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' This example assumes the Chilkat API to have been previously unlocked.
' See Global Unlock Sample for sample code.
Dim http As New Chilkat.Http
Dim success As Boolean
' Use this online tool to generate code from sample JSON: Generate Code to Create JSON
' The following JSON is sent in the request body.
' {
' "message": "You may need to add web hosts if this is consistently high.",
' "name": "Bytes received on host0",
' "options": {
' "no_data_timeframe": 20,
' "notify_no_data": true
' },
' "query": "avg(last_5m):sum:system.net.bytes_rcvd{host:host0} > 100",
' "tags": [
' "app:webserver",
' "frontend"
' ],
' "type": "query alert"
' }
Dim json As New Chilkat.JsonObject
json.UpdateString("message","You may need to add web hosts if this is consistently high.")
json.UpdateString("name","Bytes received on host0")
json.UpdateInt("options.no_data_timeframe",20)
json.UpdateBool("options.notify_no_data",True)
json.UpdateString("query","avg(last_5m):sum:system.net.bytes_rcvd{host:host0} > 100")
json.UpdateString("tags[0]","app:webserver")
json.UpdateString("tags[1]","frontend")
json.UpdateString("type","query alert")
http.SetRequestHeader("Content-Type","application/json")
http.SetRequestHeader("Accept","application/json")
Dim resp As Chilkat.HttpResponse = http.PostJson3("https://api.app.ddog-gov.com/api/v1/monitor","application/json",json)
If (http.LastMethodSuccess = False) Then
Debug.WriteLine(http.LastErrorText)
Exit Sub
End If
Dim sbResponseBody As New Chilkat.StringBuilder
resp.GetBodySb(sbResponseBody)
Dim jResp As New Chilkat.JsonObject
jResp.LoadSb(sbResponseBody)
jResp.EmitCompact = False
Debug.WriteLine("Response Body:")
Debug.WriteLine(jResp.Emit())
Dim respStatusCode As Integer = resp.StatusCode
Debug.WriteLine("Response Status Code = " & respStatusCode)
If (respStatusCode >= 400) Then
Debug.WriteLine("Response Header:")
Debug.WriteLine(resp.Header)
Debug.WriteLine("Failed.")
Exit Sub
End If
' Sample JSON response:
' (Sample code for parsing the JSON response is shown below)
' {
' "type": "query alert",
' "query": "avg(last_5m):sum:system.net.bytes_rcvd{host:host0} > 100",
' "created": "1989-12-01T14:28:43.831Z",
' "creator": {
' "email": "officia sunt",
' "handle": "pariatur",
' "name": "aute do"
' },
' "deleted": "2020-10-30T20:46:24.520Z",
' "id": -50675854,
' "matching_downtimes": [
' {
' "id": 1625,
' "end": 1412792983,
' "scope": [
' "env:staging"
' ],
' "start": 1412792983
' },
' {
' "id": 1625,
' "end": 1412792983,
' "scope": [
' "env:staging"
' ],
' "start": 1412792983
' }
' ],
' "message": "ullamco incididunt cupidatat",
' "modified": "1981-03-27T05:04:03.098Z",
' "multi": false,
' "name": "My monitor",
' "options": {
' "aggregation": {
' "group_by": "host",
' "metric": "metrics.name",
' "type": "count"
' },
' "device_ids": [
' "mobile_small",
' "chrome.tablet"
' ],
' "enable_logs_sample": false,
' "enable_samples": false,
' "escalation_message": "none",
' "evaluation_delay": -52819274,
' "group_retention_duration": "dolor Lorem qui",
' "groupby_simple_monitor": false,
