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Integre con Prometheus

Prometheus Recopila métricas de objetivos configurados en intervalos determinados, evalúa expresiones de reglas, muestra los resultados y puede activar alertas cuando observa condiciones específicas.

Nuestra integración le permite configurar Cloud Manager para enviar datos métricos sobre su implementación a su instancia de Prometheus.

  • La integración dePrometheus está disponible en Clústeres gestionados porautomatización que usan el Agente MongoDB 12.0.15.7646 o posterior. El Agente MongoDB 12.0.15.7646 se lanza con Cloud 6 07Manager...

  • Tener una instancia de Prometheus en funcionamiento. Para configurarla, consulta su Guía de instalación.

  • (Opcional) Utilice Grafana para visualizar sus métricas de Prometheus.

Para integrar Cloud Manager con Prometheus:

1
  1. Si aún no se muestra, seleccione la organización que contiene su proyecto deseado en el menú Organizations de la barra de navegación.

  2. Si aún no aparece, selecciona el proyecto deseado en el menú Projects de la barra de navegación.

  3. En la barra lateral, haga clic en Project Settings.

    La página Configuración del proyecto se muestra.

2

En la barra lateral, haz clic en Integrations en la sección Settings.

La página de Integraciones del proyecto se muestra.

3
4

Las credenciales de autenticación de Prometheus están diseñadas específicamente para su uso con la integración de Prometheus en Cloud Manager. Cloud Manager utiliza estas credenciales únicamente para acceder al punto de descubrimiento de Prometheus y extraer métricas de Prometheus de los nodos de Cloud Manager. Se limitan estrictamente a estas funciones y no tienen permisos ni capacidades adicionales más allá del acceso y la recopilación de datos de monitorización.

Importante

Copie su nombre de usuario y contraseña en una ubicación segura. No puede acceder a la contraseña después de salir de esta pantalla.

5

Tip

El valor predeterminado, 0.0.0.0:9216, recopila métricas en el puerto 9216 en todos DireccionesIPv en la máquina local.4

6

Si habilita esta configuración, Cloud Manager garantiza que su instancia de Prometheus utilice https para extraer métricas.

Campos
Descripción

Ruta del archivo de clave del certificado TLS

PEM ruta del archivo que contiene el certificado y la clave necesarios para poner en marcha un punto final de raspado de Prometheus https.

Usted es responsable de lo siguiente:

  • Emisión y renovación de archivos de clave de certificado TLS.

  • Comprobación de si el punto final se inició correctamente en los registros del agente de automatización.

Contraseña del archivo de clave del certificado TLS

Obligatorio si el archivo de clave del certificado está cifrado.

7
Método de descubrimiento
Descripción

Este método requiere Prometheus v2.28 y versiones posteriores. Genera la parte scrape_config del archivo de configuración para detectar objetivos a través de un punto final HTTP.

Este método permite a Prometheus leer documentos YAML o JSON para configurar los objetivos desde los cuales extraer datos.

El usuario tiene la responsabilidad de proporcionar los objetivos realizando una solicitud a la Discovery API y almacenando los resultados en un archivo targets.json.

Para realizar la solicitud, sustituir el texto del marcador de posición en una de las siguientes pestañas o cree su propio script en otro lenguaje.

# Sets the `Authorization` header on every scrape
# request with the username and password from the
# previous step. The URL that Prometheus fetches the
# targets from.
# Replace the <group-id> with the project ID of your
# Cloud Manager instance.
curl --header 'Accept: application/json' \
--user <username>:<password> \
--request GET "https://cloud.mongodb.com/prometheus/v1.0/groups/{GROUP-ID}/discovery"

Si necesitas instalar la biblioteca requests, consulta su Guía de instalación.

import time, json, requests
# This script sets the `Authorization` header on every
# scrape request with the configured username and
# password. Then it tells Prometheus to fetch targets
# from the specified URL.
#
# Note: Replace the <username> and <password> with the
# values in the previous step, and <group-id> with the
# project ID of your Cloud Manager instance.
basic_auth_user="<username>"
basic_auth_password="<password>"
discovery_api_url="https://cloud.mongodb.com/prometheus/v1.0/groups/{GROUP-ID}/discovery"
# The script updates your targets.json file every
# minute, if it successfully retrieves targets.
#
# Note: Replace the <path-to-targets.json> with the
# path to your targets.json file.
starttime = time.time()
while True:
r = requests.get(discovery_api_url, auth=(basic_auth_user, basic_auth_password))
if r.status_code == 200:
with open('<path-to-targets.json>', 'w') as f:
json.dump(r.json(), f)
time.sleep(60.0 - ((time.time() - starttime) % 60.0))

Para aprender más sobre la API de Discovery, consultar Devuelva los últimos objetivos para Prometheus.

8
9
  1. Se debe copiar el fragmento generado en la sección scrape_configs del archivo de configuración y sustituir el texto del marcador de posición.

    Para un ejemplo del archivo de configuración en cualquiera de los métodos, consulta Configuraciones de ejemplo.

  2. Se debe reiniciar la instancia de Prometheus.

  3. En su instancia de Prometheus, hacer clic en Status en la barra de navegación superior y luego en Targets para ver las métricas de la implementación.

A continuación se muestran ejemplos del archivo de configuración cuando se utiliza el método de descubrimiento de servicio HTTP o de descubrimiento de servicio de archivos.

El archivo de configuración en ambos métodos contiene los siguientes campos:

Campo
Descripción

scrape_interval

Tiempo que indica con qué frecuencia se deben recopilar los objetivos. Esta configuración soporta un tiempo mínimo de 10s.

job_name

Etiqueta legible por humanos asignada a las métricas recopiladas.

metrics_path

Ruta de recurso HTTP que indica dónde obtener métricas de los destinos.

scheme

Su esquema de protocolo Prometheus configurado para solicitudes, http o https. Si configura https, debe especificar tlsPemPath.

basic_auth

Encabezado de autorización para usar en cada solicitud de extracción.

El método de descubrimiento de HTTP Service también contiene el campo http_sd_configs con los siguientes subcampos:

Campo
Descripción

url

URL desde la cual Prometheus obtiene los objetivos.

refresh_interval

Hora que indica cuándo volver a realizar una query al punto de conexión.

basic_auth

Credenciales que se utilizarán para autenticar en el servidor de la API.

global:
scrape_interval: 15s
scrape_configs:
- job_name: "CM-Testing-mongo-metrics"
scrape_interval: 10s
metrics_path: /metrics
scheme : https
basic_auth:
username: prom_user_61e6e34e93eac1632d39f457
password: V7hTyLfkjwiWQbv
http_sd_configs:
- url: https://cloud.mongodb.com/prometheus/v1.0/groups/61e6e34e93eac1632d39f457/discovery
refresh_interval: 60s
basic_auth:
username: prom_user_61e6e34e93eac1632d39f457
password: V7hTyLfkjwiWQbv

El método de descubrimiento de servicios de archivo también contiene el campo file_sd_configs con el siguiente subcampo:

Campo
Descripción

files

Lista que contiene los archivos de los que se extraerán los objetivos de extracción de métricas.

global:
scrape_interval: 15s
scrape_configs:
- job_name: "CM-Testing-mongo-metrics"
scrape_interval: 10s
metrics_path: /metrics
scheme : https
basic_auth:
username: prom_user_61e6e34e93eac1632d39f457
password: V7hTyLfkjwiWQbv
file_sd_configs:
- files:
- /usr/local/etc/targets.json

Para importar un tablero de muestra de Grafana:

1

En la Interfaz de Usuario de Grafana, hacer clic en el botón y luego hacer clic en Import.

