Remove simulated data and enable real Prometheus metrics
This commit is contained in:
@@ -498,127 +498,123 @@ async def get_workload_historical_metrics(
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"""Get historical metrics for a specific workload with cluster percentages"""
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try:
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prometheus_client = PrometheusClient()
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await prometheus_client.initialize()
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# Get current usage using OpenShift-specific metrics
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cpu_usage_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_type=~".+"}}) by (workload, workload_type)'
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memory_usage_query = f'sum(container_memory_working_set_bytes{{job="kubelet", metrics_path="/metrics/cadvisor", cluster="", namespace="{namespace}", container!="", image!=""}} * on(namespace,pod) group_left(workload, workload_type) namespace_workload_pod:kube_pod_owner:relabel{{cluster="", namespace="{namespace}", workload_type=~".+"}}) by (workload, workload_type)'
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cpu_usage_data = await prometheus_client.query(cpu_usage_query)
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memory_usage_data = await prometheus_client.query(memory_usage_query)
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# Get resource requests and limits using OpenShift-specific metrics
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cpu_requests_query = f'sum(kube_pod_container_resource_requests{{job="kube-state-metrics", cluster="", namespace="{namespace}", resource="cpu"}} * on(namespace,pod) group_left(workload, workload_type) namespace_workload_pod:kube_pod_owner:relabel{{cluster="", namespace="{namespace}", workload_type=~".+"}}) by (workload, workload_type)'
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memory_requests_query = f'sum(kube_pod_container_resource_requests{{job="kube-state-metrics", cluster="", namespace="{namespace}", resource="memory"}} * on(namespace,pod) group_left(workload, workload_type) namespace_workload_pod:kube_pod_owner:relabel{{cluster="", namespace="{namespace}", workload_type=~".+"}}) by (workload, workload_type)'
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cpu_requests_data = await prometheus_client.query(cpu_requests_query)
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memory_requests_data = await prometheus_client.query(memory_requests_query)
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cpu_limits_query = f'sum(kube_pod_container_resource_limits{{job="kube-state-metrics", cluster="", namespace="{namespace}", resource="cpu"}} * on(namespace,pod) group_left(workload, workload_type) namespace_workload_pod:kube_pod_owner:relabel{{cluster="", namespace="{namespace}", workload_type=~".+"}}) by (workload, workload_type)'
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memory_limits_query = f'sum(kube_pod_container_resource_limits{{job="kube-state-metrics", cluster="", namespace="{namespace}", resource="memory"}} * on(namespace,pod) group_left(workload, workload_type) namespace_workload_pod:kube_pod_owner:relabel{{cluster="", namespace="{namespace}", workload_type=~".+"}}) by (workload, workload_type)'
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cpu_limits_data = await prometheus_client.query(cpu_limits_query)
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memory_limits_data = await prometheus_client.query(memory_limits_query)
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# Get cluster total resources
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# Get cluster total resources first
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cluster_cpu_query = 'sum(kube_node_status_allocatable{resource="cpu"})'
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cluster_memory_query = 'sum(kube_node_status_allocatable{resource="memory"})'
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cluster_cpu_data = await prometheus_client.query(cluster_cpu_query)
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cluster_memory_data = await prometheus_client.query(cluster_memory_query)
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# Extract values from OpenShift-specific queries
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# Extract cluster totals
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cluster_cpu_total = 0
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cluster_memory_total = 0
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if cluster_cpu_data.get("status") == "success" and cluster_cpu_data.get("data", {}).get("result"):
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for result in cluster_cpu_data["data"]["result"]:
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cluster_cpu_total += float(result["value"][1])
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if cluster_memory_data.get("status") == "success" and cluster_memory_data.get("data", {}).get("result"):
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for result in cluster_memory_data["data"]["result"]:
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cluster_memory_total += float(result["value"][1])
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# Get workload-specific metrics using simpler queries
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# CPU usage for specific pod
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cpu_usage_query = f'rate(container_cpu_usage_seconds_total{{namespace="{namespace}", pod=~".*{workload}.*"}}[5m])'
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memory_usage_query = f'container_memory_working_set_bytes{{namespace="{namespace}", pod=~".*{workload}.*", container!="", image!=""}}'
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# Resource requests and limits for specific pod
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cpu_requests_query = f'sum(kube_pod_container_resource_requests{{namespace="{namespace}", pod=~".*{workload}.*", resource="cpu"}})'
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memory_requests_query = f'sum(kube_pod_container_resource_requests{{namespace="{namespace}", pod=~".*{workload}.*", resource="memory"}})'
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cpu_limits_query = f'sum(kube_pod_container_resource_limits{{namespace="{namespace}", pod=~".*{workload}.*", resource="cpu"}})'
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memory_limits_query = f'sum(kube_pod_container_resource_limits{{namespace="{namespace}", pod=~".*{workload}.*", resource="memory"}})'
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# Execute queries
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cpu_usage_data = await prometheus_client.query(cpu_usage_query)
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memory_usage_data = await prometheus_client.query(memory_usage_query)
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cpu_requests_data = await prometheus_client.query(cpu_requests_query)
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memory_requests_data = await prometheus_client.query(memory_requests_query)
