Integrate with Prometheus
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Prometheus collects metrics from configured targets at given intervals, evaluates rule expressions, displays the results, and can trigger alerts when it observes specific conditions.
Our integration allows you to configure Cloud Manager to send metric data about your deployment to your Prometheus instance.
Prerequisites
Prometheus integration is available in automation managed clusters that use MongoDB Agent 12.0.15.7646 or later. MongoDB Agent 12.0.15.7646 is released with Cloud Manager 6.0.7.
Have a working Prometheus instance. To set up a working instance, see their Installation Guide.
(Optional) Use Grafana to visualize your Prometheus metrics.
Procedure
To integrate Cloud Manager with Prometheus:
1
In MongoDB Cloud Manager, go to the Project Integrations page.
If it's not already displayed, select the organization that contains your desired project from the Organizations menu in the navigation bar.
If it's not already displayed, select your desired project from the Projects menu in the navigation bar.
Next to the Projects menu, expand the Options menu, then click Integrations.
The Project Integrations page displays.
3
Enter your preferred username and password.
Prometheus authentication credentials are specifically designed for use with the Prometheus integration in Cloud Manager. Cloud Manager uses these credentials to only access the Prometheus discovery endpoint and scrape Prometheus metrics from Cloud Manager nodes. They are strictly limited to these functions and do not have any additional permissions or capabilities beyond accessing and collecting monitoring data.
Important
Copy your username and password in a secure location. You can't access the password after you leave this screen.
4
5
(Optional) Encrypt all Prometheus metrics.
If you enable this setting, Cloud Manager assures that your Prometheus
instance uses https to scrape metrics.
Fields | Description |
|---|---|
TLS Certificate Key File Path |
You are responsible for the following:
|
TLS Certificate Key File Password | Required if the certificate key file is encrypted. |
6
Select your preferred service discovery method.
Discovery Method | Description | ||||||||||||||||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
This method requires Prometheus v2.28 and later. It
generates the scrape_config
part of your configuration file
to discover targets over an HTTP endpoint. | |||||||||||||||||||||||||||||||||||||||
This method allows Prometheus to read YAML or JSON documents to configure the targets to scrape from. You are responsible for providing the targets by making a request to the Discovery API and storing its results in a To make the request, substitute the placeholder text in one of the following tabs or create your own script in another language. If you need to install the To learn more about the Discovery API, see Return the Latest Targets for Prometheus. |
8
View Your Cluster Metrics on Prometheus.
Copy the generated snippet into the scrape_configs section of your configuration file and substitute the placeholder text.
For an example of the configuration file in either method, see Example Configurations.
Restart your Prometheus instance.
In your Prometheus instance, click
Statusin the top navigation bar, and clickTargetsto see the metrics of your deployment.
Example Configurations
The following shows examples of the configuration file when you use the HTTP Service Discovery or File Service Discovery method.
The configuration file in both methods contains the following fields:
Field | Description |
|---|---|
scrape_interval | Time that indicates how frequently to scrape targets. This
setting supports a minimum time of 10s. |
job_name | Human-readable label assigned to scraped metrics. |
metrics_path | HTTP resource path that indicates where to fetch metrics from
targets. |
scheme | Your Prometheus protocol scheme configured for
requests, either http or https. If you
configure https, you must specify tlsPemPath. |
basic_auth | Authorization header to use on every scrape request. |
HTTP Service Discovery
The HTTP Service Discovery method also contains the http_sd_configs
field with the following sub-fields:
Field | Description |
|---|---|
url | URL from which Prometheus fetches the targets. |
refresh_interval | Time that indicates when to re-query the endpoint. |
basic_auth | Credentials to use for authenticating to the API server. |
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://mongodb.prakticum-team.ru/proxy/cloud.mongodb.com/prometheus/v1.0/groups/61e6e34e93eac1632d39f457/discovery refresh_interval: 60s basic_auth: username: prom_user_61e6e34e93eac1632d39f457 password: V7hTyLfkjwiWQbv
File Service Discovery
The File Service Discovery method also contains the
file_sd_configs field with the following sub-field:
Field | Description |
|---|---|
files | List that contains the files from which to extract the metrics scraping targets. |
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
Import a Sample Grafana Dashboard
To import a sample Grafana dashboard:
3
Copy over the mongo-metrics.json or the hardware-metrics.json file to create a dashboard.
