diff --git a/charts/kubezero-metrics/dashboards/kube-mixin/apiserver.json b/charts/kubezero-metrics/dashboards/kube-mixin/apiserver.json index 9830c36d..1c940dcb 100644 --- a/charts/kubezero-metrics/dashboards/kube-mixin/apiserver.json +++ b/charts/kubezero-metrics/dashboards/kube-mixin/apiserver.json @@ -968,7 +968,7 @@ "steppedLine": false, "targets": [ { - "expr": "sum(rate(workqueue_adds_total{job=\"kube-apiserver\", instance=~\"$instance\", cluster=\"$cluster\"}[5m])) by (instance, name)", + "expr": "sum(rate(workqueue_adds_total{job=\"apiserver\", instance=~\"$instance\", cluster=\"$cluster\"}[5m])) by (instance, name)", "format": "time_series", "intervalFactor": 2, "legendFormat": "{{instance}} {{name}}", @@ -1049,7 +1049,7 @@ "steppedLine": false, "targets": [ { - "expr": "sum(rate(workqueue_depth{job=\"kube-apiserver\", instance=~\"$instance\", cluster=\"$cluster\"}[5m])) by (instance, name)", + "expr": "sum(rate(workqueue_depth{job=\"apiserver\", instance=~\"$instance\", cluster=\"$cluster\"}[5m])) by (instance, name)", "format": "time_series", "intervalFactor": 2, "legendFormat": "{{instance}} {{name}}", @@ -1130,7 +1130,7 @@ "steppedLine": false, "targets": [ { - "expr": "histogram_quantile(0.99, sum(rate(workqueue_queue_duration_seconds_bucket{job=\"kube-apiserver\", instance=~\"$instance\", cluster=\"$cluster\"}[5m])) by (instance, name, le))", + "expr": "histogram_quantile(0.99, sum(rate(workqueue_queue_duration_seconds_bucket{job=\"apiserver\", instance=~\"$instance\", cluster=\"$cluster\"}[5m])) by (instance, name, le))", "format": "time_series", "intervalFactor": 2, "legendFormat": "{{instance}} {{name}}", @@ -1224,7 +1224,7 @@ "steppedLine": false, "targets": [ { - "expr": "process_resident_memory_bytes{job=\"kube-apiserver\",instance=~\"$instance\", cluster=\"$cluster\"}", + "expr": "process_resident_memory_bytes{job=\"apiserver\",instance=~\"$instance\", cluster=\"$cluster\"}", "format": "time_series", "intervalFactor": 2, "legendFormat": "{{instance}}", @@ -1305,7 +1305,7 @@ "steppedLine": false, "targets": [ { - "expr": "rate(process_cpu_seconds_total{job=\"kube-apiserver\",instance=~\"$instance\", cluster=\"$cluster\"}[5m])", + "expr": "rate(process_cpu_seconds_total{job=\"apiserver\",instance=~\"$instance\", cluster=\"$cluster\"}[5m])", "format": "time_series", "intervalFactor": 