|
193 | 193 | "targets": [
|
194 | 194 | {
|
195 | 195 | "exemplar": true,
|
196 |
| - "expr": "sum by (service) (rate(process_cpu_seconds_total{github_org=\"cobaltcore-dev\",github_repo=\"cortex\"}[1m]))", |
| 196 | + "expr": "sum by (service) (rate(process_cpu_seconds_total{github_org=\"cobaltcore-dev\",github_repo=\"cortex\"}[2m]))", |
197 | 197 | "format": "time_series",
|
198 | 198 | "instant": false,
|
199 | 199 | "interval": "",
|
| 200 | + "intervalFactor": 1, |
200 | 201 | "legendFormat": "{{service}}",
|
201 | 202 | "refId": "A"
|
202 | 203 | }
|
|
308 | 309 | "targets": [
|
309 | 310 | {
|
310 | 311 | "exemplar": false,
|
311 |
| - "expr": "sum(delta(cortex_vm_life_span_bucket{flavor_name=\"all\"}[1m]) / 2) by (le)", |
| 312 | + "expr": "sum(delta(cortex_vm_life_span_bucket{flavor_name=\"all\"}[2m]) / 2) by (le)", |
312 | 313 | "format": "heatmap",
|
313 | 314 | "instant": false,
|
314 | 315 | "interval": "",
|
|
384 | 385 | "targets": [
|
385 | 386 | {
|
386 | 387 | "exemplar": true,
|
387 |
| - "expr": "sum(delta(cortex_vm_time_until_migration_bucket{flavor_name=\"all\"}[1m]) / 2) by (le)", |
| 388 | + "expr": "sum(delta(cortex_vm_time_until_migration_bucket{flavor_name=\"all\"}[2m]) / 2) by (le)", |
388 | 389 | "format": "heatmap",
|
389 | 390 | "instant": false,
|
390 | 391 | "interval": "",
|
|
527 | 528 | "targets": [
|
528 | 529 | {
|
529 | 530 | "exemplar": true,
|
530 |
| - "expr": "(sum by(target_host) (delta(cortex_migrations_total{}[1m])))", |
| 531 | + "expr": "(sum by(target_host) (delta(cortex_migrations_total{}[2m])))", |
531 | 532 | "interval": "",
|
532 | 533 | "legendFormat": "{{target_host}}",
|
533 | 534 | "queryType": "randomWalk",
|
|
624 | 625 | "targets": [
|
625 | 626 | {
|
626 | 627 | "exemplar": true,
|
627 |
| - "expr": "(sum by(source_host) (delta(cortex_migrations_total{}[1m])))", |
| 628 | + "expr": "(sum by(source_host) (delta(cortex_migrations_total{}[2m])))", |
628 | 629 | "format": "time_series",
|
629 | 630 | "interval": "",
|
630 | 631 | "legendFormat": "{{source_host}}",
|
|
782 | 783 | "targets": [
|
783 | 784 | {
|
784 | 785 | "exemplar": true,
|
785 |
| - "expr": "sum by(type) (delta(cortex_migrations_total[1m]))", |
| 786 | + "expr": "sum by(type) (delta(cortex_migrations_total[2m]))", |
786 | 787 | "interval": "",
|
787 | 788 | "legendFormat": "Type: {{type}}",
|
788 | 789 | "queryType": "randomWalk",
|
|
793 | 794 | "timeFrom": null,
|
794 | 795 | "timeRegions": [],
|
795 | 796 | "timeShift": null,
|
796 |
| - "title": "Migrations by type (rate over 60min)", |
| 797 | + "title": "Migrations by type", |
797 | 798 | "tooltip": {
|
798 | 799 | "shared": true,
|
799 | 800 | "sort": 0,
|
|
895 | 896 | "targets": [
|
896 | 897 | {
|
897 | 898 | "exemplar": true,
|
898 |
| - "expr": "histogram_quantile(0.95, sum(rate(cortex_scheduler_pipeline_step_reorderings_levenshtein_bucket[60m])) by (le, step))", |
| 899 | + "expr": "histogram_quantile(0.95, sum(rate(cortex_scheduler_pipeline_step_reorderings_levenshtein_bucket[2m])) by (le, step))", |
899 | 900 | "interval": "",
|
900 | 901 | "legendFormat": "{{step}}",
|
901 | 902 | "refId": "A"