1 { 2 "__inputs": [ 3 { 4 "name": "DS_THANOS", 5 "label": "thanos", 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": "${DS_THANOS}" 90 }, 91 "fieldConfig": { 92 "defaults": { 93 "color": { 94 "mode": "thresholds" 95 }, 96 "custom": { 97 "align": "auto", 98 "displayMode": "auto", 99 "inspect": false 100 }, 101 "decimals": 2, 102 "displayName": "", 103 "mappings": [], 104 "thresholds": { 105 "mode": "absolute", 106 "steps": [ 107 { 108 "color": "green", 109 "value": null 110 }, 111 { 112 "color": "red", 113 "value": 80 114 } 115 ] 116 }, 117 "unit": "short" 118 }, 119 "overrides": [ 120 { 121 "matcher": { 122 "id": "byName", 123 "options": "Value" 124 }, 125 "properties": [ 126 { 127 "id": "unit", 128 "value": "short" 129 }, 130 { 131 "id": "decimals", 132 "value": 2 133 }, 134 { 135 "id": "custom.align" 136 } 137 ] 138 } 139 ] 140 }, 141 "gridPos": { 142 "h": 4, 143 "w": 24, 144 "x": 0, 145 "y": 1 146 }, 147 "id": 41, 148 "options": { 149 "footer": { 150 "fields": "", 151 "reducer": [ 152 "sum" 153 ], 154 "show": false 155 }, 156 "showHeader": true 157 }, 158 "pluginVersion": "8.5.6", 159 "targets": [ 160 { 161 "datasource": { 162 "type": "prometheus", 163 "uid": "${DS_THANOS}" 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_THANOS}" 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": "${DS_THANOS}" 358 }, 359 "exemplar": false, 360 "expr": "label_replace( sum(mongodb_info{group_id=~\"$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_THANOS}" 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_THANOS}" 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_THANOS}" 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", 660 "pointradius": 2, 661 "points": false, 662 "renderer": "flot", 663 "seriesOverrides": [], 664 "spaceLength": 10, 665 "stack": false, 666 "steppedLine": false, 667 "targets": [ 668 { 669 "exemplar": true, 670 "expr": "label_replace(sum(mongodb_mem_virtual{group_id=~\"$group_id\", cl_name=~\"$cl_name\", rs_nm=~\"$rs_nm\", instance=~\"$host.*\", process_port=~\"$process_port\"}) by (instance, process_port) , \"hostname\", \"$1\", \"instance\", \"(.*)\")", 671 "interval": "", 672 "legendFormat": "{{hostname}}:{{process_port}}", 673 "refId": "A", 674 "datasource": { 675 "type": "prometheus", 676 "uid": "${DS_THANOS}" 677 } 678 } 679 ], 680 "thresholds": [], 681 "timeRegions": [], 682 "title": "Memory - Virtual", 683 "tooltip": { 684 "shared": true, 685 "sort": 0, 686 "value_type": "individual" 687 }, 688 "type": "graph", 689 "xaxis": { 690 "mode": "time", 691 "show": true, 692 "values": [] 693 }, 694 "yaxes": [ 695 { 696 "format": "decmbytes", 697 "logBase": 1, 698 "show": true 699 }, 700 { 701 "format": "short", 702 "logBase": 1, 703 "show": true 704 } 705 ], 706 "yaxis": { 707 "align": false 708 } 709 }, 710 { 711 "collapsed": false, 712 "datasource": { 713 "type": "prometheus", 714 "uid": "000000010" 715 }, 716 "gridPos": { 717 "h": 1, 718 "w": 24, 719 "x": 0, 720 "y": 20 721 }, 722 "id": 17, 723 "panels": [], 724 "title": "Asserts", 725 "type": "row" 726 }, 727 { 728 "aliasColors": {}, 729 "bars": false, 730 "dashLength": 10, 731 "dashes": false, 732 "datasource": { 733 "type": "prometheus", 734 "uid": "${DS_THANOS}" 735 }, 736 "description": "The average rate of regular asserts raised per second over the selected sample period\n", 737 "fieldConfig": { 738 "defaults": { 739 "links": [], 740 "unit": "/s" 741 }, 742 "overrides": [] 743 }, 744 "fill": 1, 745 "fillGradient": 0, 746 "gridPos": { 747 "h": 8, 748 "w": 6, 749 "x": 0, 750 "y": 21 751 }, 752 "hiddenSeries": false, 753 "id": 73, 754 "legend": { 755 "avg": false, 756 "current": false, 757 "max": false, 758 "min": false, 759 "show": true, 760 "total": false, 761 "values": false 762 }, 763 "lines": true, 764 "linewidth": 1, 765 "nullPointMode": "null", 766 "options": { 767 "alertThreshold": true, 768 "legend": { 769 "calcs": [], 770 "displayMode": "list", 771 "placement": "bottom" 772 }, 773 "tooltip": { 774 "mode": "single" 775 } 776 }, 777 "percentage": false, 778 "pluginVersion": "8.5.6", 779 "pointradius": 2, 780 "points": false, 781 "renderer": "flot", 782 "seriesOverrides": [], 783 "spaceLength": 10, 784 "stack": false, 785 "steppedLine": false, 786 "targets": [ 787 { 788 "exemplar": true, 789 "expr": "label_replace(sum(rate(mongodb_asserts_regular{group_id=~\"$group_id\", cl_name=~\"$cl_name\", rs_nm=~\"$rs_nm\", instance=~\"$host.*\", process_port=~\"$process_port\"}[$Interval])) by (instance, process_port) , \"hostname\", \"$1\", \"instance\", \"(.*)\")", 790 "interval": "", 791 "legendFormat": "{{hostname}}:{{process_port}}", 792 "refId": "A", 793 "datasource": { 794 "type": "prometheus", 795 "uid": "${DS_THANOS}" 796 } 797 } 798 ], 799 "thresholds": [], 800 "timeRegions": [], 801 "title": "Asserts - Regular", 802 "tooltip": { 803 "shared": true, 804 "sort": 0, 805 "value_type": "individual" 806 }, 807 "type": "graph", 808 "xaxis": { 809 "mode": "time", 810 "show": true, 811 "values": [] 812 }, 813 "yaxes": [ 814 { 815 "format": "/s", 816 "logBase": 1, 817 "show": true 818 }, 819 { 820 "format": "short", 821 "logBase": 1, 822 "show": true 823 } 824 ], 825 "yaxis": { 826 "align": false 827 } 828 }, 829 { 830 "aliasColors": {}, 831 "bars": false, 832 "dashLength": 10, 833 "dashes": false, 834 "datasource": { 835 "type": "prometheus", 836 "uid": "${DS_THANOS}" 837 }, 838 "description": "The average rate of warnings per second over the selected sample period", 839 "fieldConfig": { 840 "defaults": { 841 "links": [], 842 "unit": "/s" 843 }, 844 "overrides": [] 845 }, 846 "fill": 1, 847 "fillGradient": 0, 848 "gridPos": { 849 "h": 8, 850 "w": 6, 851 "x": 6, 852 "y": 21 853 }, 854 "hiddenSeries": false, 855 "id": 74, 856 "legend": { 857 "avg": false, 858 "current": false, 859 "max": false, 860 "min": false, 861 "show": true, 862 "total": false, 863 "values": false 864 }, 865 "lines": true, 866 "linewidth": 1, 867 "nullPointMode": "null", 868 "options": { 869 "alertThreshold": true, 870 "legend": { 871 "calcs": [], 872 "displayMode": "list", 873 "placement": "bottom" 874 }, 875 "tooltip": { 876 "mode": "single" 877 } 878 }, 879 "percentage": false, 880 "pluginVersion": "8.5.6", 881 "pointradius": 2, 882 "points": false, 883 "renderer": "flot", 884 "seriesOverrides": [], 885 "spaceLength": 10, 886 "stack": false, 887 "steppedLine": false, 888 "targets": [ 889 { 890 "exemplar": true, 891 "expr": "label_replace(sum(rate(mongodb_asserts_warning{group_id=~\"$group_id\", cl_name=~\"$cl_name\", rs_nm=~\"$rs_nm\", instance=~\"$host.