' "include_tags": true,
' "locked": false,
' "min_failure_duration": 0,
' "min_location_failed": 1,
' "new_group_delay": -94315945,
' "new_host_delay": 300,
' "no_data_timeframe": -86360342,
' "notification_preset_name": "show_all",
' "notify_audit": false,
' "notify_by": [
' "labore dolore",
' "deserunt commodo consectetur"
' ],
' "notify_no_data": false,
' "on_missing_data": "resolve",
' "renotify_interval": null,
' "renotify_occurrences": 56355858,
' "renotify_statuses": [
' "warn",
' "no data"
' ],
' "require_full_window": false,
' "scheduling_options": {
' "evaluation_window": {
' "day_starts": "04:00",
' "hour_starts": 0,
' "month_starts": 1
' }
' },
' "silenced": {
' "non_6f_": 77287100
' },
' "synthetics_check_id": "culpa in laborum irure",
' "threshold_windows": {
' "recovery_window": "culpa cupidatat Lorem ut",
' "trigger_window": "fugiat officia mollit esse quis"
' },
' "thresholds": {
' "critical": -44507487.0891542,
' "critical_recovery": 94365870.17342958,
' "ok": 26645340.31156695,
' "unknown": -32772943.396166816,
' "warning": 75330874.10211122,
' "warning_recovery": 30665996.226613894
' },
' "timeout_h": null,
' "variables": [
' {
' "data_source": "rum",
' "compute": {
' "aggregation": "avg",
' "interval": 60000,
' "metric": "@duration"
' },
' "name": "query_errors",
' "group_by": [
' {
' "facet": "status",
' "limit": 10,
' "sort": {
' "aggregation": "avg",
' "metric": "minim tempor i",
' "order": "desc"
' }
' },
' {
' "facet": "status",
' "limit": 10,
' "sort": {
' "aggregation": "avg",
' "metric": "Ut fugiat officia",
' "order": "desc"
' }
' }
' ],
' "indexes": [
' "days-3",
' "days-7"
' ],
' "search": {
' "query": "service:query"
' }
' },
' {
' "data_source": "rum",
' "compute": {
' "aggregation": "avg",
' "interval": 60000,
' "metric": "@duration"
' },
' "name": "query_errors",
' "group_by": [
' {
' "facet": "status",
' "limit": 10,
' "sort": {
' "aggregation": "avg",
' "metric": "do velit",
' "order": "desc"
' }
' },
' {
' "facet": "status",
' "limit": 10,
' "sort": {
' "aggregation": "avg",
' "metric": "amet proident anim in",
' "order": "desc"
' }
' }
' ],
' "indexes": [
' "days-3",
' "days-7"
' ],
' "search": {
' "query": "service:query"
' }
' }
' ]
' },
' "overall_state": "Warn",
' "priority": 1,
' "restricted_roles": [
' "enim qui cillum est",
' "quis ut"
' ],
' "state": {
' "groups": {
' "Lorem_1": {
' "last_nodata_ts": -12653992,
' "last_notified_ts": -66141067,
' "last_resolved_ts": 5643925,
' "last_triggered_ts": -6121593,
' "name": "dolore nulla i",
' "status": "OK"
' },
' "nisi_c43": {
' "last_nodata_ts": -66061060,
' "last_notified_ts": -86988012,
' "last_resolved_ts": -39919633,
' "last_triggered_ts": 13467862,
' "name": "Ut fugiat eiusmod anim",
' "status": "Ignored"
' },
' "minim_c": {
' "last_nodata_ts": 6509669,
' "last_notified_ts": 39348490,
' "last_resolved_ts": 13221088,
' "last_triggered_ts": 21889420,
' "name": "in velit Duis",
' "status": "Alert"
' }
' }
' },
' "tags": [
' "ex tempor",
' "enim veniam dolore"
' ]
' }
' Sample code for parsing the JSON response...