2
3

1{
2 "__inputs": [
3 {
4 "name": "DS_PROMETHEUS",
5 "label": "prometheus",
6 "description": "",
7 "type": "datasource",
8 "pluginId": "prometheus",
9 "pluginName": "Prometheus"
10 }
11 ],
12 "__elements": [],
13 "__requires": [
14 {
15 "type": "grafana",
16 "id": "grafana",
17 "name": "Grafana",
18 "version": "8.5.6"
19 },
20 {
21 "type": "panel",
22 "id": "graph",
23 "name": "Graph (old)",
24 "version": ""
25 },
26 {
27 "type": "datasource",
28 "id": "prometheus",
29 "name": "Prometheus",
30 "version": "1.0.0"
31 },
32 {
33 "type": "panel",
34 "id": "table",
35 "name": "Table",
36 "version": ""
37 }
38 ],
39 "annotations": {
40 "list": [
41 {
42 "builtIn": 1,
43 "datasource": {
44 "type": "datasource",
45 "uid": "grafana"
46 },
47 "enable": true,
48 "hide": true,
49 "iconColor": "rgba(0, 211, 255, 1)",
50 "name": "Annotations & Alerts",
51 "target": {
52 "limit": 100,
53 "matchAny": false,
54 "tags": [],
55 "type": "dashboard"
56 },
57 "type": "dashboard"
58 }
59 ]
60 },
61 "editable": true,
62 "fiscalYearStartMonth": 0,
63 "graphTooltip": 0,
64 "id": null,
65 "iteration": 1657202032408,
66 "links": [],
67 "liveNow": false,
68 "panels": [
69 {
70 "collapsed": false,
71 "datasource": {
72 "type": "prometheus",
73 "uid": "000000010"
74 },
75 "gridPos": {
76 "h": 1,
77 "w": 24,
78 "x": 0,
79 "y": 0
80 },
81 "id": 10,
82 "panels": [],
83 "title": "Overview",
84 "type": "row"
85 },
86 {
87 "datasource": {
88 "type": "prometheus",
89 "uid": "${DS_PROMETHEUS}"
90 },
91 "fieldConfig": {
92 "defaults": {
93 "color": {
94 "mode": "thresholds"
95 },
96 "custom": {
97 "align": "auto",
98 "displayMode": "auto",
99 "inspect": false
100 },
101 "decimals": 2,
102 "displayName": "",
103 "mappings": [],
104 "thresholds": {
105 "mode": "absolute",
106 "steps": [
107 {
108 "color": "green",
109 "value": null
110 },
111 {
112 "color": "red",
113 "value": 80
114 }
115 ]
116 },
117 "unit": "short"
118 },
119 "overrides": [
120 {
121 "matcher": {
122 "id": "byName",
123 "options": "Value"
124 },
125 "properties": [
126 {
127 "id": "unit",
128 "value": "short"
129 },
130 {
131 "id": "decimals",
132 "value": 2
133 },
134 {
135 "id": "custom.align"
136 }
137 ]
138 }
139 ]
140 },
141 "gridPos": {
142 "h": 4,
143 "w": 24,
144 "x": 0,
145 "y": 1
146 },
147 "id": 41,
148 "options": {
149 "footer": {
150 "fields": "",
151 "reducer": [
152 "sum"
153 ],
154 "show": false
155 },
156 "showHeader": true
157 },
158 "pluginVersion": "8.5.6",
159 "targets": [
160 {
161 "datasource": {
162 "type": "prometheus",
163 "uid": "${DS_PROMETHEUS}"
164 },
165 "exemplar": false,
166 "expr": "label_replace( sum(mongodb_info{group_id=~\"$group_id\", cl_name=~\"$cl_name\", instance=~\"$host.*\"}) by (group_id, org_id, rs_nm, cl_name), \"hostname\", \"$1\", \"instance\", \"(.*)\")\n",
167 "format": "table",
168 "instant": true,
169 "interval": "",
170 "legendFormat": "",
171 "refId": "A"
172 }
173 ],
174 "title": "Group Metadata",
175 "transformations": [
176 {
177 "id": "organize",
178 "options": {
179 "excludeByName": {
180 "Time": true,
181 "Value #A": true,
182 "instance": true,
183 "rs_nm": false
184 },
185 "indexByName": {
186 "": 2,
187 "Time": 0,
188 "Value #A": 6,
189 "cl_name": 4,
190 "group_id": 3,
191 "org_id": 1,
192 "rs_nm": 5
193 },
194 "renameByName": {
195 "": "Group Name ",
196 "Time": "",
197 "cl_name": "Cluster Name",
198 "group_id": "Group Id",
199 "hostname": "Host",
200 "instance": "",
201 "org_id": "Org Id",
202 "process_port": "Port",
203 "replica_state": "ReplicaSet State",
204 "rs_nm": "ReplicaSet Name"
205 }
206 }
207 },
208 {
209 "id": "groupBy",
210 "options": {
211 "fields": {
212 "Cluster Name": {
213 "aggregations": [],
214 "operation": "groupby"
215 },
216 "Group Id": {
217 "aggregations": [],
218 "operation": "groupby"
219 },
220 "Group Name ": {
221 "aggregations": [],
222 "operation": "groupby"
223 },
224 "Host": {
225 "aggregations": [],
226 "operation": "groupby"
227 },
228 "Host ": {
229 "aggregations": [],
230 "operation": "groupby"
231 },
232 "Org Id": {
233 "aggregations": [],
234 "operation": "groupby"
235 },
236 "Port": {
237 "aggregations": [],
238 "operation": "groupby"
239 },
240 "Replica set state": {
241 "aggregations": [],
242 "operation": "groupby"
243 },
244 "ReplicaSet Name": {
245 "aggregations": [],
246 "operation": "groupby"
247 },
248 "ReplicaSet State": {
249 "aggregations": [],
250 "operation": "groupby"
251 },
252 "host ": {
253 "aggregations": [],
254 "operation": "groupby"
255 },
256 "hostname": {
257 "aggregations": [],
258 "operation": "groupby"
259 },
260 "instance": {
261 "aggregations": [],
262 "operation": "groupby"
263 },
264 "port": {
265 "aggregations": [],
266 "operation": "groupby"
267 },
268 "process_port": {
269 "aggregations": [],
270 "operation": "groupby"
271 },
272 "replica set": {
273 "aggregations": [],
274 "operation": "groupby"
275 },
276 "replica set state": {
277 "aggregations": [],
278 "operation": "groupby"
279 },
280 "replica_state": {
281 "aggregations": [],
282 "operation": "groupby"
283 },
284 "rs_nm": {
285 "aggregations": [],
286 "operation": "groupby"
287 }
288 }
289 }
290 },
291 {
292 "id": "merge",
293 "options": {
294 "reducers": []
295 }
296 }
297 ],
298 "type": "table"
299 },
300 {
301 "datasource": {
302 "type": "prometheus",
303 "uid": "${DS_PROMETHEUS}"
304 },
305 "fieldConfig": {
306 "defaults": {
307 "color": {
308 "mode": "thresholds"
309 },
310 "custom": {
311 "align": "auto",
312 "displayMode": "auto",
313 "inspect": false
314 },
315 "decimals": 0,
316 "displayName": "",
317 "mappings": [],
318 "thresholds": {
319 "mode": "absolute",
320 "steps": [
321 {
322 "color": "green",
323 "value": null
324 },
325 {
326 "color": "red",
327 "value": 80
328 }
329 ]
330 },
331 "unit": "none"
332 },
333 "overrides": []
334 },
335 "gridPos": {
336 "h": 6,
337 "w": 24,
338 "x": 0,
339 "y": 5
340 },
341 "id": 42,
342 "options": {
343 "footer": {
344 "fields": "",
345 "reducer": [
346 "sum"
347 ],
348 "show": false
349 },
350 "showHeader": true
351 },
352 "pluginVersion": "8.5.6",
353 "targets": [
354 {
355 "datasource": {
356 "type": "prometheus",
357 "uid": "${DS_PROMETHEUS}"
358 },
359 "exemplar": false,
360 "expr": "label_replace( sum(mongodb_info{group_id=~\"$group_id\", cl_name=~\"$cl_name\", instance=~\"$host.*\"}) by (instance, replica_state_name, process_port, rs_nm, process_type), \"hostname\", \"$1\", \"instance\", \"(.*):.*\")\n",
361 "format": "table",
362 "instant": true,
363 "interval": "",
364 "legendFormat": "",
365 "refId": "A"
366 }
367 ],
368 "title": "Cluster host list",
369 "transformations": [
370 {
371 "id": "organize",
372 "options": {
373 "excludeByName": {
374 "Time": true,
375 "Value #A": true,
376 "instance": false,
377 "rs_nm": false
378 },
379 "indexByName": {
380 "Time": 0,
381 "Value": 6,
382 "instance": 1,
383 "process_port": 2,
384 "process_type": 4,
385 "replica_state_name": 5,
386 "rs_nm": 3
387 },
388 "renameByName": {
389 "Time": "",
390 "Value": "",
391 "hostname": "Host",
392 "instance": "Hostname",
393 "process_port": "Port",
394 "process_type": "Process Type",
395 "replica_state": "ReplicaSet State",
396 "replica_state_name": "Replica State",
397 "rs_nm": "ReplicaSet Name"
398 }
399 }
400 },
401 {
402 "id": "groupBy",
403 "options": {
404 "fields": {
405 "Host": {
406 "aggregations": [],
407 "operation": "groupby"
408 },
409 "Host ": {
410 "aggregations": [],
411 "operation": "groupby"
412 },
413 "Hostname": {
414 "aggregations": [],
415 "operation": "groupby"
416 },
417 "Port": {
418 "aggregations": [],
419 "operation": "groupby"
420 },
421 "Process Type": {
422 "aggregations": [],
423 "operation": "groupby"
424 },
425 "Replica State": {
