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提交 5d8fd5c6 编写于 作者: H huanggze 提交者： zryfish
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round cpu usage metrics 

Signed-off-by: Nhuanggze <loganhuang@yunify.com>
上级 d8117e56
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Showing with 10 addition and 10 deletion
pkg/models/metrics/metricsruleconst.go
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......@@ -378,7 +378,7 @@ var ComponentMetricsNames = []string{
var RulePromQLTmplMap = MetricMap{
//cluster
"cluster_cpu_utilisation": ":node_cpu_utilisation:avg1m",
"cluster_cpu_usage": `:node_cpu_utilisation:avg1m * sum(node:node_num_cpu:sum)`,
"cluster_cpu_usage": `round(:node_cpu_utilisation:avg1m * sum(node:node_num_cpu:sum), 0.001)`,
"cluster_cpu_total": "sum(node:node_num_cpu:sum)",
"cluster_memory_utilisation": ":node_memory_utilisation:",
"cluster_memory_available": "sum(node:node_memory_bytes_available:sum)",
......@@ -491,7 +491,7 @@ var RulePromQLTmplMap = MetricMap{
"node_pod_abnormal_count": `node:pod_abnormal:count$1`,
// without log node: unless on(node) kube_node_labels{label_role="log"}
"node_cpu_usage": `node:node_cpu_utilisation:avg1m$1 * node:node_num_cpu:sum$1`,
"node_cpu_usage": `round(node:node_cpu_utilisation:avg1m$1 * node:node_num_cpu:sum$1, 0.001)`,
"node_load1": `node:load1:ratio$1`,
"node_load5": `node:load5:ratio$1`,
......@@ -501,7 +501,7 @@ var RulePromQLTmplMap = MetricMap{
"node_pod_abnormal_ratio": `node:pod_abnormal:ratio$1`,
//namespace
"namespace_cpu_usage": `namespace:container_cpu_usage_seconds_total:sum_rate{namespace!="", namespace=~"$1"} * on (namespace) group_left(label_kubesphere_io_workspace)(kube_namespace_labels)`,
"namespace_cpu_usage": `round(namespace:container_cpu_usage_seconds_total:sum_rate{namespace!="", namespace=~"$1"} * on (namespace) group_left(label_kubesphere_io_workspace)(kube_namespace_labels), 0.001)`,
"namespace_memory_usage": `namespace:container_memory_usage_bytes:sum{namespace!="", namespace=~"$1"} * on (namespace) group_left(label_kubesphere_io_workspace)(kube_namespace_labels)`,
"namespace_memory_usage_wo_cache": `namespace:container_memory_usage_bytes_wo_cache:sum{namespace!="", namespace=~"$1"}* on (namespace) group_left(label_kubesphere_io_workspace)(kube_namespace_labels)`,
"namespace_net_bytes_transmitted": `sum by (namespace) (irate(container_network_transmit_bytes_total{namespace!="", namespace=~"$1", pod_name!="", ` + ExcludedVirtualNetworkInterfaces + `, job="kubelet"}[5m]))* on (namespace) group_left(label_kubesphere_io_workspace)(kube_namespace_labels)`,
......@@ -570,19 +570,19 @@ var RulePromQLTmplMap = MetricMap{
"namespace_resourcequota_used_ratio": `namespace:resourcequota_used:ratio{namespace!="", namespace=~"$1"}`,
// pod
"pod_cpu_usage": `sum(irate(container_cpu_usage_seconds_total{job="kubelet", namespace="$1", pod_name!="", pod_name="$2", image!=""}[5m])) by (namespace, pod_name)`,
"pod_cpu_usage": `round(sum(irate(container_cpu_usage_seconds_total{job="kubelet", namespace="$1", pod_name!="", pod_name="$2", image!=""}[5m])) by (namespace, pod_name), 0.001)`,
"pod_memory_usage": `sum(container_memory_usage_bytes{job="kubelet", namespace="$1", pod_name!="", pod_name="$2", image!=""}) by (namespace, pod_name)`,
"pod_memory_usage_wo_cache": `sum(container_memory_usage_bytes{job="kubelet", namespace="$1", pod_name!="", pod_name="$2", image!=""} - container_memory_cache{job="kubelet", namespace="$1", pod_name!="", pod_name="$2",image!=""}) by (namespace, pod_name)`,
"pod_net_bytes_transmitted": `sum by (namespace, pod_name) (irate(container_network_transmit_bytes_total{namespace="$1", pod_name!="", pod_name="$2", ` + ExcludedVirtualNetworkInterfaces + `, job="kubelet"}[5m]))`,
"pod_net_bytes_received": `sum by (namespace, pod_name) (irate(container_network_receive_bytes_total{namespace="$1", pod_name!="", pod_name="$2", ` + ExcludedVirtualNetworkInterfaces + `, job="kubelet"}[5m]))`,