' Use this online tool to generate parsing code from sample JSON: Generate JSON Parsing Code
Dim v_end As Integer
Dim start As Integer
Dim j As Integer
Dim count_j As Integer
Dim strVal As String
Dim data_source As String
Dim Aggregation As String
Dim Interval As Integer
Dim computeMetric As String
Dim Query As String
Dim facet As String
Dim limit As Integer
Dim sortAggregation As String
Dim sortMetric As String
Dim Order As String
Dim v_type As String = jResp.StringOf("type")
Dim query As String = jResp.StringOf("query")
Dim created As String = jResp.StringOf("created")
Dim v_Email As String = jResp.StringOf("creator.email")
Dim Handle As String = jResp.StringOf("creator.handle")
Dim Name As String = jResp.StringOf("creator.name")
Dim deleted As String = jResp.StringOf("deleted")
Dim id As Integer = jResp.IntOf("id")
Dim message As String = jResp.StringOf("message")
Dim modified As String = jResp.StringOf("modified")
Dim multi As Boolean = jResp.BoolOf("multi")
Dim name As String = jResp.StringOf("name")
Dim Group_by As String = jResp.StringOf("options.aggregation.group_by")
Dim Metric As String = jResp.StringOf("options.aggregation.metric")
Dim v_Type As String = jResp.StringOf("options.aggregation.type")
Dim Enable_logs_sample As Boolean = jResp.BoolOf("options.enable_logs_sample")
Dim Enable_samples As Boolean = jResp.BoolOf("options.enable_samples")
Dim Escalation_message As String = jResp.StringOf("options.escalation_message")
Dim Evaluation_delay As Integer = jResp.IntOf("options.evaluation_delay")
Dim Group_retention_duration As String = jResp.StringOf("options.group_retention_duration")
Dim Groupby_simple_monitor As Boolean = jResp.BoolOf("options.groupby_simple_monitor")
Dim Include_tags As Boolean = jResp.BoolOf("options.include_tags")
Dim Locked As Boolean = jResp.BoolOf("options.locked")
Dim Min_failure_duration As Integer = jResp.IntOf("options.min_failure_duration")
Dim Min_location_failed As Integer = jResp.IntOf("options.min_location_failed")
Dim New_group_delay As Integer = jResp.IntOf("options.new_group_delay")
Dim New_host_delay As Integer = jResp.IntOf("options.new_host_delay")
Dim No_data_timeframe As Integer = jResp.IntOf("options.no_data_timeframe")
Dim Notification_preset_name As String = jResp.StringOf("options.notification_preset_name")
Dim Notify_audit As Boolean = jResp.BoolOf("options.notify_audit")
Dim Notify_no_data As Boolean = jResp.BoolOf("options.notify_no_data")
Dim On_missing_data As String = jResp.StringOf("options.on_missing_data")
Dim Renotify_interval As String = jResp.StringOf("options.renotify_interval")
Dim Renotify_occurrences As Integer = jResp.IntOf("options.renotify_occurrences")
Dim Require_full_window As Boolean = jResp.BoolOf("options.require_full_window")
Dim Day_starts As String = jResp.StringOf("options.scheduling_options.evaluation_window.day_starts")
Dim Hour_starts As Integer = jResp.IntOf("options.scheduling_options.evaluation_window.hour_starts")
Dim Month_starts As Integer = jResp.IntOf("options.scheduling_options.evaluation_window.month_starts")
Dim Non_6f_ As Integer = jResp.IntOf("options.silenced.non_6f_")
Dim Synthetics_check_id As String = jResp.StringOf("options.synthetics_check_id")
Dim Recovery_window As String = jResp.StringOf("options.threshold_windows.recovery_window")
Dim Trigger_window As String = jResp.StringOf("options.threshold_windows.trigger_window")
Dim Critical As String = jResp.StringOf("options.thresholds.critical")
Dim Critical_recovery As String = jResp.StringOf("options.thresholds.critical_recovery")
Dim Ok As String = jResp.StringOf("options.thresholds.ok")
Dim Unknown As String = jResp.StringOf("options.thresholds.unknown")