426 "aggregations": [],
427 "operation": "groupby"
428 },
429 "Replica set state": {
430 "aggregations": [],
431 "operation": "groupby"
432 },
433 "ReplicaSet Name": {
434 "aggregations": [],
435 "operation": "groupby"
436 },
437 "ReplicaSet State": {
438 "aggregations": [],
439 "operation": "groupby"
440 },
441 "host ": {
442 "aggregations": [],
443 "operation": "groupby"
444 },
445 "hostname": {
446 "aggregations": [],
447 "operation": "groupby"
448 },
449 "instance": {
450 "aggregations": [],
451 "operation": "groupby"
452 },
453 "port": {
454 "aggregations": [],
455 "operation": "groupby"
456 },
457 "process_port": {
458 "aggregations": [],
459 "operation": "groupby"
460 },
461 "replica set": {
462 "aggregations": [],
463 "operation": "groupby"
464 },
465 "replica set state": {
466 "aggregations": [],
467 "operation": "groupby"
468 },
469 "replica_state": {
470 "aggregations": [],
471 "operation": "groupby"
472 },
473 "rs_nm": {
474 "aggregations": [],
475 "operation": "groupby"
476 }
477 }
478 }
479 },
480 {
481 "id": "merge",
482 "options": {
483 "reducers": []
484 }
485 }
486 ],
487 "type": "table"
488 },
489 {
490 "collapsed": false,
491 "datasource": {
492 "type": "prometheus",
493 "uid": "000000010"
494 },
495 "gridPos": {
496 "h": 1,
497 "w": 24,
498 "x": 0,
499 "y": 11
500 },
501 "id": 8,
502 "panels": [],
503 "title": "Memory",
504 "type": "row"
505 },
506 {
507 "aliasColors": {},
508 "bars": false,
509 "dashLength": 10,
510 "dashes": false,
511 "datasource": {
512 "type": "prometheus",
513 "uid": "${DS_PROMETHEUS}"
514 },
515 "description": "The number of megabytes resident. MMAPv1: It is typical over time, on a dedicated database server, for this number to approach the amount of physical ram on the box. WiredTiger: In a standard deployment resident is the amount of memory used by the WiredTiger cache plus the memory dedicated to other in memory structures used by the mongod process. By default, mongod with WiredTiger reserves 50% of the total physical memory on the server for the cache and at steady state, WiredTiger tries to limit cache usage to 80% of that total. For example, if a server has 16GB of memory, WiredTiger will assume it can use 8GB for cache and at steady state should use about 6.5GB.",
516 "fieldConfig": {
517 "defaults": {
518 "links": [],
519 "unit": "decmbytes"
520 },
521 "overrides": []
522 },
523 "fill": 1,
524 "fillGradient": 0,
525 "gridPos": {
526 "h": 8,
527 "w": 12,
528 "x": 0,
529 "y": 12
530 },
531 "hiddenSeries": false,
532 "id": 2,
533 "legend": {
534 "avg": false,
535 "current": false,
536 "max": false,
537 "min": false,
538 "show": true,
539 "total": false,
540 "values": false
541 },
542 "lines": true,
543 "linewidth": 1,
544 "nullPointMode": "null",
545 "options": {
546 "alertThreshold": true,
547 "legend": {
548 "calcs": [],
549 "displayMode": "list",
550 "placement": "bottom"
551 },
552 "tooltip": {
553 "mode": "single"
554 }
555 },
556 "percentage": false,
557 "pluginVersion": "8.5.6",
558 "pointradius": 2,
559 "points": false,
560 "renderer": "flot",
561 "seriesOverrides": [],
562 "spaceLength": 10,
563 "stack": false,
564 "steppedLine": false,
565 "targets": [
566 {
567 "exemplar": true,
568 "expr": "label_replace(sum(mongodb_mem_resident{group_id=~\"$group_id\", cl_name=~\"$cl_name\", rs_nm=~\"$rs_nm\", instance=~\"$host.*\", process_port=~\"$process_port\"}) by (instance, process_port) , \"hostname\", \"$1\", \"instance\", \"(.*)\")",
569 "interval": "",
570 "legendFormat": "{{hostname}}:{{process_port}}",
571 "refId": "A",
572 "datasource": {
573 "type": "prometheus",
574 "uid": "${DS_PROMETHEUS}"
575 }
576 }
577 ],
578 "thresholds": [],
579 "timeRegions": [],
580 "title": "Memory - Resident",
581 "tooltip": {
582 "shared": true,
583 "sort": 0,
584 "value_type": "individual"
585 },
586 "type": "graph",
587 "xaxis": {
588 "mode": "time",
589 "show": true,
590 "values": []
591 },
592 "yaxes": [
593 {
594 "format": "decmbytes",
595 "logBase": 1,
596 "show": true
597 },
598 {
599 "format": "short",
600 "logBase": 1,
601 "show": true
602 }
603 ],
604 "yaxis": {
605 "align": false
606 }
607 },
608 {
609 "aliasColors": {},
610 "bars": false,
611 "dashLength": 10,
612 "dashes": false,
613 "datasource": {
614 "type": "prometheus",
615 "uid": "${DS_PROMETHEUS}"
616 },
617 "description": "The virtual megabytes for the mongod process. MMAPv1: Generally virtual should be a little larger than mapped (or 2x with --journal), but if virtual is many gigabytes larger, it indicates that excessive memory is being used by other aspects than the memory mapping of files -- that would be bad/suboptimal. The most common case of usage of a high amount of memory for non-mapped is that there are very many connections to the database. Each connection has a thread stack and the memory for those stacks can add up to a considerable amount. WiredTiger: Generally virtual should be a little larger than mapped, but if virtual is many gigabytes larger, it indicates that excessive memory is being used by other aspects than the memory mapping of files -- that would be bad/suboptimal. The most common case of usage of a high amount of memory for non-mapped is that there are very many connections to the database. Each connection has a thread stack and the memory for those stacks can add up to a considerable amount.",
618 "fieldConfig": {
619 "defaults": {
620 "links": [],
621 "unit": "decmbytes"
622 },
623 "overrides": []
624 },
625 "fill": 1,
626 "fillGradient": 0,
627 "gridPos": {
628 "h": 8,
629 "w": 12,
630 "x": 12,
631 "y": 12
632 },
633 "hiddenSeries": false,
634 "id": 72,
635 "legend": {
636 "avg": false,
637 "current": false,
638 "max": false,
639 "min": false,
640 "show": true,
641 "total": false,
642 "values": false
643 },
644 "lines": true,
645 "linewidth": 1,
646 "nullPointMode": "null",
647 "options": {
648 "alertThreshold": true,
649 "legend": {
650 "calcs": [],
651 "displayMode": "list",
652 "placement": "bottom"
653 },
654 "tooltip": {
655 "mode": "single"
656 }
657 },
658 "percentage": false,
659 "pluginVersion": "8.5.6",
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994 "description": "The percentage of time the CPU had something runnable, but the hypervisor chose to run something else. For servers with more than 1 CPU core, this value can exceed 100%.\n",
995 "fieldConfig": {
996 "defaults": {
997 "color": {
998 "mode": "palette-classic"
999 },
1000 "custom": {
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1002 "axisPlacement": "auto",
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1006 "gradientMode": "none",
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1015 "scaleDistribution": {
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1034 "value": null
1035 },
1036 {
1037 "color": "red",
1038 "value": 80
1039 }
1040 ]
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1042 "unit": "percent"
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1049 "options": {
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1051 "names": [
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1053 ],
1054 "prefix": "All except:",
1055 "readOnly": true
1056 }
1057 },
1058 "properties": [
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1064 "viz": true
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1068 }
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1080 "calcs": [],
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1082 "placement": "bottom"
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1086 }
1087 },
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1092 "interval": "",
1093 "legendFormat": "host - {{hostname}}",
1094 "refId": "A"