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cpu_limits_data = await prometheus_client.query(cpu_limits_query)
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memory_limits_data = await prometheus_client.query(memory_limits_query)
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# Extract values
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cpu_usage = 0
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memory_usage = 0
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cpu_requests = 0
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memory_requests = 0
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cpu_limits = 0
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memory_limits = 0
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cluster_cpu_total = 0
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cluster_memory_total = 0
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# Check if we got any data from Prometheus
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prometheus_available = False
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# Extract CPU usage from workload-specific query
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# Extract CPU usage
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if cpu_usage_data.get("status") == "success" and cpu_usage_data.get("data", {}).get("result"):
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for result in cpu_usage_data["data"]["result"]:
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if result.get("metric", {}).get("workload") == workload:
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cpu_usage = float(result["value"][1])
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break
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cpu_usage += float(result["value"][1])
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# Extract Memory usage from workload-specific query
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# Extract Memory usage
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if memory_usage_data.get("status") == "success" and memory_usage_data.get("data", {}).get("result"):
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for result in memory_usage_data["data"]["result"]:
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if result.get("metric", {}).get("workload") == workload:
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memory_usage = float(result["value"][1])
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break
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memory_usage += float(result["value"][1])
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# Extract CPU requests from workload-specific query
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# Extract CPU requests
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if cpu_requests_data.get("status") == "success" and cpu_requests_data.get("data", {}).get("result"):
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for result in cpu_requests_data["data"]["result"]:
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if result.get("metric", {}).get("workload") == workload:
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cpu_requests = float(result["value"][1])
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break
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cpu_requests += float(result["value"][1])
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# Extract Memory requests from workload-specific query
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# Extract Memory requests
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if memory_requests_data.get("status") == "success" and memory_requests_data.get("data", {}).get("result"):
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for result in memory_requests_data["data"]["result"]:
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if result.get("metric", {}).get("workload") == workload:
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memory_requests = float(result["value"][1])
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break
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memory_requests += float(result["value"][1])
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# Extract CPU limits from workload-specific query
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# Extract CPU limits
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if cpu_limits_data.get("status") == "success" and cpu_limits_data.get("data", {}).get("result"):
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for result in cpu_limits_data["data"]["result"]:
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if result.get("metric", {}).get("workload") == workload:
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cpu_limits = float(result["value"][1])
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break
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cpu_limits += float(result["value"][1])
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# Extract Memory limits from workload-specific query
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# Extract Memory limits
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if memory_limits_data.get("status") == "success" and memory_limits_data.get("data", {}).get("result"):
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for result in memory_limits_data["data"]["result"]:
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if result.get("metric", {}).get("workload") == workload:
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memory_limits = float(result["value"][1])
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break
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memory_limits += float(result["value"][1])
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if cluster_cpu_data.get("status") == "success" and cluster_cpu_data.get("data", {}).get("result"):
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cluster_cpu_total = float(cluster_cpu_data["data"]["result"][0]["value"][1])
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# Check if we have real data
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prometheus_available = cluster_cpu_total > 0 and cluster_memory_total > 0
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if cluster_memory_data.get("status") == "success" and cluster_memory_data.get("data", {}).get("result"):
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cluster_memory_total = float(cluster_memory_data["data"]["result"][0]["value"][1])
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# Check if Prometheus is available (any non-zero values)
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if cluster_cpu_total > 0 or cluster_memory_total > 0:
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prometheus_available = True
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# If Prometheus is not available, provide simulated data for demonstration
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# If no real data, return zeros with appropriate message
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if not prometheus_available:
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# Simulate cluster resources (typical OpenShift cluster)
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cluster_cpu_total = 24.0 # 6 nodes * 4 cores each