*\", process_port=~\"$process_port\"}[$Interval])) by (instance, process_port) , \"hostname\", \"$1\", \"instance\", \"(.*)\")", 892 "interval": "", 893 "legendFormat": "{{hostname}}:{{process_port}}", 894 "refId": "A", 895 "datasource": { 896 "type": "prometheus", 897 "uid": "${DS_THANOS}" 898 } 899 } 900 ], 901 "thresholds": [], 902 "timeRegions": [], 903 "title": "Asserts - Warning", 904 "tooltip": { 905 "shared": true, 906 "sort": 0, 907 "value_type": "individual" 908 }, 909 "type": "graph", 910 "xaxis": { 911 "mode": "time", 912 "show": true, 913 "values": [] 914 }, 915 "yaxes": [ 916 { 917 "format": "/s", 918 "logBase": 1, 919 "show": true 920 }, 921 { 922 "format": "short", 923 "logBase": 1, 924 "show": true 925 } 926 ], 927 "yaxis": { 928 "align": false 929 } 930 }, 931 { 932 "aliasColors": {}, 933 "bars": false, 934 "dashLength": 10, 935 "dashes": false, 936 "datasource": { 937 "type": "prometheus", 938 "uid": "${DS_THANOS}" 939 }, 940 "description": "The average rate of message asserts per second over the selected sample period. These are internal server errors that have a well defined text string. 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For servers with more than 1 CPU core, this value can exceed 100%\n", 1352 "fieldConfig": { 1353 "defaults": { 1354 "color": { 1355 "mode": "palette-classic" 1356 }, 1357 "custom": { 1358 "axisLabel": "", 1359 "axisPlacement": "auto", 1360 "barAlignment": 0, 1361 "drawStyle": "line", 1362 "fillOpacity": 0, 1363 "gradientMode": "none", 1364 "hideFrom": { 1365 "legend": false, 1366 "tooltip": false, 1367 "viz": false 1368 }, 1369 "lineInterpolation": "linear", 1370 "lineWidth": 1, 1371 "pointSize": 5, 1372 "scaleDistribution": { 1373 "type": "linear" 1374 }, 1375 "showPoints": "auto", 1376 "spanNulls": false, 1377 "stacking": { 1378 "group": "A", 1379 "mode": "none" 1380 }, 1381 "thresholdsStyle": { 1382 "mode": "off" 1383 } 1384 }, 1385 "mappings": [], 1386 "thresholds": { 1387 "mode": "absolute", 1388 "steps": [ 1389 { 1390 "color": "green", 1391 "value": null 1392 }, 1393 { 1394 "color": "red", 1395 "value": 80 1396 } 1397 ] 1398 }, 1399 "unit": "percent" 1400 }, 1401 "overrides": [] 1402 }, 1403 "gridPos": { 1404 "h": 7, 1405 "w": 5, 1406 "x": 0, 1407 "y": 31 1408 }, 1409 "id": 23, 1410 "options": { 1411 "legend": { 1412 "calcs": [], 1413 "displayMode": "list", 1414 "placement": "bottom" 1415 }, 1416 "tooltip": { 1417 "mode": "single" 1418 } 1419 }, 1420 "targets": [ 1421 { 1422 "exemplar": true, 1423 "expr": "label_replace(sum(rate(hardware_system_cpu_io_wait_milliseconds{group_id=~\"$group_id\", instance=~\"$host.*\"}[$interval]) / 10) by (instance) , \"hostname\", \"$1\", \"instance\", \"(.*):.*\")", 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. 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It is scaled to a range of 0-100% by dividing by the number of CPU cores.