1095 }
1096 ],
1097 "title": "System cpu - steal",
1098 "type": "timeseries"
1099 },
1100 {
1101 "datasource": null,
1102 "description": "The percentage of time the CPU spent servicing guest, which is included in user. For servers with more than 1 CPU core, this value can exceed 100%.\n",
1103 "fieldConfig": {
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1105 "color": {
1106 "mode": "palette-classic"
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1111 "barAlignment": 0,
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1121 "lineWidth": 1,
1122 "pointSize": 5,
1123 "scaleDistribution": {
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1125 },
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1127 "spanNulls": false,
1128 "stacking": {
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1131 },
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1133 "mode": "off"
1134 }
1135 },
1136 "mappings": [],
1137 "thresholds": {
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1139 "steps": [
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1141 "color": "green",
1142 "value": null
1143 },
1144 {
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1146 "value": 80
1147 }
1148 ]
1149 },
1150 "unit": "percent"
1151 },
1152 "overrides": []
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1156 "w": 5,
1157 "x": 5,
1158 "y": 24
1159 },
1160 "id": 20,
1161 "options": {
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1164 "displayMode": "list",
1165 "placement": "bottom"
1166 },
1167 "tooltip": {
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1169 }
1170 },
1171 "targets": [
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1175 "interval": "",
1176 "legendFormat": "host - {{hostname}}",
1177 "refId": "A"
1178 }
1179 ],
1180 "title": "System cpu - guest",
1181 "type": "timeseries"
1182 },
1183 {
1184 "datasource": null,
1185 "description": "The percentage of time the CPU spent performing software interrupts. For servers with more than 1 CPU core, this value can exceed 100%.\n",
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1188 "color": {
1189 "mode": "palette-classic"
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1193 "axisPlacement": "auto",
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1195 "drawStyle": "line",
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1197 "gradientMode": "none",
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1200 "tooltip": false,
1201 "viz": false
1202 },
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1204 "lineWidth": 1,
1205 "pointSize": 5,
1206 "scaleDistribution": {
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1208 },
1209 "showPoints": "auto",
1210 "spanNulls": false,
1211 "stacking": {
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1214 },
1215 "thresholdsStyle": {
1216 "mode": "off"
1217 }
1218 },
1219 "mappings": [],
1220 "thresholds": {
1221 "mode": "absolute",
1222 "steps": [
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1224 "color": "green",
1225 "value": null
1226 },
1227 {
1228 "color": "red",
1229 "value": 80
1230 }
1231 ]
1232 },
1233 "unit": "percent"
1234 },
1235 "overrides": []
1236 },
1237 "gridPos": {
1238 "h": 7,
1239 "w": 5,
1240 "x": 10,
1241 "y": 24
1242 },
1243 "id": 21,
1244 "options": {
1245 "legend": {
1246 "calcs": [],
1247 "displayMode": "list",
1248 "placement": "bottom"
1249 },
1250 "tooltip": {
1251 "mode": "single"
1252 }
1253 },
1254 "targets": [
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1258 "interval": "",
1259 "legendFormat": "host - {{hostname}}",
1260 "refId": "A"
1261 }
1262 ],
1263 "title": "System cpu - softirq",
1264 "type": "timeseries"
1265 },
1266 {
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1268 "description": "The percentage of time the CPU spent performing hardware interrupts. For servers with more than 1 CPU core, this value can exceed 100%.\n",
1269 "fieldConfig": {
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1280 "gradientMode": "none",
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1283 "tooltip": false,
1284 "viz": false
1285 },
1286 "lineInterpolation": "linear",
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1288 "pointSize": 5,
1289 "scaleDistribution": {
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1291 },
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1293 "spanNulls": false,
1294 "stacking": {
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1296 "mode": "none"
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1298 "thresholdsStyle": {
1299 "mode": "off"
1300 }
1301 },
1302 "mappings": [],
1303 "thresholds": {
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1308 "value": null
1309 },
1310 {
1311 "color": "red",
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1313 }
1314 ]
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1316 "unit": "percent"
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1318 "overrides": []
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1320 "gridPos": {
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1322 "w": 5,
1323 "x": 15,
1324 "y": 24
1325 },
1326 "id": 22,
1327 "options": {
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1330 "displayMode": "list",
1331 "placement": "bottom"
1332 },
1333 "tooltip": {
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1335 }
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1341 "interval": "",
1342 "legendFormat": "host - {{hostname}}",
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1344 }
1345 ],
1346 "title": "System cpu - irq",
1347 "type": "timeseries"
1348 },
1349 {
1350 "datasource": null,
1351 "description": "The percentage of time the CPU spent waiting for IO operations to complete. For servers with more than 1 CPU core, this value can exceed 100%\n",
1352 "fieldConfig": {
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1354 "color": {
1355 "mode": "palette-classic"
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1360 "barAlignment": 0,
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1366 "tooltip": false,
1367 "viz": false
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1369 "lineInterpolation": "linear",
1370 "lineWidth": 1,
1371 "pointSize": 5,
1372 "scaleDistribution": {
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1374 },
1375 "showPoints": "auto",
1376 "spanNulls": false,
1377 "stacking": {
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1380 },
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1383 }
1384 },
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1388 "steps": [
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1392 },
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1396 }
1397 ]
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1399 "unit": "percent"
1400 },
1401 "overrides": []
1402 },
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1405 "w": 5,
1406 "x": 0,
1407 "y": 31
1408 },
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1413 "displayMode": "list",
1414 "placement": "bottom"
1415 },
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1418 }
1419 },
1420 "targets": [
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1424 "interval": "",
1425 "legendFormat": "host - {{hostname}}",
1426 "refId": "A"
1427 }
1428 ],
1429 "title": "System cpu - iowait",
1430 "type": "timeseries"
1431 },
1432 {
1433 "datasource": null,
1434 "description": "The percentage of time the CPU spent occupied by all processes with a positive nice value. For servers with more than 1 CPU core, this value can exceed 100%.\n",
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1455 "scaleDistribution": {
