Back to Collection Items
require 'chilkat'
# This example assumes the Chilkat API to have been previously unlocked.
# See Global Unlock Sample for sample code.
http = Chilkat::CkHttp.new()
# 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"
# }
json = Chilkat::CkJsonObject.new()
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")
# resp is a CkHttpResponse
resp = http.PostJson3("https://api.app.ddog-gov.com/api/v1/monitor","application/json",json)
if (http.get_LastMethodSuccess() == false)
print http.lastErrorText() + "\n";
exit
end
sbResponseBody = Chilkat::CkStringBuilder.new()
resp.GetBodySb(sbResponseBody)
jResp = Chilkat::CkJsonObject.new()
jResp.LoadSb(sbResponseBody)
jResp.put_EmitCompact(false)
print "Response Body:" + "\n";
print jResp.emit() + "\n";
respStatusCode = resp.get_StatusCode()
print "Response Status Code = " + respStatusCode.to_s() + "\n";
if (respStatusCode >= 400)
print "Response Header:" + "\n";
print resp.header() + "\n";
print "Failed." + "\n";
exit
end
# 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
v_type = jResp.stringOf("type")
query = jResp.stringOf("query")
created = jResp.stringOf("created")
v_Email = jResp.stringOf("creator.email")
Handle = jResp.stringOf("creator.handle")
Name = jResp.stringOf("creator.name")
deleted = jResp.stringOf("deleted")
id = jResp.IntOf("id")
message = jResp.stringOf("message")
modified = jResp.stringOf("modified")
multi = jResp.BoolOf("multi")
name = jResp.stringOf("name")
Group_by = jResp.stringOf("options.aggregation.group_by")
Metric = jResp.stringOf("options.aggregation.metric")
v_Type = jResp.stringOf("options.aggregation.type")
Enable_logs_sample = jResp.BoolOf("options.enable_logs_sample")
Enable_samples = jResp.BoolOf("options.enable_samples")
Escalation_message = jResp.stringOf("options.escalation_message")
Evaluation_delay = jResp.IntOf("options.evaluation_delay")
Group_retention_duration = jResp.stringOf("options.group_retention_duration")
Groupby_simple_monitor = jResp.BoolOf("options.groupby_simple_monitor")
Include_tags = jResp.BoolOf("options.include_tags")
Locked = jResp.BoolOf("options.locked")
Min_failure_duration = jResp.IntOf("options.min_failure_duration")
Min_location_failed = jResp.IntOf("options.min_location_failed")
New_group_delay = jResp.IntOf("options.new_group_delay")
New_host_delay = jResp.IntOf("options.new_host_delay")
No_data_timeframe = jResp.IntOf("options.no_data_timeframe")
Notification_preset_name = jResp.stringOf("options.notification_preset_name")
Notify_audit = jResp.BoolOf("options.notify_audit")
Notify_no_data = jResp.BoolOf("options.notify_no_data")
On_missing_data = jResp.stringOf("options.on_missing_data")
Renotify_interval = jResp.stringOf("options.renotify_interval")
Renotify_occurrences = jResp.IntOf("options.renotify_occurrences")
Require_full_window = jResp.BoolOf("options.require_full_window")
Day_starts = jResp.stringOf("options.scheduling_options.evaluation_window.day_starts")
Hour_starts = jResp.IntOf("options.scheduling_options.evaluation_window.hour_starts")
Month_starts = jResp.IntOf("options.scheduling_options.evaluation_window.month_starts")
Non_6f_ = jResp.IntOf("options.silenced.non_6f_")
Synthetics_check_id = jResp.stringOf("options.synthetics_check_id")
Recovery_window = jResp.stringOf("options.threshold_windows.recovery_window")
Trigger_window = jResp.stringOf("options.threshold_windows.trigger_window")
Critical = jResp.stringOf("options.thresholds.critical")
Critical_recovery = jResp.stringOf("options.thresholds.critical_recovery")
Ok = jResp.stringOf("options.thresholds.ok")
Unknown = jResp.stringOf("options.thresholds.unknown")
Warning = jResp.stringOf("options.thresholds.warning")
Warning_recovery = jResp.stringOf("options.thresholds.warning_recovery")
Timeout_h = jResp.stringOf("options.timeout_h")
overall_state = jResp.stringOf("overall_state")
priority = jResp.IntOf("priority")
Last_nodata_ts = jResp.IntOf("state.groups.Lorem_1.last_nodata_ts")
Last_notified_ts = jResp.IntOf("state.groups.Lorem_1.last_notified_ts")