"pod_cpu_usage_all": `sum(irate(container_cpu_usage_seconds_total{job="kubelet", namespace="$1", pod_name!="", pod_name=~"$2", image!=""}[5m])) by (namespace, pod_name)`,
"pod_cpu_usage_all": `round(sum(irate(container_cpu_usage_seconds_total{job="kubelet", namespace="$1", pod_name!="", pod_name=~"$2", image!=""}[5m])) by (namespace, pod_name), 0.001)`,
"pod_memory_usage_all": `sum(container_memory_usage_bytes{job="kubelet", namespace="$1", pod_name!="", pod_name=~"$2", image!=""}) by (namespace, pod_name)`,
"pod_memory_usage_wo_cache_all": `sum(container_memory_usage_bytes{job="kubelet", namespace="$1", pod_name!="", pod_name=~"$2", image!=""} - container_memory_cache{job="kubelet", namespace="$1", pod_name!="", pod_name=~"$2", image!=""}) by (namespace, pod_name)`,
"pod_net_bytes_transmitted_all": `sum by (namespace, pod_name) (irate(container_network_transmit_bytes_total{namespace="$1", pod_name!="", pod_name=~"$2", ` + ExcludedVirtualNetworkInterfaces + `, job="kubelet"}[5m]))`,
"pod_net_bytes_received_all": `sum by (namespace, pod_name) (irate(container_network_receive_bytes_total{namespace="$1", pod_name!="", pod_name=~"$2", ` + ExcludedVirtualNetworkInterfaces + `, job="kubelet"}[5m]))`,
"pod_cpu_usage_node": `sum by (node, pod_name) (irate(container_cpu_usage_seconds_total{job="kubelet",pod_name!="", pod_name=~"$2", image!=""}[5m]) * on (namespace, pod_name) group_left(node) label_join(node_namespace_pod:kube_pod_info:{node="$3"}, "pod_name", "", "pod", "_name"))`,
"pod_cpu_usage_node": `round(sum by (node, pod_name) (irate(container_cpu_usage_seconds_total{job="kubelet",pod_name!="", pod_name=~"$2", image!=""}[5m]) * on (namespace, pod_name) group_left(node) label_join(node_namespace_pod:kube_pod_info:{node="$3"}, "pod_name", "", "pod", "_name")), 0.001)`,
"pod_memory_usage_node": `sum by (node, pod_name) (container_memory_usage_bytes{job="kubelet",pod_name!="", pod_name=~"$2", image!=""} * on (namespace, pod_name) group_left(node) label_join(node_namespace_pod:kube_pod_info:{node="$3"}, "pod_name", "", "pod", "_name"))`,
"pod_memory_usage_wo_cache_node": `sum by (node, pod_name) ((container_memory_usage_bytes{job="kubelet",pod_name!="", pod_name=~"$2", image!=""} - container_memory_cache{job="kubelet",pod_name!="", pod_name=~"$2", image!=""}) * on (namespace, pod_name) group_left(node) label_join(node_namespace_pod:kube_pod_info:{node="$3"}, "pod_name", "", "pod", "_name"))`,
"pod_net_bytes_transmitted_node": `sum by (node, pod_name) (irate(container_network_transmit_bytes_total{pod_name!="", pod_name=~"$2", ` + ExcludedVirtualNetworkInterfaces + `, job="kubelet"}[5m]) * on (pod_name) group_left(node) label_join(node_namespace_pod:kube_pod_info:{node="$3"}, "pod_name", "", "pod", "_name"))`,
......@@ -590,7 +590,7 @@ var RulePromQLTmplMap = MetricMap{
// workload
// Join the "container_cpu_usage_seconds_total" metric with "kube_pod_owner" to calculate workload-level resource usage
"workload_pod_cpu_usage": `namespace:workload_cpu_usage:sum{namespace="$2", workload=~"$3"}`,
"workload_pod_cpu_usage": `round(namespace:workload_cpu_usage:sum{namespace="$2", workload=~"$3"}, 0.001)`,
"workload_pod_memory_usage": `namespace:workload_memory_usage:sum{namespace="$2", workload=~"$3"}`,
"workload_pod_memory_usage_wo_cache": `namespace:workload_memory_usage_wo_cache:sum{namespace="$2", workload=~"$3"}`,
"workload_pod_net_bytes_transmitted": `namespace:workload_net_bytes_transmitted:sum_irate{namespace="$2", workload=~"$3"}`,
......@@ -609,20 +609,20 @@ var RulePromQLTmplMap = MetricMap{
"workload_statefulset_unavailable_replicas_ratio": `namespace:statefulset_unavailable_replicas:ratio{namespace="$2", statefulset=~"$3"}`,
// container
"container_cpu_usage": `sum(irate(container_cpu_usage_seconds_total{namespace="$1", pod_name="$2", container_name!="POD", container_name=~"$3"}[5m])) by (namespace, pod_name, container_name)`,
"container_cpu_usage": `round(sum(irate(container_cpu_usage_seconds_total{namespace="$1", pod_name="$2", container_name!="POD", container_name=~"$3"}[5m])) by (namespace, pod_name, container_name), 0.001)`,