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1471 "steps": [
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1475 },
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1480 ]
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1484 "overrides": []
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1491 },
1492 "id": 24,
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1497 "placement": "bottom"
1498 },
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1500 "mode": "single"
1501 }
1502 },
1503 "targets": [
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1507 "interval": "",
1508 "legendFormat": "host - {{hostname}}",
1509 "refId": "A"
1510 }
1511 ],
1512 "title": "System cpu - nice",
1513 "type": "timeseries"
1514 },
1515 {
1516 "datasource": null,
1517 "description": "The percentage of time the CPU spent servicing operating system calls from all processes. For servers with more than 1 CPU core, this value can exceed 100%.\n",
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1538 "scaleDistribution": {
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1540 },
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1546 },
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1549 }
1550 },
1551 "mappings": [],
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1554 "steps": [
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1558 },
1559 {
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1561 "value": 80
1562 }
1563 ]
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1565 "unit": "percent"
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1567 "overrides": []
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1571 "w": 5,
1572 "x": 10,
1573 "y": 31
1574 },
1575 "id": 25,
1576 "options": {
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1584 }
1585 },
1586 "targets": [
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1590 "interval": "",
1591 "legendFormat": "host - {{hostname}}",
1592 "refId": "A"
1593 }
1594 ],
1595 "title": "System cpu - kernel",
1596 "type": "timeseries"
1597 },
1598 {
1599 "datasource": null,
1600 "description": "The percentage of time the CPU spent servicing all user applications (not just MongoDB processes). For servers with more than 1 CPU core, this value can exceed 100%.\n",
1601 "fieldConfig": {
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1632 }
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1641 },
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1645 }
1646 ]
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1648 "unit": "percent"
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1650 "overrides": []
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1654 "w": 5,
1655 "x": 15,
1656 "y": 31
1657 },
1658 "id": 26,
1659 "options": {
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1667 }
1668 },
1669 "targets": [
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1673 "interval": "",
1674 "legendFormat": "host - {{hostname}}",
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1676 }
1677 ],
1678 "title": "System cpu - user",
1679 "type": "timeseries"
1680 },
1681 {
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1683 "datasource": null,
1684 "gridPos": {
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1686 "w": 24,
1687 "x": 0,
1688 "y": 38
1689 },
1690 "id": 44,
1691 "panels": [],
1692 "title": "Normalized System Cpu",
1693 "type": "row"
1694 },
1695 {
1696 "datasource": null,
1697 "description": "The percentage of time the CPU had something runnable, but the hypervisor chose to run something else. It is scaled to a range of 0-100% by dividing by the number of CPU cores.\n",
1698 "fieldConfig": {
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1729 }
1730 },
1731 "mappings": [],
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1734 "steps": [
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1738 },
1739 {
1740 "color": "red",
1741 "value": 80
1742 }
1743 ]
1744 },
1745 "unit": "percent"
1746 },
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1752 "options": {
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1754 "names": [
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1756 ],
1757 "prefix": "All except:",
1758 "readOnly": true
1759 }
1760 },
1761 "properties": [
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1766 "tooltip": false,
1767 "viz": true
1768 }
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1774 "gridPos": {
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1776 "w": 5,
1777 "x": 0,
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1780 "id": 46,
1781 "options": {
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1789 }
1790 },
1791 "targets": [
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1795 "interval": "",
1796 "legendFormat": "host - {{hostname}}",
1797 "refId": "A"
1798 }
1799 ],
1800 "title": "Normalized System cpu - steal",
1801 "type": "timeseries"
1802 },
1803 {
1804 "datasource": null,
1805 "description": "The percentage of time the CPU spent servicing guest, which is included in user. It is scaled to a range of 0-100% by dividing by the number of CPU cores.\n",
1806 "fieldConfig": {
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1837 }
1838 },
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1842 "steps": [
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1846 },
1847 {
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1852 },
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1855 "overrides": []
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1860 "x": 5,
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1864 "options": {
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1867 "displayMode": "list",
1868 "placement": "bottom"
1869 },
1870 "tooltip": {
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1873 },
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1882 ],
1883 "title": "Normalized System cpu - guest",
1884 "type": "timeseries"
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1886 {
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1932 "value": 80
1933 }
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1935 },
1936 "unit": "percent"
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1939 },
1940 "gridPos": {
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1942 "w": 5,
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1944 "y": 39
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1947 "options": {
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1952 },
1953 "tooltip": {
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1955 }
1956 },
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1962 "legendFormat": "host - {{hostname}}",
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1964 }
1965 ],
1966 "title": "Normalized System cpu - softirq",
1967 "type": "timeseries"
1968 },
1969 {
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1971 "description": "The percentage of time the CPU spent performing hardware interrupts. It is scaled to a range of 0-100% by dividing by the number of CPU cores.\n",
1972 "fieldConfig": {
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1991 "pointSize": 5,
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2000 },
2001 "thresholdsStyle": {
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2004 },
2005 "mappings": [],
2006 "thresholds": {
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2008 "steps": [
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2015 "value": 80
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2018 },
2019 "unit": "percent"
2020 },
2021 "overrides": []