|
|
905 | 906 | "timeFrom": null,
|
906 | 907 | "timeRegions": [],
|
907 | 908 | "timeShift": null,
|
908 |
| - "title": "Resorted hosts by scheduler step (rate over 60min)", |
| 909 | + "title": "Resorted hosts by scheduler step (rate over 2min)", |
909 | 910 | "tooltip": {
|
910 | 911 | "shared": true,
|
911 | 912 | "sort": 0,
|
|
992 | 993 | "targets": [
|
993 | 994 | {
|
994 | 995 | "exemplar": true,
|
995 |
| - "expr": "sum by(vmware,rebuild,resize,live) (rate(cortex_scheduler_pipeline_requests_total{}[60m]))", |
| 996 | + "expr": "sum by(vmware,rebuild,resize,live) (rate(cortex_scheduler_pipeline_requests_total{}[2m]))", |
996 | 997 | "interval": "",
|
997 | 998 | "legendFormat": "Rebuild: {{rebuild}}, Resize: {{resize}}, Live: {{live}}, VMware: {{vmware}}",
|
998 | 999 | "refId": "A"
|
|
1002 | 1003 | "timeFrom": null,
|
1003 | 1004 | "timeRegions": [],
|
1004 | 1005 | "timeShift": null,
|
1005 |
| - "title": "Requests by type (rate over 60min)", |
| 1006 | + "title": "Requests by type (rate over 2min)", |
1006 | 1007 | "tooltip": {
|
1007 | 1008 | "shared": true,
|
1008 | 1009 | "sort": 0,
|
|
1090 | 1091 | "targets": [
|
1091 | 1092 | {
|
1092 | 1093 | "exemplar": true,
|
1093 |
| - "expr": "histogram_quantile(0.95, sum(rate(cortex_scheduler_pipeline_step_run_duration_seconds_bucket[1m])) by (le, step))", |
| 1094 | + "expr": "histogram_quantile(0.95, sum(rate(cortex_scheduler_pipeline_step_run_duration_seconds_bucket[2m])) by (le, step))", |
1094 | 1095 | "interval": "",
|
1095 | 1096 | "legendFormat": "{{step}}",
|
1096 | 1097 | "refId": "A"
|
|
1197 | 1198 | "targets": [
|
1198 | 1199 | {
|
1199 | 1200 | "exemplar": true,
|
1200 |
| - "expr": "sum(rate(cortex_scheduler_api_request_duration_seconds_count{status=~\"2.+\"}[1m])) by (method, path, status, error)", |
| 1201 | + "expr": "sum(rate(cortex_scheduler_api_request_duration_seconds_count{status=~\"2.+\"}[2m])) by (method, path, status, error)", |
1201 | 1202 | "interval": "",
|
1202 | 1203 | "legendFormat": "{{method}} {{path}} {{status}} {{error}}",
|
1203 | 1204 | "refId": "A"
|
|
1294 | 1295 | "targets": [
|
1295 | 1296 | {
|
1296 | 1297 | "exemplar": true,
|
1297 |
| - "expr": "sum(rate(cortex_scheduler_api_request_duration_seconds_count{status=~\"4.+|5.+\"}[1m])) by (method, path, status, error)", |
| 1298 | + "expr": "sum(rate(cortex_scheduler_api_request_duration_seconds_count{status=~\"4.+|5.+\"}[2m])) by (method, path, status, error)", |
1298 | 1299 | "instant": false,
|
1299 | 1300 | "interval": "",
|
1300 | 1301 | "legendFormat": "{{method}} {{path}} {{status}} {{error}}",
|
|
1409 | 1410 | "targets": [
|
1410 | 1411 | {
|
1411 | 1412 | "exemplar": true,
|
1412 |
| - "expr": "histogram_quantile(0.95, sum(rate(cortex_scheduler_api_request_duration_seconds_bucket{status=~\"2.+\"}[1m])) by (le, method, path, status, error))", |
| 1413 | + "expr": "histogram_quantile(0.95, sum(rate(cortex_scheduler_api_request_duration_seconds_bucket{status=~\"2.+\"}[2m])) by (le, method, path, status, error))", |
1413 | 1414 | "interval": "",
|
1414 | 1415 | "legendFormat": "{{method}} {{path}} {{status}} {{error}}",