Dim Warning As String = jResp.StringOf("options.thresholds.warning")
Dim Warning_recovery As String = jResp.StringOf("options.thresholds.warning_recovery")
Dim Timeout_h As String = jResp.StringOf("options.timeout_h")
Dim overall_state As String = jResp.StringOf("overall_state")
Dim priority As Integer = jResp.IntOf("priority")
Dim Last_nodata_ts As Integer = jResp.IntOf("state.groups.Lorem_1.last_nodata_ts")
Dim Last_notified_ts As Integer = jResp.IntOf("state.groups.Lorem_1.last_notified_ts")
Dim Last_resolved_ts As Integer = jResp.IntOf("state.groups.Lorem_1.last_resolved_ts")
Dim Last_triggered_ts As Integer = jResp.IntOf("state.groups.Lorem_1.last_triggered_ts")
Dim Lorem_1Name As String = jResp.StringOf("state.groups.Lorem_1.name")
Dim Status As String = jResp.StringOf("state.groups.Lorem_1.status")
Dim Nisi_c43Last_nodata_ts As Integer = jResp.IntOf("state.groups.nisi_c43.last_nodata_ts")
Dim Nisi_c43Last_notified_ts As Integer = jResp.IntOf("state.groups.nisi_c43.last_notified_ts")
Dim Nisi_c43Last_resolved_ts As Integer = jResp.IntOf("state.groups.nisi_c43.last_resolved_ts")
Dim Nisi_c43Last_triggered_ts As Integer = jResp.IntOf("state.groups.nisi_c43.last_triggered_ts")
Dim Nisi_c43Name As String = jResp.StringOf("state.groups.nisi_c43.name")
Dim Nisi_c43Status As String = jResp.StringOf("state.groups.nisi_c43.status")
Dim Minim_cLast_nodata_ts As Integer = jResp.IntOf("state.groups.minim_c.last_nodata_ts")
Dim Minim_cLast_notified_ts As Integer = jResp.IntOf("state.groups.minim_c.last_notified_ts")
Dim Minim_cLast_resolved_ts As Integer = jResp.IntOf("state.groups.minim_c.last_resolved_ts")
Dim Minim_cLast_triggered_ts As Integer = jResp.IntOf("state.groups.minim_c.last_triggered_ts")
Dim Minim_cName As String = jResp.StringOf("state.groups.minim_c.name")
Dim Minim_cStatus As String = jResp.StringOf("state.groups.minim_c.status")
Dim i As Integer = 0
Dim count_i As Integer = jResp.SizeOfArray("matching_downtimes")
While i < count_i
jResp.I = i
id = jResp.IntOf("matching_downtimes[i].id")
v_end = jResp.IntOf("matching_downtimes[i].end")
start = jResp.IntOf("matching_downtimes[i].start")
j = 0
count_j = jResp.SizeOfArray("matching_downtimes[i].scope")
While j < count_j
jResp.J = j
strVal = jResp.StringOf("matching_downtimes[i].scope[j]")
j = j + 1
End While
i = i + 1
End While
i = 0
count_i = jResp.SizeOfArray("options.device_ids")
While i < count_i
jResp.I = i
strVal = jResp.StringOf("options.device_ids[i]")
i = i + 1
End While
i = 0
count_i = jResp.SizeOfArray("options.notify_by")
While i < count_i
jResp.I = i
strVal = jResp.StringOf("options.notify_by[i]")
i = i + 1
End While
i = 0
count_i = jResp.SizeOfArray("options.renotify_statuses")
While i < count_i
jResp.I = i
strVal = jResp.StringOf("options.renotify_statuses[i]")
i = i + 1
End While
i = 0
count_i = jResp.SizeOfArray("options.variables")
While i < count_i
jResp.I = i
data_source = jResp.StringOf("options.variables[i].data_source")
Aggregation = jResp.StringOf("options.variables[i].compute.aggregation")
Interval = jResp.IntOf("options.variables[i].compute.interval")
computeMetric = jResp.StringOf("options.variables[i].compute.metric")
name = jResp.StringOf("options.variables[i].name")
Query = jResp.StringOf("options.variables[i].search.query")
j = 0
count_j = jResp.SizeOfArray("options.variables[i].group_by")
While j < count_j
jResp.J = j
facet = jResp.StringOf("options.variables[i].group_by[j].facet")
limit = jResp.IntOf("options.variables[i].group_by[j].limit")
sortAggregation = jResp.StringOf("options.variables[i].group_by[j].sort.aggregation")
sortMetric = jResp.StringOf("options.variables[i].group_by[j].sort.metric")