\n", 1698 "fieldConfig": { 1699 "defaults": { 1700 "color": { 1701 "mode": "palette-classic" 1702 }, 1703 "custom": { 1704 "axisLabel": "", 1705 "axisPlacement": "auto", 1706 "barAlignment": 0, 1707 "drawStyle": "line", 1708 "fillOpacity": 0, 1709 "gradientMode": "none", 1710 "hideFrom": { 1711 "legend": false, 1712 "tooltip": false, 1713 "viz": false 1714 }, 1715 "lineInterpolation": "linear", 1716 "lineWidth": 1, 1717 "pointSize": 5, 1718 "scaleDistribution": { 1719 "type": "linear" 1720 }, 1721 "showPoints": "auto", 1722 "spanNulls": false, 1723 "stacking": { 1724 "group": "A", 1725 "mode": "none" 1726 }, 1727 "thresholdsStyle": { 1728 "mode": "off" 1729 } 1730 }, 1731 "mappings": [], 1732 "thresholds": { 1733 "mode": "absolute", 1734 "steps": [ 1735 { 1736 "color": "green", 1737 "value": null 1738 }, 1739 { 1740 "color": "red", 1741 "value": 80 1742 } 1743 ] 1744 }, 1745 "unit": "percent" 1746 }, 1747 "overrides": [ 1748 { 1749 "__systemRef": "hideSeriesFrom", 1750 "matcher": { 1751 "id": "byNames", 1752 "options": { 1753 "mode": "exclude", 1754 "names": [ 1755 "host - banana-shard-00-01.faplr.mmscloudteam.com" 1756 ], 1757 "prefix": "All except:", 1758 "readOnly": true 1759 } 1760 }, 1761 "properties": [ 1762 { 1763 "id": "custom.hideFrom", 1764 "value": { 1765 "legend": false, 1766 "tooltip": false, 1767 "viz": true 1768 } 1769 } 1770 ] 1771 } 1772 ] 1773 }, 1774 "gridPos": { 1775 "h": 7, 1776 "w": 5, 1777 "x": 0, 1778 "y": 39 1779 }, 1780 "id": 46, 1781 "options": { 1782 "legend": { 1783 "calcs": [], 1784 "displayMode": "list", 1785 "placement": "bottom" 1786 }, 1787 "tooltip": { 1788 "mode": "single" 1789 } 1790 }, 1791 "targets": [ 1792 { 1793 "exemplar": true, 1794 "expr": "label_replace( sum(rate(hardware_system_cpu_steal_milliseconds{group_id=~\"$group_id\", instance=~\"$host.*\"}[$interval]) / (10 * hardware_platform_num_logical_cpus{group_id=~\"$group_id\", instance=~\"$host.*\"})) by (instance) , \"hostname\", \"$1\", \"instance\", \"(.*):.*\")", 1795 "interval": "", 1796 "legendFormat": "host - {{hostname}}", 1797 "refId": "A" 1798 } 1799 ], 1800 "title": "Normalized System cpu - steal", 1801 "type": "timeseries" 1802 }, 1803 { 1804 "datasource": null, 1805 "description": "The percentage of time the CPU spent servicing guest, which is included in user. It is scaled to a range of 0-100% by dividing by the number of CPU cores.\n", 1806 "fieldConfig": { 1807 "defaults": { 1808 "color": { 1809 "mode": "palette-classic" 1810 }, 1811 "custom": { 1812 "axisLabel": "", 1813 "axisPlacement": "auto", 1814 "barAlignment": 0, 1815 "drawStyle": "line", 1816 "fillOpacity": 0, 1817 "gradientMode": "none", 1818 "hideFrom": { 1819 "legend": false, 1820 "tooltip": false, 1821 "viz": false 1822 }, 1823 "lineInterpolation": "linear", 1824 "lineWidth": 1, 1825 "pointSize": 5, 1826 "scaleDistribution": { 1827 "type": "linear" 1828 }, 1829 "showPoints": "auto", 1830 "spanNulls": false, 1831 "stacking": { 1832 "group": "A", 1833 "mode": "none" 1834 }, 1835 "thresholdsStyle": { 1836 "mode": "off" 1837 } 1838 }, 1839 "mappings": [], 1840 "thresholds": { 1841 "mode": "absolute", 1842 "steps": [ 1843 { 1844 "color": "green", 1845 "value": null 1846 }, 1847 { 1848 "color": "red", 1849 "value": 80 1850 } 1851 ] 1852 }, 1853 "unit": "percent" 1854 }, 1855 "overrides": [] 1856 }, 1857 "gridPos": { 1858 "h": 7, 1859 "w": 5, 1860 "x": 5, 1861 "y": 39 1862 }, 1863 "id": 47, 1864 "options": { 1865 "legend": { 1866 "calcs": [], 1867 "displayMode": "list", 1868 "placement": "bottom" 1869 }, 1870 "tooltip": { 1871 "mode": "single" 1872 } 1873 }, 1874 "targets": [ 1875 { 1876 "exemplar": true, 1877 "expr": "label_replace( sum(rate(hardware_system_cpu_guest_milliseconds{group_id=~\"$group_id\", instance=~\"$host.