|
1415 | 1416 | "refId": "A"
|
|
1521 | 1522 | "targets": [
|
1522 | 1523 | {
|
1523 | 1524 | "exemplar": true,
|
1524 |
| - "expr": "histogram_quantile(0.95, sum(rate(cortex_scheduler_api_request_duration_seconds_bucket{status=~\"4.+|5.+\"}[1m])) by (le, method, path, status, error))", |
| 1525 | + "expr": "histogram_quantile(0.95, sum(rate(cortex_scheduler_api_request_duration_seconds_bucket{status=~\"4.+|5.+\"}[2m])) by (le, method, path, status, error))", |
1525 | 1526 | "interval": "",
|
1526 | 1527 | "legendFormat": "{{method}} {{path}} {{status}} {{error}}",
|
1527 | 1528 | "refId": "A"
|
|
1638 | 1639 | "targets": [
|
1639 | 1640 | {
|
1640 | 1641 | "exemplar": true,
|
1641 |
| - "expr": "bottomk(1, min by (host, step) (rate(cortex_scheduler_pipeline_step_weight_modification[1m])) < 0) by (host)", |
| 1642 | + "expr": "bottomk(1, min by (host, step) (rate(cortex_scheduler_pipeline_step_weight_modification[2m])) < 0) by (host)", |
1642 | 1643 | "format": "time_series",
|
1643 | 1644 | "instant": false,
|
1644 | 1645 | "interval": "",
|
|
1708 | 1709 | "targets": [
|
1709 | 1710 | {
|
1710 | 1711 | "exemplar": true,
|
1711 |
| - "expr": "topk(1, max by (host, step) (rate(cortex_scheduler_pipeline_step_weight_modification[1m])) > 0) by (host)", |
| 1712 | + "expr": "topk(1, max by (host, step) (rate(cortex_scheduler_pipeline_step_weight_modification[2m])) > 0) by (host)", |
1712 | 1713 | "format": "time_series",
|
1713 | 1714 | "instant": false,
|
1714 | 1715 | "interval": "",
|
|
1785 | 1786 | "targets": [
|
1786 | 1787 | {
|
1787 | 1788 | "exemplar": true,
|
1788 |
| - "expr": "histogram_quantile(0.95, sum(rate(cortex_feature_pipeline_step_run_duration_seconds_bucket[1m])) by (le, step))", |
| 1789 | + "expr": "histogram_quantile(0.95, sum(rate(cortex_feature_pipeline_step_run_duration_seconds_bucket[2m])) by (le, step))", |
1789 | 1790 | "interval": "",
|
1790 | 1791 | "legendFormat": "{{step}}",
|
1791 | 1792 | "refId": "A"
|
|
1957 | 1958 | "targets": [
|
1958 | 1959 | {
|
1959 | 1960 | "exemplar": true,
|
1960 |
| - "expr": "histogram_quantile(0.95, sum(rate(cortex_sync_run_duration_seconds_bucket[1m])) by (le, datasource))", |
| 1961 | + "expr": "histogram_quantile(0.95, sum(rate(cortex_sync_run_duration_seconds_bucket[2m])) by (le, datasource))", |
1961 | 1962 | "interval": "",
|
1962 | 1963 | "legendFormat": "{{datasource}}",
|
1963 | 1964 | "refId": "A"
|
|
2055 | 2056 | "targets": [
|
2056 | 2057 | {
|
2057 | 2058 | "exemplar": true,
|
2058 |
| - "expr": "sum by (datasource) (increase(cortex_sync_objects{github_org=\"cobaltcore-dev\",github_repo=\"cortex\"}[1m])) / count by (datasource) (cortex_sync_objects{github_org=\"cobaltcore-dev\",github_repo=\"cortex\"})", |
| 2059 | + "expr": "sum by (datasource) (increase(cortex_sync_objects{github_org=\"cobaltcore-dev\",github_repo=\"cortex\"}[2m])) / count by (datasource) (cortex_sync_objects{github_org=\"cobaltcore-dev\",github_repo=\"cortex\"})", |
2059 | 2060 | "format": "time_series",
|
2060 | 2061 | "instant": false,
|
2061 | 2062 | "interval": "",
|
|
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