Order = jResp.StringOf("options.variables[i].group_by[j].sort.order")
j = j + 1
End While
j = 0
count_j = jResp.SizeOfArray("options.variables[i].indexes")
While j < count_j
jResp.J = j
strVal = jResp.StringOf("options.variables[i].indexes[j]")
j = j + 1
End While
i = i + 1
End While
i = 0
count_i = jResp.SizeOfArray("restricted_roles")
While i < count_i
jResp.I = i
strVal = jResp.StringOf("restricted_roles[i]")
i = i + 1
End While
i = 0
count_i = jResp.SizeOfArray("tags")
While i < count_i
jResp.I = i
strVal = jResp.StringOf("tags[i]")
i = i + 1
End While
Curl Command
curl -X POST
-H "Content-Type: application/json"
-H "Accept: application/json"
-d '{
"message": "You may need to add web hosts if this is consistently high.",
"name": "Bytes received on host0",
"options": {
"no_data_timeframe": 20,
"notify_no_data": true
},
"query": "avg(last_5m):sum:system.net.bytes_rcvd{host:host0} > 100",
"tags": [
"app:webserver",
"frontend"
],
"type": "query alert"
}'
https://api.app.ddog-gov.com/api/v1/monitor
Postman Collection Item JSON
{
"name": "Create a monitor",
"request": {
"method": "POST",
"header": [
{
"key": "Content-Type",
"value": "application/json"
},
{
"key": "Accept",
"value": "application/json"
}
],
"body": {
"mode": "raw",
"raw": "{\n \"message\": \"You may need to add web hosts if this is consistently high.\",\n \"name\": \"Bytes received on host0\",\n \"options\": {\n \"no_data_timeframe\": 20,\n \"notify_no_data\": true\n },\n \"query\": \"avg(last_5m):sum:system.net.bytes_rcvd{host:host0} > 100\",\n \"tags\": [\n \"app:webserver\",\n \"frontend\"\n ],\n \"type\": \"query alert\"\n}",
"options": {
"raw": {
"headerFamily": "json",
"language": "json"
}
}
},
"url": {
"raw": "{{baseUrl}}/api/v1/monitor",
"host": [
"{{baseUrl}}"
],
"path": [
"api",
"v1",
"monitor"
]
},
"description": "Create a monitor using the specified options.\n\n#### Monitor Types\n\nThe type of monitor chosen from:\n\n- anomaly: `query alert`\n- APM: `query alert` or `trace-analytics alert`\n- composite: `composite`\n- custom: `service check`\n- event: `event alert`\n- forecast: `query alert`\n- host: `service check`\n- integration: `query alert` or `service check`\n- live process: `process alert`\n- logs: `log alert`\n- metric: `query alert`\n- network: `service check`\n- outlier: `query alert`\n- process: `service check`\n- rum: `rum alert`\n- SLO: `slo alert`\n- watchdog: `event alert`\n- event-v2: `event-v2 alert`\n- audit: `audit alert`\n- error-tracking: `error-tracking alert`\n- database-monitoring: `database-monitoring alert`\n\n**Note**: Synthetic monitors are created through the Synthetics API. See the [Synthetics API] (https://docs.datadoghq.com/api/latest/synthetics/) documentation for more information.\n\n#### Query Types\n\n##### Metric Alert Query\n\nExample: `time_aggr(time_window):space_aggr:metric{tags} [by {key}] operator #`\n\n- `time_aggr`: avg, sum, max, min, change, or pct_change\n- `time_window`: `last_#m` (with `#` between 1 and 10080 depending on the monitor type) or `last_#h`(with `#` between 1 and 168 depending on the monitor type) or `last_1d`, or `last_1w`\n- `space_aggr`: avg, sum, min, or max\n- `tags`: one or more tags (comma-separated), or *\n- `key`: a 'key' in key:value tag syntax; defines a separate alert for each tag in the group (multi-alert)\n- `operator`: <, <=, >, >=, ==, or !