*\"}[$interval]) / (10 * hardware_platform_num_logical_cpus{group_id=~\"$group_id\", instance=~\"$host.*\"})) by (instance) , \"hostname\", \"$1\", \"instance\", \"(.*):.*\")", 1878 "interval": "", 1879 "legendFormat": "host - {{hostname}}", 1880 "refId": "A" 1881 } 1882 ], 1883 "title": "Normalized System cpu - guest", 1884 "type": "timeseries" 1885 }, 1886 { 1887 "datasource": null, 1888 "description": "The percentage of time the CPU spent performing software interrupts. It is scaled to a range of 0-100% by dividing by the number of CPU cores.\n", 1889 "fieldConfig": { 1890 "defaults": { 1891 "color": { 1892 "mode": "palette-classic" 1893 }, 1894 "custom": { 1895 "axisLabel": "", 1896 "axisPlacement": "auto", 1897 "barAlignment": 0, 1898 "drawStyle": "line", 1899 "fillOpacity": 0, 1900 "gradientMode": "none", 1901 "hideFrom": { 1902 "legend": false, 1903 "tooltip": false, 1904 "viz": false 1905 }, 1906 "lineInterpolation": "linear", 1907 "lineWidth": 1, 1908 "pointSize": 5, 1909 "scaleDistribution": { 1910 "type": "linear" 1911 }, 1912 "showPoints": "auto", 1913 "spanNulls": false, 1914 "stacking": { 1915 "group": "A", 1916 "mode": "none" 1917 }, 1918 "thresholdsStyle": { 1919 "mode": "off" 1920 } 1921 }, 1922 "mappings": [], 1923 "thresholds": { 1924 "mode": "absolute", 1925 "steps": [ 1926 { 1927 "color": "green", 1928 "value": null 1929 }, 1930 { 1931 "color": "red", 1932 "value": 80 1933 } 1934 ] 1935 }, 1936 "unit": "percent" 1937 }, 1938 "overrides": [] 1939 }, 1940 "gridPos": { 1941 "h": 7, 1942 "w": 5, 1943 "x": 10, 1944 "y": 39 1945 }, 1946 "id": 48, 1947 "options": { 1948 "legend": { 1949 "calcs": [], 1950 "displayMode": "list", 1951 "placement": "bottom" 1952 }, 1953 "tooltip": { 1954 "mode": "single" 1955 } 1956 }, 1957 "targets": [ 1958 { 1959 "exemplar": true, 1960 "expr": "label_replace( sum(rate(hardware_system_cpu_soft_irq_milliseconds{group_id=~\"$group_id\", instance=~\"$host.*\"}[$interval]) / (10 * hardware_platform_num_logical_cpus{group_id=~\"$group_id\", instance=~\"$host.*\"})) by (instance) , \"hostname\", \"$1\", \"instance\", \"(.*):.*\")", 1961 "interval": "", 1962 "legendFormat": "host - {{hostname}}", 1963 "refId": "A" 1964 } 1965 ], 1966 "title": "Normalized System cpu - softirq", 1967 "type": "timeseries" 1968 }, 1969 { 1970 "datasource": null, 1971 "description": "The percentage of time the CPU spent performing hardware interrupts. 