"container_memory_usage": `sum(container_memory_usage_bytes{namespace="$1", pod_name="$2", container_name!="POD", container_name=~"$3"}) by (namespace, pod_name, container_name)`,
"container_memory_usage_wo_cache": `container_memory_usage_bytes{namespace="$1", pod_name="$2", container_name!="POD", container_name=~"$3"} - ignoring(id, image, endpoint, instance, job, name, service) container_memory_cache{namespace="$1", pod_name="$2", container_name!="POD", container_name=~"$3"}`,
"container_net_bytes_transmitted": `sum(irate(container_network_transmit_bytes_total{job="kubelet", namespace="$1", pod_name="$2", container_name="POD", ` + ExcludedVirtualNetworkInterfaces + `}[5m])) by (namespace, pod_name, container_name)`,
"container_net_bytes_received": `sum(irate(container_network_receive_bytes_total{job="kubelet", namespace="$1", pod_name="$2", container_name="POD", ` + ExcludedVirtualNetworkInterfaces + `}[5m])) by (namespace, pod_name, container_name)`,
"container_cpu_usage_node": `sum by (node, pod_name, container_name) (irate(container_cpu_usage_seconds_total{job="kubelet", pod_name="$2", container_name!="POD", container_name!="", container_name=~"$3", image!=""}[5m]) * on (pod_name) group_left(node) label_join(node_namespace_pod:kube_pod_info:{node="$1"}, "pod_name", "", "pod", "_name"))`,
"container_cpu_usage_node": `round(sum by (node, pod_name, container_name) (irate(container_cpu_usage_seconds_total{job="kubelet", pod_name="$2", container_name!="POD", container_name!="", container_name=~"$3", image!=""}[5m]) * on (pod_name) group_left(node) label_join(node_namespace_pod:kube_pod_info:{node="$1"}, "pod_name", "", "pod", "_name")), 0.001)`,
"container_memory_usage_node": `sum by (node, pod_name, container_name) (container_memory_usage_bytes{job="kubelet", pod_name="$2", container_name!="POD", container_name!="", container_name=~"$3", image!=""} * on (pod_name) group_left(node) label_join(node_namespace_pod:kube_pod_info:{node="$1"}, "pod_name", "", "pod", "_name"))`,
"container_memory_usage_wo_cache_node": `sum by (node, pod_name, container_name) ((container_memory_usage_bytes{job="kubelet", pod_name="$2", container_name!="POD", container_name!="", container_name=~"$3", image!=""} - container_memory_cache{job="kubelet", pod_name="$2", container_name!="POD", container_name!="", container_name=~"$3", image!=""}) * on (pod_name) group_left(node) label_join(node_namespace_pod:kube_pod_info:{node="$1"}, "pod_name", "", "pod", "_name"))`,
"container_net_bytes_transmitted_node": `sum by (node, pod_name, container_name) (irate(container_network_transmit_bytes_total{job="kubelet", ` + ExcludedVirtualNetworkInterfaces + `, pod_name="$2", container_name="POD", container_name!="", image!=""}[5m]) * on (pod_name) group_left(node) label_join(node_namespace_pod:kube_pod_info:{node="$1"}, "pod_name", "", "pod", "_name"))`,
"container_net_bytes_received_node": `sum by (node, pod_name, container_name) (irate(container_network_receive_bytes_total{job="kubelet", ` + ExcludedVirtualNetworkInterfaces + `, pod_name="$2", container_name="POD", container_name!="", image!=""}[5m]) * on (pod_name) group_left(node) label_join(node_namespace_pod:kube_pod_info:{node="$1"}, "pod_name", "", "pod", "_name"))`,
// workspace
"workspace_cpu_usage": `sum(namespace:container_cpu_usage_seconds_total:sum_rate{namespace!="", namespace$1})`,
"workspace_cpu_usage": `round(sum(namespace:container_cpu_usage_seconds_total:sum_rate{namespace!="", namespace$1}), 0.001)`,
"workspace_memory_usage": `sum(namespace:container_memory_usage_bytes:sum{namespace!="", namespace$1})`,
"workspace_memory_usage_wo_cache": `sum(namespace:container_memory_usage_bytes_wo_cache:sum{namespace!="", namespace$1})`,
"workspace_net_bytes_transmitted": `sum(sum by (namespace) (irate(container_network_transmit_bytes_total{namespace!="", namespace$1, pod_name!="", ` + ExcludedVirtualNetworkInterfaces + `, job="kubelet"}[5m])))`,
......
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