Create monitor

Body

Configuration for a monitoring rule. Monitors can be configured to: - Check threshold values (e.g., CPU usage > 90%) - Match specific events in logs - Detect anomalies based on historical patterns Each monitor runs on a specified interval and can trigger notifications through configured notifiers.

application/json

Property	Type	Description
`alertOnNoData`	`boolean`	Whether to alert when no data is received
`aplQuery`	`string`	APL (Axiom Processing Language) query string used for monitoring. This query defines what data to analyze and how to process it. At least one of aplQuery or mplQuery must be provided.
`columnName`	`string`	Name of the column to monitor
`compareDays`	`number<int64>`	Number of days to compare for anomaly detection
`createdAt`	`string<date-time>`	Timestamp when the monitor was created
`createdBy`	`string`	ID of the user who created the monitor
`description`	`string`	Detailed description of the monitor's purpose
`disabled`	`boolean`	Whether the monitor is currently disabled
`disabledUntil`	`string<date-time>`	Timestamp until when the monitor should remain disabled
`intervalMinutes`	`integer<int64>`	How frequently the monitor should run, in minutes. Minimum value is 1 minute.
`mplQuery`	`string`	MPL (Metrics Processing Language) query string for metrics-based monitoring. Use this as an alternative to aplQuery for metrics datasets. At least one of aplQuery or mplQuery must be provided.
`name`	`string`Required	Name of the monitor
`notifierIds`	`string[]`	List of notifier IDs that will receive alerts. Notifiers can be email, Slack, webhook endpoints, etc.
`notifyByGroup`	`boolean`	Whether to group notifications
`notifyEveryRun`	`boolean`	Whether to send notifications on every check
`operator`	`string`	Comparison operator for threshold checks: - Below: Trigger when value < threshold - BelowOrEqual: Trigger when value <= threshold - Above: Trigger when value > threshold - AboveOrEqual: Trigger when value >= threshold - AboveOrBelow: Trigger when value is outside a range
`rangeMinutes`	`integer<int64>`	Time window to evaluate in each check, in minutes. For example, "last 5 minutes of data"
`resolvable`	`boolean`	Whether the alert can be manually resolved
`secondDelay`	`number<int64>`	Delay in seconds before triggering the alert
`skipResolved`	`boolean`	Whether to skip resolved alerts
`threshold`	`number<double>`	Threshold value for triggering the alert
`tolerance`	`number`	Tolerance percentage for anomaly detection
`triggerAfterNPositiveResults`	`number<int64>`	Number of positive results needed before triggering
`triggerFromNRuns`	`number<int64>`	Number of consecutive check runs that must fail before triggering an alert. Use this to avoid alerting on temporary spikes.
`type`	`string`Required	Type of monitoring check to perform: - Threshold: Compares a numeric value against a threshold - MatchEvent: Looks for specific events or patterns - AnomalyDetection: Identifies unusual patterns based on historical data
`updatedAt`	`string<date-time>`	Timestamp when the monitor was last updated

Request

curl -X POST 'https://api.axiom.co/v2/monitors' \
  -H 'Authorization: Bearer API_TOKEN' \
  -H 'Content-Type: application/json' \
  -d '{"alertOnNoData":true,"aplQuery":"| where severity = 'error' | count() > 100","columnName":"cpu_usage","compareDays":7,"createdAt":"2024-03-20T10:00:00Z","createdBy":"usr_789xyz","description":"Monitors CPU usage and alerts when it exceeds 90%","disabled":false,"disabledUntil":"2024-04-01T00:00:00Z","intervalMinutes":5,"mplQuery":"test-metrics:http_request_duration_seconds","name":"Production CPU Monitor","notifierIds":["notify_slack_prod","notify_email_oncall"],"notifyByGroup":false,"notifyEveryRun":false,"operator":"Above","rangeMinutes":5,"resolvable":true,"secondDelay":300,"skipResolved":false,"threshold":90,"tolerance":10,"triggerAfterNPositiveResults":2,"triggerFromNRuns":3,"type":"Threshold","updatedAt":"2024-03-20T10:30:00Z"}'

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API token RequiredRequest body application/json

Response

200Monitor

application/json