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4030 "queryValue": "", 4031 "refresh": 1, 4032 "regex": "", 4033 "skipUrlSync": false, 4034 "type": "datasource" 4035 }, 4036 { 4037 "allValue": null, 4038 "current": { 4039 "selected": false, 4040 "text": "611c15fc5851c22d37e3f351", 4041 "value": "611c15fc5851c22d37e3f351" 4042 }, 4043 "datasource": null, 4044 "definition": "label_values(group_id)", 4045 "description": null, 4046 "error": null, 4047 "hide": 0, 4048 "includeAll": false, 4049 "label": "Group Id", 4050 "multi": false, 4051 "name": "group_id", 4052 "options": [], 4053 "query": { 4054 "query": "label_values(group_id)", 4055 "refId": "StandardVariableQuery" 4056 }, 4057 "refresh": 1, 4058 "regex": "", 4059 "skipUrlSync": false, 4060 "sort": 0, 4061 "type": "query" 4062 }, 4063 { 4064 "allValue": null, 4065 "current": { 4066 "selected": false, 4067 "text": "Cluster0", 4068 "value": "Cluster0" 4069 }, 4070 "datasource": null, 4071 "definition": "label_values(mongodb_up{group_id='$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": [], 4080 "query": { 4081 "query": "label_values(mongodb_up{group_id='$group_id'}, cluster_name)", 4082 "refId": "StandardVariableQuery" 4083 }, 4084 "refresh": 2, 4085 "regex": "", 4086 "skipUrlSync": false, 4087 "sort": 0, 4088 "type": "query" 4089 }, 4090 { 4091 "allValue": null, 4092 "current": { 4093 "selected": true, 4094 "text": [ 4095 "All" 4096 ], 4097 "value": [ 4098 "$__all" 4099 ] 4100 }, 4101 "datasource": null, 4102 "definition": "label_values(mongodb_up{group_id='$group_id', cluster_name='$cluster_name'}, replica_set_name)", 4103 "description": null, 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": { 4112 "query": "label_values(mongodb_up{group_id='$group_id', 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"text": "1m", 4190 "value": "1m" 4191 }, 4192 "description": null, 4193 "error": null, 4194 "hide": 0, 4195 "label": "Interval", 4196 "name": "interval", 4197 "options": [ 4198 { 4199 "selected": false, 4200 "text": "auto", 4201 "value": "$__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 - Atlas - new", 4249 "uid": "7LTNNcpnzsasddsd", 4250 "version": 1 4251 }
To learn more about importing Grafana dashboards, see the Grafana documentation.
Performance Metrics Available to Prometheus
The following metrics are available when you use the Prometheus integration with your MongoDB Atlas cluster:
serverStatus metrics
replSetStatus metrics
MongoDB Metric Labels
Each MongoDB metric contains the following labels:
Label | Description |
|---|---|
group_id | Unique hexadecimal digit string that identifies the project. |
org_id | Unique hexadecimal digit string that identifies the organization. |
cl_role | Human readable label that defines the cluster role. |
cl_name | Human-readable label that identifies the cluster. |
rs_nm | Human-readable label that identifies the replica set. |
rs_state | Number that indicates the replica set state. |
process_port | Port on which the process runs. |
MongoDB Information Metrics
mongodb_info is a gauge that always has the value of 1. This
metric contains all the MongoDB Metric Labels and
also the following labels:
Label | Description |
|---|---|
mongodb_version | String that represents the major, minor, and patch versions. |
replica_state_name | String that indicates the replica set member status. |
process_type | String that indicates the process running. Its values can be
mongod, mongos, or config. |
Hardware Metrics
Note
You can also view descriptions of each hardware metric in the Prometheus expression browser.