=\n- `#`: an integer or decimal number used to set the threshold\n\nIf you are using the `_change_` or `_pct_change_` time aggregator, instead use `change_aggr(time_aggr(time_window),\ntimeshift):space_aggr:metric{tags} [by {key}] operator #` with:\n\n- `change_aggr` change, pct_change\n- `time_aggr` avg, sum, max, min [Learn more](https://docs.datadoghq.com/monitors/create/types/#define-the-conditions)\n- `time_window` last\\_#m (between 1 and 2880 depending on the monitor type), last\\_#h (between 1 and 48 depending on the monitor type), or last_#d (1 or 2)\n- `timeshift` #m_ago (5, 10, 15, or 30), #h_ago (1, 2, or 4), or 1d_ago\n\nUse this to create an outlier monitor using the following query:\n`avg(last_30m):outliers(avg:system.cpu.user{role:es-events-data} by {host}, 'dbscan', 7) > 0`\n\n##### Service Check Query\n\nExample: `\"check\".over(tags).last(count).by(group).count_by_status()`\n\n- `check` name of the check, for example `datadog.agent.up`\n- `tags` one or more quoted tags (comma-separated), or \"*\". for example: `.over(\"env:prod\", \"role:db\")`; `over` cannot be blank.\n- `count` must be at greater than or equal to your max threshold (defined in the `options`). It is limited to 100.\nFor example, if you've specified to notify on 1 critical, 3 ok, and 2 warn statuses, `count` should be at least 3.\n- `group` must be specified for check monitors. Per-check grouping is already explicitly known for some service checks.\nFor example, Postgres integration monitors are tagged by `db`, `host`, and `port`, and Network monitors by `host`, `instance`, and `url`. See [Service Checks](https://docs.datadoghq.com/api/latest/service-checks/) documentation for more information.\n\n##### Event Alert Query\n\nExample: `events('sources:nagios status:error,warning priority:normal tags: \"string query\"').rollup(\"count\").last(\"1h\")\"`\n\n- `event`, the event query string:\n- `string_query` free text query to match against event title and text.\n- `sources` event sources (comma-separated).\n- `status` event statuses (comma-separated). Valid options: error, warn, and info.\n- `priority` event priorities (comma-separated). Valid options: low, normal, all.\n- `host` event reporting host (comma-separated).\n- `tags` event tags (comma-separated).\n- `excluded_tags` excluded event tags (comma-separated).\n- `rollup` the stats roll-up method. `count` is the only supported method now.\n- `last` the timeframe to roll up the counts. Examples: 45m, 4h. Supported timeframes: m, h and d. This value should not exceed 48 hours.\n\n**NOTE** The Event Alert Query is being deprecated and replaced by the Event V2 Alert Query. For more information, see the [Event Migration guide](https://docs.datadoghq.com/events/guides/migrating_to_new_events_features/).\n\n##### Event V2 Alert Query\n\nExample: `events(query).rollup(rollup_method[, measure]).last(time_window) operator #`\n\n- `query` The search query - following the [Log search syntax](https://docs.datadoghq.com/logs/search_syntax/).\n- `rollup_method` The stats roll-up method - supports `count`, `avg` and `cardinality`.\n- `measure` For `avg` and cardinality `rollup_method` - specify the measure or the facet name you want to use.\n- `time_window` #m (between 1 and 2880), #h (between 1 and 48).\n- `operator` `<`, `<=`, `>`, `>=`, `==`, or `!=`.\n- `#` an integer or decimal number used to set the threshold.\n\n##### Process Alert Query\n\nExample: `processes(search).over(tags).rollup('count').last(timeframe) operator #`\n\n- `search` free text search string for querying processes.\nMatching processes match results on the [Live Processes](https://docs.datadoghq.com/infrastructure/process/?tab=linuxwindows) page.\n- `tags` one or more tags (comma-separated)\n- `timeframe` the timeframe to roll up the counts. Examples: 10m, 4h. 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Valid options: `7d`, `30d`, `90d`.