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2026 "x": 15,
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2028 },
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2030 "options": {
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2036 "tooltip": {
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2045 "legendFormat": "host - {{hostname}}",
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2047 }
2048 ],
2049 "title": "Normalized System cpu - irq",
2050 "type": "timeseries"
2051 },
2052 {
2053 "datasource": null,
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2074 "pointSize": 5,
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2080 "stacking": {
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2083 },
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2087 },
2088 "mappings": [],
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2095 },
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2099 }
2100 ]
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2103 },
2104 "overrides": []
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2106 "gridPos": {
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2108 "w": 5,
2109 "x": 0,
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2111 },
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2113 "options": {
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2116 "displayMode": "list",
2117 "placement": "bottom"
2118 },
2119 "tooltip": {
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2121 }
2122 },
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2127 "interval": "",
2128 "legendFormat": "host - {{hostname}}",
2129 "refId": "A"
2130 }
2131 ],
2132 "title": "Normalized System cpu - iowait",
2133 "type": "timeseries"
2134 },
2135 {
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2137 "description": "The percentage of time the CPU spent occupied by all processes with a positive nice value. It is scaled to a range of 0-100% by dividing by the number of CPU cores.\n",
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2167 "thresholdsStyle": {
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2182 }
2183 ]
2184 },
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2187 "overrides": []
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2192 "x": 5,
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2194 },
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2196 "options": {
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2201 },
2202 "tooltip": {
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2205 },
2206 "targets": [
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2211 "legendFormat": "host - {{hostname}}",
2212 "refId": "A"
2213 }
2214 ],
2215 "title": "Normalized System cpu - nice",
2216 "type": "timeseries"
2217 },
2218 {
2219 "datasource": null,
2220 "description": "The percentage of time the CPU spent servicing operating system calls from all processes. It is scaled to a range of 0-100% by dividing by the number of CPU cores.\n",
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2235 "tooltip": false,
2236 "viz": false
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2253 },
2254 "mappings": [],
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2261 },
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2265 }
2266 ]
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2269 },
2270 "overrides": []
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2272 "gridPos": {
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2274 "w": 5,
2275 "x": 10,
2276 "y": 46
2277 },
2278 "id": 53,
2279 "options": {
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2288 },
2289 "targets": [
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2293 "interval": "",
2294 "legendFormat": "host - {{hostname}}",
2295 "refId": "A"
2296 }
2297 ],
2298 "title": "Normalized System cpu - kernel",
2299 "type": "timeseries"
2300 },
2301 {
2302 "datasource": null,
2303 "description": "The percentage of time the CPU spent servicing all user applications (not just MongoDB processes). It is scaled to a range of 0-100% by dividing by the number of CPU cores.\n",
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2318 "tooltip": false,
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2323 "pointSize": 5,
2324 "scaleDistribution": {
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2327 "showPoints": "auto",
2328 "spanNulls": false,
2329 "stacking": {
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2332 },
2333 "thresholdsStyle": {
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2335 }
2336 },
2337 "mappings": [],
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2344 },
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2347 "value": 80
2348 }
2349 ]
2350 },
2351 "unit": "percent"
2352 },
2353 "overrides": []
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2355 "gridPos": {
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2357 "w": 5,
2358 "x": 15,
2359 "y": 46
2360 },
2361 "id": 50,
2362 "options": {
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2368 "tooltip": {
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2370 }
2371 },
2372 "targets": [
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2376 "interval": "",
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2378 "refId": "A"
2379 }
2380 ],
2381 "title": "Normalized System cpu - user",
2382 "type": "timeseries"
2383 },
2384 {
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2386 "datasource": null,
2387 "gridPos": {
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2390 "x": 0,
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2392 },
2393 "id": 28,
2394 "panels": [],
2395 "title": "System Network",
2396 "type": "row"
2397 },
2398 {
2399 "datasource": null,
2400 "description": "The average rate of physical bytes received per second by the eth0 network interface\n",
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2415 "tooltip": false,
2416 "viz": false
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2420 "pointSize": 5,
2421 "scaleDistribution": {
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2424 "showPoints": "auto",
2425 "spanNulls": false,
2426 "stacking": {
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2429 },
2430 "thresholdsStyle": {
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2432 }
2433 },
2434 "mappings": [],
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2437 "steps": [
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2441 },
2442 {
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2445 }
2446 ]
2447 },
2448 "unit": "Bps"
2449 },
2450 "overrides": []
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2452 "gridPos": {
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2454 "w": 10,
2455 "x": 0,
2456 "y": 54
2457 },
2458 "id": 73,
2459 "options": {
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2463 "placement": "bottom"
2464 },
2465 "tooltip": {
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2467 }
2468 },
2469 "targets": [
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2473 "interval": "",
2474 "legendFormat": "host - {{hostname}}",
2475 "refId": "A"
2476 }
2477 ],
2478 "title": "Network bytes In",
2479 "type": "timeseries"
2480 },
2481 {
2482 "datasource": null,
2483 "description": "The average rate of physical bytes transmitted per second by the eth0 network interface",
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2503 "pointSize": 5,
2504 "scaleDistribution": {
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2506 },
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2508 "spanNulls": false,