Name | Operating System | Type | Description |
|---|---|---|---|
hardware_system_cpu_nice | Unix, Darwin | Counter | Time spent in user mode with low priority. |
hardware_system_cpu_io_wait | Unix | Counter | Time waiting for I/O to complete. |
hardware_system_cpu_irq | Unix | Counter | Time spent servicing interrupts. |
hardware_system_cpu_soft_irq | Unix | Counter | Time spent servicing softirq's. |
hardware_system_cpu_steal | Unix | Counter | Time spent in other operating systems when running in a virtual
environment. |
hardware_system_cpu_guest | Unix | Counter | Time spent running a virtual CPU for the guest operating systems under the control of the Linux kernel. |
hardware_system_cpu_guest_nice | Unix | Counter | Time spent running a guest with an adjusted niceness. |
hardware_system_cpu_kernel_milliseconds | All | Counter | Time spent in system mode. |
hardware_system_cpu_user_milliseconds | All | Counter | Time spent in user mode. |
hardware_disk_metrics_weighted_time_io | Unix | Counter | Weighted time spent doing I/O's. |
hardware_disk_metrics_physical_write_count | Unix | Counter | Number of physical write I/O's processed. |
hardware_disk_metrics_physical_read_count | Unix | Counter | Number of physical read I/O's processed. |
hardware_disk_metrics_total_time | Unix | Counter | Total time this block device is active. |
hardware_disk_metrics_idle_time | Windows | Counter | Time spent in the idle task. |
hardware_disk_metrics_disk_space_free_bytes | All | Gauge | Disk space available in the mounted file system. |
hardware_disk_metrics_disk_space_used_bytes | All | Gauge | Disk space used in the mounted file system. |
hardware_disk_metrics_read_count | All | Counter | Number of read I/O's processed. |
hardware_disk_metrics_read_time_milliseconds | All | Counter | Total wait time for read requests. |
hardware_disk_metrics_write_count | All | Counter | Number of write I/O's processed. |
hardware_disk_metrics_write_time_milliseconds | All | Counter | Total wait time for write requests. |
hardware_process_cpu_children_user | Unix | Counter | Amount of time scheduled in user mode for this process to wait for children. |
hardware_process_cpu_children_kernel | Unix | Counter | Amount of time scheduled in kernel mode for this process to wait for children. |
hardware_process_cpu_kernel_milliseconds | All | Counter | Amount of time scheduled in kernel mode for this process. |
hardware_process_cpu_user_milliseconds | All | Counter | Amount of time scheduled in user mode for this process. |
hardware_system_vm_page_swap_in | Unix | Counter | Number of pages the system has swapped in from disk. |
hardware_system_vm_page_swap_out | Unix | Counter | Number of pages the system has swapped out to disk. |
hardware_system_memory_mem_total | Unix | Gauge | Total usable RAM (physical RAM minus a few reserved bits and the kernel binary code). |
hardware_system_memory_mem_free | Unix | Gauge | Sum of LowFree + HighFree. |
hardware_system_memory_mem_available | Unix | Gauge | An estimate of how much memory is available for starting new applications, without swapping. |
hardware_system_memory_buffers | Unix | Gauge | Temporary storage for raw disk blocks that shouldn't get tremendously large. |
hardware_system_memory_cached | Unix | Gauge | In-memory cache for files read from the disk. This doesn't include SwapCached. |
hardware_system_memory_swap_total | Unix | Gauge | Total amount of swap space available. |
hardware_system_memory_swap_free | Unix | Gauge | Total amount of swap space unused. |
hardware_system_memory_shared_mem | Unix | Gauge | Amount of memory consumed in file systems whose contents reside in virtual memory. |
hardware_system_memory_swap_free_kilobytes | All | Gauge | Total amount of swap space unused. |
hardware_system_memory_swap_total_kilobytes | All | Gauge | Total amount of swap space available. |
hardware_platform_num_logical_cpus | All | Gauge | Number of logical CPUs usable by the current process. |
hardware_system_network_eth0_bytes_in_bytes | All | Counter | Number of bytes of data received by the interface. |
hardware_system_network_eth0_bytes_out_bytes | All | Counter | Number of bytes of data transmitted by the interface. |
hardware_system_network_lo_bytes_in_bytes | All | Counter | Number of bytes of data received by the interface. |
hardware_system_network_lo_bytes_out_bytes | All | Counter | Number of bytes of data transmitted by the interface. |
Hardware Metric Labels
Each hardware metric contains the following labels:
Label | Description |
|---|---|
group_id | Unique hexadecimal digit string that identifies the project. |
org_id | Unique hexadecimal digit string that identifies the organization. |
process_port | Port on which the process runs. |
disk_name | Human-readable label that identifies the disk. |