2, "legendFormat": "{{instance}}", @@ -1386,7 +1386,7 @@ "steppedLine": false, "targets": [ { - "expr": "go_goroutines{job=\"kube-apiserver\",instance=~\"$instance\", cluster=\"$cluster\"}", + "expr": "go_goroutines{job=\"apiserver\",instance=~\"$instance\", cluster=\"$cluster\"}", "format": "time_series", "intervalFactor": 2, "legendFormat": "{{instance}}", @@ -1490,7 +1490,7 @@ "multi": false, "name": "instance", "options": [ ], - "query": "label_values(apiserver_request_total{job=\"kube-apiserver\", cluster=\"$cluster\"}, instance)", + "query": "label_values(apiserver_request_total{job=\"apiserver\", cluster=\"$cluster\"}, instance)", "refresh": 2, "regex": "", "sort": 1, diff --git a/charts/kubezero-metrics/templates/grafana-dashboards-k8s.yaml b/charts/kubezero-metrics/templates/grafana-dashboards-k8s.yaml index e66a9bc2..b85c3345 100644 --- a/charts/kubezero-metrics/templates/grafana-dashboards-k8s.yaml +++ b/charts/kubezero-metrics/templates/grafana-dashboards-k8s.yaml @@ -16,7 +16,7 @@ binaryData: node.json.gz: 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 apiserver.json.gz: - H4sIAAAAAAAC/+2d62/bthbAv+evINQNSAa39StpXKD3Is2jK5C2WetuH9rCoCXa5iJLKknZ8TLfv/0eUg9Tr8RpndhJOGBtxJco8jx+OjxRL7cQsno96gWh4NZL9OVbLSph5HtIGdHKsOf5Agvqe7LwEoqg0KVcqCZwOVfNiEMF7rsESgfY5UQVDj0i3jpQ5IWuG5UwHIy6vu8KGkB5XRWOqEMOfU8w3+WZ/jTT16XeuTaxAHtEtf+i5hTNDMptGIl4cnpWd0TQp9MPaJsTNqE2QS6ZEBf5/b+JLeiE7CDsOcgXI8LQmAhGbY4cygMXzwiUe0iMKJRgPur7mDkIM4IGPkPUgz/HalGwi4KQBT4nHDq4s2dWLZmIgwXmfshsoj1FVEO4zWgg+69/mkNGnTN/sbmqcASXzdrieiqv21rBRbJ78fVMXseX83RstYHpONbYd+RaWGPMzh1/6i0mwWE3oaaxaCuoUNJkvfcFrMmiqZgFqlyQC2Gpwjn8GckEIwMQXjl5q1XnVlTmT0ulxHVxwDPymqlwCjU5gdOHi3pie0S6dEz8UOR2PBnZZ6+xfT5kfugVxl+0+RO7Iamuzk5BlT9pdjp2e8+qZYvZsI+3m60XNVjYTg216zVUf7bf2cm3e+K027iFLa30W+a+GVG2zpgPYjgiIbeyrYhNx1gtUStXkZH33/0pGmNvhgICI3oC+QMkDQ/hgqPtPgg6XGJHSf2UUQEKQD3UqoOIzzga4QlBfUI8qOdTwkAFeGjbhPMBrPhM9RpgLhDx/HA4+m92jpFGyFnENw89KrJNhjgckow6RMKLL5KNadTruRUcUy+pzFfxkT8t20wpyiMprb7rnOI+ydq+slbvQG2I2n7BQqI1mmfnv1DobIXSxuzOULCVbILdMnnN2lttHYKAesNupIaNqrqilGbXE1p7eKzkaSJXDgkfKZWu5ZtNklXPVMxryw3OsDdcYvBmdvBKTQApOAJlOPNh5XhRFCy5iqryXWzrwB15YMbBnhTadeWMShYezLQYUGlhLaus4gQ83Cf6jxp+t/5rrg3YwNK+qvzKrmqp3oHxu37rBmAC5Bhy7sVFFdGDWe+fH5RU+mnHJdc8dg7tfCE7BxEt0dQBdd1DaSnV/ksb2GqACWzswx/7HWkDG/sFGyiNR4UCyrvo40XDNcGaNjqtwkC6vlfqqGIlGDMce8WtEpgNiVhiF8hFoOaEAyrRgbBebEZf4gmmLu5Tl4pZq+5cQl3/1VcLu+5Xq4ZsN+Sg91DwS/zjV2te3KmFrRTg1XpwC0p4sVliQ06wLdQaNQtNXDIknnOSjlccBKRTkaJ1sKxUpGaRl6xgAg8H2jqgbViJHfQf1Ok8q9fzwi9SKL3M7yfwlHP9jsZYwsH+ubAFOOdVlKHR1W8/PwPVYjn18+U8rVc31LzE1t1I+VSn97ExxZPhop/2/BkOwi7F/DAhlZwP6mNW6ucsia+nxBuKkbKqhTpS1W3lZBLaI0QYA4Duhw4oIgK4dslAINf3z2F3EQZiCRmYkU6n/ivSVQ0NQwxWVBDC89xBlXnJPZgsfcOwQ6MXlvoN/HjWGkYKVhRe2Iuhd8C7+VczvQnsaXmNHTIWTaysFjxhVQ31KmoYHY5AAZyqucS2U+JNvgY6/UUdJR15h6m0V+Aq860kmF+rwNLK85Kbq4ppfOvGMoRUYICCl0zgEw/LOT+QvaVchHL43WJduTLAbjkAxMonDFw/Z4EYCQguBY7Isn8AJwEiR0qeCJytTaq0M3bP+9lCAS86pZMEdxMExDmNXHex/sbeDxAM/Ya2V+IE0dNIreG/nbt0iMreROZm5b4xt5dy6icRvhUEQdZ9GtGBKK+MneqxnOzryDauwqfmVd1nouQ9SqlxL3Gz1HPohDohzjiycpesgk7ZmV3gC8qL8+qH9nkkeyU2JoleyEXKQ1/8tlHSq9qkpXZJhdHKH2GGL5Z5k6ryb0u+8kYiKd9BS59BVvrD15gXXvg0R1DaLfIEpVXautzove4hPaquv1v50lRryw13XPoWTA2O8aWk+qM/zQRg0/l0Y2XOhrhSFT9Kg4kwgpWtTwB2tFcMyjFovaVto4m3bWy8DTta0O307adu7c1x10TaVhdp2zWRNhNpu5eRtpaJtP1spE3a18cVavsoPUox3maibI8oylaOHZWsAWCAOAG77SAH3MaIoFS/OJJvl/0ZssG633Ysbc/E0kws7fZiaVdbGaXI8i7Pm8+ePadFg2InDvHJ7t7BXvu1dSM6Wwzfum74k+bhYf3wR4dvXzd8q/mifdT50eF3rxv+uN48abdvQDrXRjRbpRHNgkyvPKDJw7G0fNvS9O1EfwFuRPb3ZYFAekpfXzIsyO54Kfy408jm5aUy4Wg+3/zApkKYT6dv0VP0MXZXJqC5loDmQh5BygN+b6OV9+Y5ykOR9589lwl5aRgqUycZESHziIOmVMQnwdB89+Jip4JDV4WhLwyGGgzdpCPd1rqOdBMCSqjn5yhIdn31v68WIGQ1E6HnaLV33Qz2SuZ+3/hLnTEb+lo3fa3pGLV+CwC2+Y/yUBksYisu8+hkjK/TAayKd4O60a+qSJspU+sUlf2rqAyjIZ0QL7Vgtwxf+wa+DHwZ+JLnqBGs9L6HWCloCfY4YZR00otV++WIcuGDYxynvTbuIOwew9BRvNwGh9aMQw8hEMVNPpzJhzP5cLngoPo9Uy06ePYBOPTsM/x/0D38/d+j49Pj7rHJjltddlzHZMeZ7DiTHfc4s+OUtX1c6XF/KQdj8uNMflwBQ5Zkj03JlsuNZEJlJlRm0uVMutx9Tpe7mkdMvpx7FdOYhDmTMGcS5h5gwtzNuXSt6XONhuFSw6XmCHd1+XMJFt1xAt1m0di9OjTWicyk0JkUOpNC92hS6KTVVCl0FZh2x/l0jaahMUNjhsZWnlC3OWdn9xmOTEqdSakzKXUmpe7qlLoNJMSVc1rrAXNaaZUBtQ0Htb01hs22ZShqe+qzcwAzcN/YcXgUpLr825f4dR72ydMU4CSHUQ+m6NkqQvZLclEJaF92x992dlSYLGlbQ9Ib33FcK7n5fI4uL+X97wXBwb6gP+TGoAMHHAfslQG4NQOcf7endLcR19rcR7jv8ayV00rb0IqhFUMrFbTikECMDKhsFKgcyT0xlLLuMNNIrt4955RNfghDKjlS2f0RUilRh2VApaTbz3JK2RHXrR5+Xfm7hAZSfg5Scqexd0gpxYOsbfkvLNVQCb7EEJM7C+tF3ue2saaGXLJj2OZGbHMK++fZM0M35hDNHKKZQ7THC3vmXxAwUamNAr72ungvYL78BorM+YbZe6I3JmOfzXr9mSC8iuFuhnDrYrTNR7N3aq0Njq0Zx5SsPwAk2/DnMCGnHIWYD8gbCjEUEn1tS5DtBEXsIExjSVem8vxAJMmwSBWLHJ59RiGX0mxwxJx9mbOvxwQi5mPqBkQMiCg/4/eGPvNDITfQhD9uFznepCttmOOxMcdtnUpt9nM85JOprfgJLG6PyBj/SRiPZhklAYOtnkW3cjA7VwOBeR4upFTZWeYRGcNKxxJkHLhY/qJ8qnXgKbnQZHshDRpkZBAu+b6pQwY4dMs+sarXlhGhNYo4QzMuFTKVfkBaQzmt1lffCshbU+t7SNgsDscXkU8abmmHsxIKpUOS/2Jzui/a7bdyj6MtGHbd5PvjucfQllJfhyUANVkrzVuB2QV/6JCDsm8lpwuZ/OK1PtYYdoSW9ElWuaTLdUusbteLrOh2xRduUle+U74Nzeu2IXZG+naBsKu15n8kM7GytYUpy7LyxvEmR8+kVYScdKOBdD69652vV+181ptVadB1e54gzqo3vTJjqRTrFolMD0NGthKnNI8MLx0vPpG++G67P33aSJgo+SR75AEW3QIKNMQWneMl6SU8q4OJtbsQIKtR1y5a+kVjvPh5V/u5oV+06nrNgtyspvZzw4ns4bfkGSSBa9Jz7V30gff0gfW7NNv6xeIb/tYLR59vMpfM8v3jq5cZ63P3MPaSiY8+OHuLIqmMKkL19m7VO8Tex7hBOp09Z28wsJ29/caLfh8PBm2n3+hHjSepP65vzf8P1OdmvlGiAAA= + 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 cluster-total.json.gz: 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 controller-manager.json.gz: diff --git a/charts/kubezero-metrics/update.sh b/charts/kubezero-metrics/update.sh index d3dde446..fcbc7d9e 100755 --- a/charts/kubezero-metrics/update.sh +++ b/charts/kubezero-metrics/update.sh @@ -12,6 +12,10 @@ patch -p0 -i zdt.patch --no-backup-if-mismatch # Create ZDT dashboard configmap cd dashboards ./build.sh + +# Patch for the apiserver dashboard +patch -p1 -i ../zdt-apiserver-dashboard.patch --no-backup-if-mismatch + ../sync_grafana_dashboards.py metrics-dashboards.yaml ../templates/grafana-dashboards-metrics.yaml ../sync_grafana_dashboards.py k8s-dashboards.yaml ../templates/grafana-dashboards-k8s.yaml ../sync_grafana_dashboards.py zdt-dashboards.yaml ../templates/grafana-dashboards-zdt.yaml diff --git a/charts/kubezero-metrics/zdt-apiserver-dashboard.patch b/charts/kubezero-metrics/zdt-apiserver-dashboard.patch new file mode 100644 index 00000000..4b6adfd1 --- /dev/null +++ b/charts/kubezero-metrics/zdt-apiserver-dashboard.patch @@ -0,0 +1,67 @@ +diff --git a/kube-mixin/apiserver.json b/kube-mixin/apiserver.json +index 9830c36..1c940dc 100644 +--- a/kube-mixin/apiserver.json ++++ b/kube-mixin/apiserver.json +@@ -968,7 +968,7 @@ + "steppedLine": false, + "targets": [ + { +- "expr": "sum(rate(workqueue_adds_total{job=\"kube-apiserver\", instance=~\"$instance\", cluster=\"$cluster\"}[5m])) by (instance, name)", ++ "expr": "sum(rate(workqueue_adds_total{job=\"apiserver\", instance=~\"$instance\", cluster=\"$cluster\"}[5m])) by (instance, name)", + "format": "time_series", + "intervalFactor": 2, + "legendFormat": "{{instance}} {{name}}", +@@ -1049,7 +1049,7 @@ + "steppedLine": false, + "targets": [ + { +- "expr": "sum(rate(workqueue_depth{job=\"kube-apiserver\", instance=~\"$instance\", cluster=\"$cluster\"}[5m])) by (instance, name)", ++ "expr": "sum(rate(workqueue_depth{job=\"apiserver\", instance=~\"$instance\", cluster=\"$cluster\"}[5m])) by (instance, name)", + "format": "time_series", + "intervalFactor": 2, + "legendFormat": "{{instance}} {{name}}", +@@ -1130,7 +1130,7 @@ + "steppedLine": false, + "targets": [ + { +- "expr": "histogram_quantile(0.99, sum(rate(workqueue_queue_duration_seconds_bucket{job=\"kube-apiserver\", instance=~\"$instance\", cluster=\"$cluster\"}[5m])) by (instance, name, le))", ++ "expr": "histogram_quantile(0.99, sum(rate(workqueue_queue_duration_seconds_bucket{job=\"apiserver\", instance=~\"$instance\", cluster=\"$cluster\"}[5m])) by (instance, name, le))", + "format": "time_series", + "intervalFactor": 2, + "legendFormat": "{{instance}} {{name}}", +@@ -1224,7 +1224,7 @@ + "steppedLine": false, + "targets": [ + { +- "expr": "process_resident_memory_bytes{job=\"kube-apiserver\",instance=~\"$instance\", cluster=\"$cluster\"}", ++ "expr": "process_resident_memory_bytes{job=\"apiserver\",instance=~\"$instance\", cluster=\"$cluster\"}", + "format": "time_series", + "intervalFactor": 2, + "legendFormat": "{{instance}}", +@@ -1305,7 +1305,7 @@ + "steppedLine": false, + "targets": [ + { +- "expr": "rate(process_cpu_seconds_total{job=\"kube-apiserver\",instance=~\"$instance\", cluster=\"$cluster\"}[5m])", ++ "expr": "rate(process_cpu_seconds_total{job=\"apiserver\",instance=~\"$instance\", cluster=\"$cluster\"}[5m])", + "format": "time_series", + "intervalFactor": 2, + "legendFormat": "{{instance}}", +@@ -1386,7 +1386,7 @@ + "steppedLine": false, + "targets": [ + { +- "expr": "go_goroutines{job=\"kube-apiserver\",instance=~\"$instance\", cluster=\"$cluster\"}", ++ "expr": "go_goroutines{job=\"apiserver\",instance=~\"$instance\", cluster=\"$cluster\"}", + "format": "time_series", + "intervalFactor": 2, + "legendFormat": "{{instance}}", +@@ -1490,7 +1490,7 @@ + "multi": false, + "name": "instance", + "options": [ ], +- "query": "label_values(apiserver_request_total{job=\"kube-apiserver\", cluster=\"$cluster\"}, instance)", ++ "query": "label_values(apiserver_request_total{job=\"apiserver\", cluster=\"$cluster\"}, instance)", + "refresh": 2, + "regex": "", + "sort": 1,