\n- `operator`: `>=` or `>`\n\n##### Audit Alert Query\n\nExample: `audits(query).rollup(rollup_method[, measure]).last(time_window) operator #`\n\n- `query` The search query - following the [Log search syntax](https://docs.datadoghq.com/logs/search_syntax/).\n- `rollup_method` The stats roll-up method - supports `count`, `avg` and `cardinality`.\n- `measure` For `avg` and cardinality `rollup_method` - specify the measure or the facet name you want to use.\n- `time_window` #m (between 1 and 2880), #h (between 1 and 48).\n- `operator` `<`, `<=`, `>`, `>=`, `==`, or `!=`.\n- `#` an integer or decimal number used to set the threshold.\n\n**NOTE** Only available on US1-FED and in closed beta on US1, EU, AP1, US3, and US5.\n\n##### CI Pipelines Alert Query\n\nExample: `ci-pipelines(query).rollup(rollup_method[, measure]).last(time_window) operator #`\n\n- `query` The search query - following the [Log search syntax](https://docs.datadoghq.com/logs/search_syntax/).\n- `rollup_method` The stats roll-up method - supports `count`, `avg`, and `cardinality`.\n- `measure` For `avg` and cardinality `rollup_method` - specify the measure or the facet name you want to use.\n- `time_window` #m (between 1 and 2880), #h (between 1 and 48).\n- `operator` `<`, `<=`, `>`, `>=`, `==`, or `!=`.\n- `#` an integer or decimal number used to set the threshold.\n\n**NOTE** CI Pipeline monitors are in alpha on US1, EU, AP1, US3, and US5.\n\n##### CI Tests Alert Query\n\nExample: `ci-tests(query).rollup(rollup_method[, measure]).last(time_window) operator #`\n\n- `query` The search query - following the [Log search syntax](https://docs.datadoghq.com/logs/search_syntax/).\n- `rollup_method` The stats roll-up method - supports `count`, `avg`, and `cardinality`.\n- `measure` For `avg` and cardinality `rollup_method` - specify the measure or the facet name you want to use.\n- `time_window` #m (between 1 and 2880), #h (between 1 and 48).\n- `operator` `<`, `<=`, `>`, `>=`, `==`, or `!=`.\n- `#` an integer or decimal number used to set the threshold.\n\n**NOTE** CI Test monitors are available only in closed beta on US1, EU, AP1, US3, and US5.\n\n##### Error Tracking Alert Query\n\nExample(RUM): `error-tracking-rum(query).rollup(rollup_method[, measure]).last(time_window) operator #`\nExample(APM Traces): `error-tracking-traces(query).rollup(rollup_method[, measure]).last(time_window) operator #`\n\n- `query` The search query - following the [Log search syntax](https://docs.datadoghq.com/logs/search_syntax/).\n- `rollup_method` The stats roll-up method - supports `count`, `avg`, and `cardinality`.\n- `measure` For `avg` and cardinality `rollup_method` - specify the measure or the facet name you want to use.\n- `time_window` #m (between 1 and 2880), #h (between 1 and 48).\n- `operator` `<`, `<=`, `>`, `>=`, `==`, or `!=`.\n- `#` an integer or decimal number used to set the threshold.\n\n**Database Monitoring Alert Query**\n\nExample: `database-monitoring(query).rollup(rollup_method[, measure]).last(time_window) operator #`\n\n- `query` The search query - following the [Log search syntax](https://docs.datadoghq.com/logs/search_syntax/).\n- `rollup_method` The stats roll-up method - supports `count`, `avg`, and `cardinality`.\n- `measure` For `avg` and cardinality `rollup_method` - specify the measure or the facet name you want to use.\n- `time_window` #m (between 1 and 2880), #h (between 1 and 48).\n- `operator` `<`, `<=`, `>`, `>=`, `==`, or `!=`.\n- `#` an integer or decimal number used to set the threshold.\n\n**NOTE** Database Monitoring monitors are in alpha on US1."
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