2509 "stacking": {
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2512 },
2513 "thresholdsStyle": {
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2515 }
2516 },
2517 "mappings": [],
2518 "thresholds": {
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2520 "steps": [
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2524 },
2525 {
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2527 "value": 80
2528 }
2529 ]
2530 },
2531 "unit": "Bps"
2532 },
2533 "overrides": []
2534 },
2535 "gridPos": {
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2537 "w": 10,
2538 "x": 10,
2539 "y": 54
2540 },
2541 "id": 74,
2542 "options": {
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2546 "placement": "bottom"
2547 },
2548 "tooltip": {
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2550 }
2551 },
2552 "targets": [
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2555 "expr": "label_replace( sum(rate(hardware_system_network_eth0_bytes_out_bytes{group_id=~\"$group_id\", instance=~\"$host.*\"}[$interval])) by (instance) + sum(rate(hardware_system_network_lo_bytes_out_bytes{group_id=~\"$group_id\", instance=~\"$host.*\"}[$interval])) by (instance), \"hostname\", \"$1\", \"instance\", \"(.*):.*\")",
2556 "interval": "",
2557 "legendFormat": "host - {{hostname}}",
2558 "refId": "A"
2559 }
2560 ],
2561 "title": "Network bytes Out",
2562 "type": "timeseries"
2563 },
2564 {
2565 "collapsed": false,
2566 "datasource": null,
2567 "gridPos": {
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2569 "w": 24,
2570 "x": 0,
2571 "y": 63
2572 },
2573 "id": 30,
2574 "panels": [],
2575 "title": "System Disk",
2576 "type": "row"
2577 },
2578 {
2579 "datasource": null,
2580 "description": "The total bytes of free disk space on the disk partition used by MongoDB.\n",
2581 "fieldConfig": {
2582 "defaults": {
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2585 },
2586 "custom": {
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2588 "axisPlacement": "auto",
2589 "barAlignment": 0,
2590 "drawStyle": "line",
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2592 "gradientMode": "none",
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2595 "tooltip": false,
2596 "viz": false
2597 },
2598 "lineInterpolation": "linear",
2599 "lineWidth": 1,
2600 "pointSize": 5,
2601 "scaleDistribution": {
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2605 "spanNulls": false,
2606 "stacking": {
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2609 },
2610 "thresholdsStyle": {
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2612 }
2613 },
2614 "mappings": [],
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2617 "steps": [
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2621 },
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2624 "value": 80
2625 }
2626 ]
2627 },
2628 "unit": "decbytes"
2629 },
2630 "overrides": []
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2634 "w": 6,
2635 "x": 0,
2636 "y": 64
2637 },
2638 "id": 14,
2639 "options": {
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2642 "displayMode": "list",
2643 "placement": "bottom"
2644 },
2645 "tooltip": {
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2647 }
2648 },
2649 "targets": [
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2652 "expr": "label_replace( sum(hardware_disk_metrics_disk_space_free_bytes{group_id=~\"$group_id\", instance=~\"$host.*\"}) by (instance, disk_name) , \"hostname\", \"$1\", \"instance\", \"(.*):.*\")",
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2654 "legendFormat": "disk - {{disk_name}}, host - {{hostname}} ",
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2656 }
2657 ],
2658 "title": "System Disk - Free",
2659 "type": "timeseries"
2660 },
2661 {
2662 "datasource": null,
2663 "description": "The percent of free disk space on the partition used by MongoDB.\n",
2664 "fieldConfig": {
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3546 "mappings": [],
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3754 }
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4044 "definition": "label_values(group_id)",
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4046 "error": null,
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4048 "includeAll": false,
4049 "label": "Group Id",
4050 "multi": false,
4051 "name": "group_id",
4052 "options": [],
4053 "query": {
4054 "query": "label_values(group_id)",
4055 "refId": "StandardVariableQuery"
4056 },
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4060 "sort": 0,
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4067 "text": "Cluster0",
4068 "value": "Cluster0"
4069 },
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4071 "definition": "label_values(mongodb_up{group_id='$group_id'}, cluster_name)",
4072 "description": null,
4073 "error": null,
4074 "hide": 0,
4075 "includeAll": false,
4076 "label": "Cluster Name",
4077 "multi": false,
4078 "name": "cluster_name",
4079 "options": [],
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4083 },
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4085 "regex": "",
4086 "skipUrlSync": false,
4087 "sort": 0,
4088 "type": "query"
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4090 {
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4092 "current": {
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4094 "text": [
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4096 ],
4097 "value": [
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4099 ]
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4104 "error": null,
4105 "hide": 0,
4106 "includeAll": true,
4107 "label": "Replica set name",
4108 "multi": true,
4109 "name": "replica_set_name",
4110 "options": [],
4111 "query": {
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4135 "error": null,
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4139 "multi": true,
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4159 "value": [
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4166 "error": null,
4167 "hide": 0,
4168 "includeAll": true,
4169 "label": "Process Port",
4170 "multi": true,
4171 "name": "process_port",
4172 "options": [],
4173 "query": {
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4176 },
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4178 "regex": "",
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4183 {
4184 "auto": true,
4185 "auto_count": 30,
4186 "auto_min": "10s",
4187 "current": {
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4189 "text": "1m",
4190 "value": "1m"
4191 },
4192 "description": null,
4193 "error": null,
4194 "hide": 0,
4195 "label": "Interval",
4196 "name": "interval",
4197 "options": [
4198 {
4199 "selected": false,
4200 "text": "auto",
4201 "value": "$__auto_interval_interval"
4202 },
4203 {
4204 "selected": false,
4205 "text": "30s",
4206 "value": "30s"
4207 },
4208 {
4209 "selected": true,
4210 "text": "1m",
4211 "value": "1m"
4212 },
4213 {
4214 "selected": false,
4215 "text": "5m",
4216 "value": "5m"
4217 },
4218 {
4219 "selected": false,
4220 "text": "30m",
4221 "value": "30m"
4222 },
4223 {
4224 "selected": false,
4225 "text": "1h",
4226 "value": "1h"
4227 },
4228 {
4229 "selected": false,
4230 "text": "1d",
4231 "value": "1d"
4232 }
4233 ],
4234 "query": "30s,1m,5m,30m,1h,1d",
4235 "queryValue": "",
4236 "refresh": 2,
4237 "skipUrlSync": false,
4238 "type": "interval"
4239 }
4240 ]
4241 },
4242 "time": {
4243 "from": "now-30m",
4244 "to": "now"
4245 },
4246 "timepicker": {},
4247 "timezone": "",
4248 "title": "Hardware Metrics - Cloud Manager",
4249 "uid": "7LTNNcpnzsasddsd",
4250 "version": 1
4251}