Last_resolved_ts = jResp.IntOf("state.groups.Lorem_1.last_resolved_ts")
Last_triggered_ts = jResp.IntOf("state.groups.Lorem_1.last_triggered_ts")
Lorem_1Name = jResp.stringOf("state.groups.Lorem_1.name")
Status = jResp.stringOf("state.groups.Lorem_1.status")
Nisi_c43Last_nodata_ts = jResp.IntOf("state.groups.nisi_c43.last_nodata_ts")
Nisi_c43Last_notified_ts = jResp.IntOf("state.groups.nisi_c43.last_notified_ts")
Nisi_c43Last_resolved_ts = jResp.IntOf("state.groups.nisi_c43.last_resolved_ts")
Nisi_c43Last_triggered_ts = jResp.IntOf("state.groups.nisi_c43.last_triggered_ts")
Nisi_c43Name = jResp.stringOf("state.groups.nisi_c43.name")
Nisi_c43Status = jResp.stringOf("state.groups.nisi_c43.status")
Minim_cLast_nodata_ts = jResp.IntOf("state.groups.minim_c.last_nodata_ts")
Minim_cLast_notified_ts = jResp.IntOf("state.groups.minim_c.last_notified_ts")
Minim_cLast_resolved_ts = jResp.IntOf("state.groups.minim_c.last_resolved_ts")
Minim_cLast_triggered_ts = jResp.IntOf("state.groups.minim_c.last_triggered_ts")
Minim_cName = jResp.stringOf("state.groups.minim_c.name")
Minim_cStatus = jResp.stringOf("state.groups.minim_c.status")
i = 0
count_i = jResp.SizeOfArray("matching_downtimes")
while i < count_i
jResp.put_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.put_J(j)
strVal = jResp.stringOf("matching_downtimes[i].scope[j]")
j = j + 1
end
i = i + 1
end
i = 0
count_i = jResp.SizeOfArray("options.device_ids")
while i < count_i
jResp.put_I(i)
strVal = jResp.stringOf("options.device_ids[i]")
i = i + 1
end
i = 0
count_i = jResp.SizeOfArray("options.notify_by")
while i < count_i
jResp.put_I(i)
strVal = jResp.stringOf("options.notify_by[i]")
i = i + 1
end
i = 0
count_i = jResp.SizeOfArray("options.renotify_statuses")
while i < count_i
jResp.put_I(i)
strVal = jResp.stringOf("options.renotify_statuses[i]")
i = i + 1
end
i = 0
count_i = jResp.SizeOfArray("options.variables")
while i < count_i
jResp.put_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.put_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
j = 0
count_j = jResp.SizeOfArray("options.variables[i].indexes")
while j < count_j
jResp.put_J(j)
strVal = jResp.stringOf("options.variables[i].indexes[j]")
j = j + 1
end
i = i + 1
end
i = 0
count_i = jResp.SizeOfArray("restricted_roles")
while i < count_i
jResp.put_I(i)
strVal = jResp.stringOf("restricted_roles[i]")
i = i + 1
end
i = 0
count_i = jResp.SizeOfArray("tags")
while i < count_i
jResp.put_I(i)
strVal = jResp.stringOf("tags[i]")
i = i + 1
end
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. Supported timeframes: s, m, h and d\n- `operator` <, <=, >, >=, ==, or !=\n- `#` an integer or decimal number used to set the threshold\n\n##### Logs Alert Query\n\nExample: `logs(query).index(index_name).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- `index_name` For multi-index organizations, the log index in which the request is performed.\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##### Composite Query\n\nExample: `12345 && 67890`, where `12345` and `67890` are the IDs of non-composite monitors\n\n* `name` [*required*, *default* = **dynamic, based on query**]: The name of the alert.\n* `message` [*required*, *default* = **dynamic, based on query**]: A message to include with notifications for this monitor.\nEmail notifications can be sent to specific users by using the same '@username' notation as events.\n* `tags` [*optional*, *default* = **empty list**]: A list of tags to associate with your monitor.\nWhen getting all monitor details via the API, use the `monitor_tags` argument to filter results by these tags.\nIt is only available via the API and isn't visible or editable in the Datadog UI.\n\n##### SLO Alert Query\n\nExample: `error_budget(\"slo_id\").over(\"time_window\") operator #`\n\n- `slo_id`: The alphanumeric SLO ID of the SLO you are configuring the alert for.\n- `time_window`: The time window of the SLO target you wish to alert on. 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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