
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"type": "cpu_low_utilization",
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"severity": "info",
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"message": f"Low CPU utilization: {cpu_utilization:.1f}%",
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"recommendation": "Consider reducing CPU requests to optimize resource allocation"
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})
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if memory_utilization > 80:
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recommendations.append({
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"type": "memory_high_utilization",
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"severity": "warning",
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"message": f"High memory utilization: {memory_utilization:.1f}%",
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"recommendation": "Consider increasing memory requests or optimizing memory usage"
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})
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elif memory_utilization < 20:
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recommendations.append({
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"type": "memory_low_utilization",
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"severity": "info",
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"message": f"Low memory utilization: {memory_utilization:.1f}%",
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"recommendation": "Consider reducing memory requests to optimize resource allocation"
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})
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return {
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'namespace': namespace,
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'pod_name': pod_name,
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'time_range': time_range,
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'cpu_usage': float(cpu_usage[0][1]) if cpu_usage else 0,
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'memory_usage': float(memory_usage[0][1]) if memory_usage else 0,
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'cpu_requests': float(cpu_requests[0][1]) if cpu_requests else 0,
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'memory_requests': float(memory_requests[0][1]) if memory_requests else 0,
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'cpu_utilization': cpu_utilization,
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'memory_utilization': memory_utilization,
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'container_count': int(container_count[0][1]) if container_count else 0,
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'recommendations': recommendations
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}
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except Exception as e:
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logger.error(f"Error getting historical analysis for pod {pod_name} in namespace {namespace}: {e}")
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return {
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'namespace': namespace,
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'pod_name': pod_name,
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'time_range': time_range,
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'error': str(e),
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'recommendations': []
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}
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@@ -1042,7 +1042,6 @@
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<div class="accordion-stat">${totalValidations} analysis</div>
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<div class="accordion-stat" style="color: #dc3545;">${errorCount} errors</div>
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<div class="accordion-stat" style="color: #ffc107;">${warningCount} warnings</div>
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<button class="btn btn-secondary" style="padding: 0.25rem 0.5rem; font-size: 0.8rem; margin-left: 0.5rem;" onclick="event.stopPropagation(); loadNamespaceHistoricalAnalysis('${namespace.namespace}')">Historical Analysis</button>
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</div>
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<div class="accordion-arrow">▶</div>
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</div>
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@@ -1056,7 +1055,10 @@
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<div class="pod-item">
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<div class="pod-header">
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<div class="pod-name">${pod.pod_name}</div>
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<div style="display: flex; align-items: center; gap: 0.5rem;">
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<div class="pod-validations-count">${pod.validations.length} validations</div>
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<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>
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</div>
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</div>
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<div class="validation-list">
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`;
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@@ -1356,6 +1358,28 @@
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}
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// Historical Analysis Modal Functions
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async function loadPodHistoricalAnalysis(namespace, podName) {
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showLoading();
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try {
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const timeRange = '24h'; // Default time range
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const response = await fetch(`/api/v1/namespace/${namespace}/pod/${podName}/historical-analysis?time_range=${timeRange}`);
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if (!response.ok) {
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throw new Error(`HTTP ${response.status}: ${response.statusText}`);
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}
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const data = await response.json();
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displayPodHistoricalAnalysis(data);
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showHistoricalModal(`${namespace}/${podName}`);
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} catch (error) {
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showError('Error loading historical analysis: ' + error.message);
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} finally {
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hideLoading();
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}
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}
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async function loadNamespaceHistoricalAnalysis(namespace) {
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showLoading();
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@@ -1378,6 +1402,84 @@
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}
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}
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function displayPodHistoricalAnalysis(data) {
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const container = document.getElementById('historicalModalBody');
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if (data.analysis.error) {
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container.innerHTML = `
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<div class="error">
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<h3>Error loading historical data</h3>
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<p>${data.analysis.error}</p>
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</div>
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`;
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return;
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}
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const analysis = data.analysis;
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const recommendations = analysis.recommendations || [];
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let html = `
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<div class="historical-summary">
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<h3>Pod: ${analysis.pod_name}</h3>
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<p><strong>Namespace:</strong> ${analysis.namespace}</p>
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<p><strong>Time Range:</strong> ${analysis.time_range}</p>
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<p><strong>Containers:</strong> ${analysis.container_count}</p>
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</div>
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<div class="historical-stats">
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<div class="historical-stat">
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<h4>CPU Usage</h4>
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<div class="value">${analysis.cpu_usage.toFixed(3)} cores</div>
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</div>
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<div class="historical-stat">
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<h4>Memory Usage</h4>
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<div class="value">${(analysis.memory_usage / (1024*1024*1024)).toFixed(2)} GiB</div>
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</div>
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<div class="historical-stat">
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<h4>CPU Utilization</h4>
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<div class="value" style="color: ${analysis.cpu_utilization > 80 ? '#dc3545' : analysis.cpu_utilization < 20 ? '#28a745' : '#007bff'}">${analysis.cpu_utilization.toFixed(1)}%</div>
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</div>
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<div class="historical-stat">
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<h4>Memory Utilization</h4>
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<div class="value" style="color: ${analysis.memory_utilization > 80 ? '#dc3545' : analysis.memory_utilization < 20 ? '#28a745' : '#007bff'}">${analysis.memory_utilization.toFixed(1)}%</div>
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</div>
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</div>
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`;
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if (recommendations.length > 0) {
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html += `
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<div class="historical-summary">
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<h3>Recommendations</h3>
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`;
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recommendations.forEach(rec => {
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const severityClass = rec.severity;
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html += `
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<div class="historical-validation ${severityClass}">
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<div class="validation-header">
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<span class="severity-badge severity-${severityClass}">${severityClass}</span>
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${rec.message}
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</div>
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<div class="validation-recommendation">
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<strong>Recommendation:</strong> ${rec.recommendation}
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</div>
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</div>
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`;
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});
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html += `</div>`;
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} else {
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html += `
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<div class="historical-summary">
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<h3>Recommendations</h3>
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<p>No specific recommendations at this time. Resource utilization appears to be within normal ranges.</p>
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</div>
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`;
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}
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container.innerHTML = html;
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}
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function displayNamespaceHistoricalAnalysis(data) {
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const container = document.getElementById('historicalModalBody');
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