Para aprender más sobre la importación de tableros de Grafana, consulta la documentación de Grafana.

Las siguientes métricas están disponibles cuando utiliza la integración de Prometheus con su clúster MongoDB Atlas:

Cada métrica de MongoDB contiene las siguientes etiquetas:

Etiqueta
Descripción

group_id

String única de dígitos hexadecimales que identifica el proyecto.

org_id

String única de dígitos hexadecimales que identifica a la organización.

cl_role

Etiqueta legible por humanos que define el rol del clúster.

cl_name

Etiqueta legible por humanos que identifica el clúster.

rs_nm

Etiqueta legible por humanos que identifica el conjunto de réplicas.

rs_state

Número que indica el estado del Set de réplicas.

process_port

Puerto en el cual se ejecuta el proceso.

mongodb_info es un medidor que siempre tiene el valor de 1. Esta métrica contiene todas las Etiquetas de métricas de MongoDB y también las siguientes etiquetas:

Etiqueta
Descripción

mongodb_version

String que representa las versiones principal, secundaria y de parche.

replica_state_name

String que indica el estado del Set de réplicas.

process_type

String que indica el proceso en ejecución. Sus valores pueden ser mongod, mongos o config.

Nota

También puedes ver descripciones de cada métrica de hardware en el navegador de expresiones Prometheus.

Nombre
Sistema operativo
Tipo
Descripción

hardware_system_cpu_nice

Unix, Darwin

Contador

Tiempo pasado en modo usuario con baja prioridad.

hardware_system_cpu_io_wait

UNIX

Contador

Tiempo de espera para que se complete la E/S.

hardware_system_cpu_irq

UNIX

Contador

Tiempo dedicado a atender las interrupciones.

hardware_system_cpu_soft_irq

UNIX

Contador

Tiempo dedicado al mantenimiento de softirq.

hardware_system_cpu_steal

UNIX

Contador

Tiempo dedicado a otros sistemas operativos al ejecutarse en un entorno virtual.

hardware_system_cpu_guest

UNIX

Contador

Tiempo dedicado a ejecutar una CPU virtual para los sistemas operativos invitados bajo el control del kernel de Linux.

hardware_system_cpu_guest_nice

UNIX

Contador

Tiempo dedicado a ejecutar un invitado con una prioridad ajustada.

hardware_system_cpu_kernel_milliseconds

Todo

Contador

Tiempo empleado en moda de sistema.

hardware_system_cpu_user_milliseconds

Todo

Contador

Tiempo dedicado en modo de usuario.

hardware_disk_metrics_weighted_time_io

UNIX

Contador

Tiempo ponderado dedicado a realizar operaciones de E/S.

hardware_disk_metrics_physical_write_count

UNIX

Contador

Número de E/S de escritura física procesadas.

hardware_disk_metrics_physical_read_count

UNIX

Contador

Número de E/S de lectura física procesadas.

hardware_disk_metrics_total_time

UNIX

Contador

Tiempo total que el dispositivo de bloque está activo.

hardware_disk_metrics_idle_time

Windows

Contador

Tiempo dedicado a la tarea inactiva.

hardware_disk_metrics_disk_space_free_bytes

Todo

Medidor

Espacio en disco disponible en el sistema de archivos montado.

hardware_disk_metrics_disk_space_used_bytes

Todo

Medidor

Espacio en disco utilizado en el sistema de archivos montado.

hardware_disk_metrics_read_count

Todo

Contador

Número de E/S de lectura procesadas.

hardware_disk_metrics_read_time_milliseconds

Todo

Contador

Tiempo total de espera para las solicitudes de lectura.

hardware_disk_metrics_write_count

Todo

Contador

Número de E/S de guardado procesadas.

hardware_disk_metrics_write_time_milliseconds

Todo

Contador

Tiempo total de espera para las solicitudes de guardado.

hardware_process_cpu_children_user

UNIX

Contador

Cantidad de tiempo programado en modo de usuario para que este proceso espere a los procesos secundarios.

hardware_process_cpu_children_kernel

UNIX

Contador

Cantidad de tiempo programada en el modo kernel para que este proceso espere a los procesos secundarios.

hardware_process_cpu_kernel_milliseconds

Todo

Contador

Cantidad de tiempo programada en modo kernel para este proceso.

hardware_process_cpu_user_milliseconds

Todo

Contador

Cantidad de tiempo programada en modo usuario para este proceso.

hardware_system_vm_page_swap_in

UNIX

Contador

Número de páginas que el sistema ha intercambiado desde el disco.

hardware_system_vm_page_swap_out

UNIX

Contador

Número de páginas que el sistema ha paginado al disco.

hardware_system_memory_mem_total

UNIX

Medidor

RAM total utilizable (RAM física menos algunos bits reservados y el código binario del kernel).

hardware_system_memory_mem_free

UNIX

Medidor

Suma de LowFree y HighFree.

hardware_system_memory_mem_available

UNIX

Medidor

Una estimación de la cantidad de memoria disponible para iniciar nuevas aplicaciones, sin intercambio de memoria.

hardware_system_memory_buffers

UNIX

Medidor

Almacenamiento temporal para bloques de disco sin procesar que no deberían volverse excesivamente grandes.

hardware_system_memory_cached

UNIX

Medidor

Caché en memoria para archivos leídos desde el disco. Esto no incluye SwapCached.

hardware_system_memory_swap_total

UNIX

Medidor

Cantidad total de espacio de intercambio disponible.

hardware_system_memory_swap_free

UNIX

Medidor

Cantidad total de espacio de intercambio no utilizado.

hardware_system_memory_shared_mem

UNIX

Medidor

Cantidad de memoria consumida en sistemas de archivos cuyos contenidos residen en la memoria virtual.

hardware_system_memory_swap_free_kilobytes

Todo

Medidor

Cantidad total de espacio de intercambio no utilizado.

hardware_system_memory_swap_total_kilobytes

Todo

Medidor

Cantidad total de espacio de intercambio disponible.

hardware_platform_num_logical_cpus

Todo

Medidor

Número de CPUs lógicas utilizables por el proceso actual.

hardware_system_network_eth0_bytes_in_bytes

Todo

Contador

Número de bytes de datos recibidos por la interfaz.

hardware_system_network_eth0_bytes_out_bytes

Todo

Contador

Número de bytes de datos transmitidos por la interfaz.

hardware_system_network_lo_bytes_in_bytes

Todo

Contador

Número de bytes de datos recibidos por la interfaz.

hardware_system_network_lo_bytes_out_bytes

Todo

Contador

Número de bytes de datos transmitidos por la interfaz.

Cada métrica de hardware contiene las siguientes etiquetas:

Etiqueta
Descripción

group_id

String única de dígitos hexadecimales que identifica el proyecto.

org_id

String única de dígitos hexadecimales que identifica a la organización.

process_port

Puerto en el cual se ejecuta el proceso.

disk_name

Etiqueta legible por humanos que identifica el disco.

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