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cluster_memory_total = 96.0 * (1024**3) # 6 nodes * 16GB each
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# Simulate workload metrics based on namespace
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if namespace == "resource-governance":
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cpu_usage = 0.05
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memory_usage = 128 * (1024**2) # 128MB
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cpu_requests = 0.1
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memory_requests = 128 * (1024**2)
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cpu_limits = 0.5
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memory_limits = 512 * (1024**2)
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elif namespace == "shishika01":
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cpu_usage = 0.15
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memory_usage = 256 * (1024**2) # 256MB
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cpu_requests = 0.2
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memory_requests = 256 * (1024**2)
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cpu_limits = 1.0
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memory_limits = 1024 * (1024**2)
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else:
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cpu_usage = 0.08
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memory_usage = 192 * (1024**2) # 192MB
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cpu_requests = 0.15
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memory_requests = 192 * (1024**2)
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cpu_limits = 0.8
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memory_limits = 768 * (1024**2)
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return {
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"workload": workload,
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"namespace": namespace,
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"time_range": time_range,
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"prometheus_available": False,
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"data_source": "no_data",
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"message": "No metrics data available for this workload",
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"cluster_total": {
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"cpu_cores": 0,
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"memory_bytes": 0,
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"memory_gb": 0
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},
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"workload_metrics": {
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"cpu": {
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"usage_cores": 0,
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"usage_percent": 0,
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"requests_cores": 0,
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"requests_percent": 0,
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"limits_cores": 0,
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"limits_percent": 0
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},
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"memory": {
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"usage_bytes": 0,
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"usage_mb": 0,
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"usage_percent": 0,
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"requests_bytes": 0,
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"requests_mb": 0,
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"requests_percent": 0,
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"limits_bytes": 0,
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"limits_mb": 0,
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"limits_percent": 0
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}
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}
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}
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# Calculate percentages
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cpu_usage_percent = (cpu_usage / cluster_cpu_total * 100) if cluster_cpu_total > 0 else 0
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@@ -632,8 +628,8 @@ async def get_workload_historical_metrics(
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"workload": workload,
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"namespace": namespace,
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"time_range": time_range,
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"prometheus_available": prometheus_available,
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"data_source": "simulated" if not prometheus_available else "prometheus",
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"prometheus_available": True,
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"data_source": "prometheus",
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"cluster_total": {
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"cpu_cores": cluster_cpu_total,
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"memory_bytes": cluster_memory_total,
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@@ -1566,9 +1566,9 @@
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const workloadDataDiv = document.getElementById('workloadData');
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// Add data source indicator
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const dataSourceIndicator = data.data_source === 'simulated' ?
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'<div style="background: #fff3cd; border: 1px solid #ffeaa7; border-radius: 4px; padding: 10px; margin-bottom: 15px; color: #856404;"><strong>📊 Demo Mode:</strong> Showing simulated data for demonstration. Prometheus integration requires proper RBAC configuration.</div>' :
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'<div style="background: #d4edda; border: 1px solid #c3e6cb; border-radius: 4px; padding: 10px; margin-bottom: 15px; color: #155724;"><strong>✅ Live Data:</strong> Real metrics from Prometheus</div>';
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const dataSourceIndicator = data.data_source === 'prometheus' ?
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'<div style="background: #d4edda; border: 1px solid #c3e6cb; border-radius: 4px; padding: 10px; margin-bottom: 15px; color: #155724;"><strong>✅ Live Data:</strong> Real metrics from Prometheus</div>' :
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'<div style="background: #f8d7da; border: 1px solid #f5c6cb; border-radius: 4px; padding: 10px; margin-bottom: 15px; color: #721c24;"><strong>⚠️ No Data:</strong> No metrics available for this workload</div>';
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// Render cluster total resources
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clusterTotalDiv.innerHTML = dataSourceIndicator + `
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