> ## Documentation Index
> Fetch the complete documentation index at: https://axiom.co/docs/llms.txt
> Use this file to discover all available pages before exploring further.
## Submitting Feedback
If you encounter incorrect, outdated, or confusing documentation on this page, submit feedback:
POST https://axiom.co/docs/feedback
```json
{
"path": "/restapi/endpoints/getMonitors",
"feedback": "Description of the issue"
}
```
Only submit feedback when you have something specific and actionable to report.
# List all monitors
> Lists all configured monitors. Returns an array of monitor configurations including their IDs and current status.
The API endpoint `/v2/monitors` only returns monitors for datasets that your API token has query access to. If the API returns an empty list, ensure your token has query permissions for the datasets used by your monitors.
## OpenAPI
````yaml v2 get /monitors
openapi: 3.0.0
info:
description: A public and stable API for interacting with axiom services
title: Axiom
termsOfService: http://axiom.co/terms
contact:
name: Axiom support team
url: https://axiom.co
email: hello@axiom.co
license:
name: Apache 2.0
url: https://www.apache.org/licenses/LICENSE-2.0.html
version: 2.0.0
servers:
- url: https://api.axiom.co/v2/
security:
- bearerAuth: []
paths:
/monitors:
get:
tags:
- Monitors
description: >-
Lists all configured monitors. Returns an array of monitor
configurations including their IDs and current status.
operationId: getMonitors
responses:
'200':
description: Monitor
content:
application/json:
schema:
type: array
items:
$ref: '#/components/schemas/MonitorWithId'
security:
- Auth:
- monitors|read
components:
schemas:
MonitorWithId:
description: Monitor configuration with its unique identifier
allOf:
- $ref: '#/components/schemas/Monitor'
- type: object
required:
- id
properties:
id:
description: Unique identifier for the monitor
type: string
example: mon_xyz789
Monitor:
description: >
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.
type: object
required:
- name
- type
properties:
alertOnNoData:
description: Whether to alert when no data is received
type: boolean
example: true
aplQuery:
description: |
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.
type: string
example: '| where severity = ''error'' | count() > 100'
columnName:
description: Name of the column to monitor
type: string
example: cpu_usage
compareDays:
description: Number of days to compare for anomaly detection
type: number
format: int64
maximum: 7
example: 7
createdAt:
description: Timestamp when the monitor was created
type: string
format: date-time
example: '2024-03-20T10:00:00Z'
createdBy:
description: ID of the user who created the monitor
type: string
example: usr_789xyz
description:
description: Detailed description of the monitor's purpose
type: string
example: Monitors CPU usage and alerts when it exceeds 90%
disabled:
description: Whether the monitor is currently disabled
type: boolean
example: false
disabledUntil:
description: Timestamp until when the monitor should remain disabled
type: string
format: date-time
example: '2024-04-01T00:00:00Z'
nullable: true
intervalMinutes:
description: |
How frequently the monitor should run, in minutes.
Minimum value is 1 minute.
type: integer
format: int64
minimum: 1
example: 5
mplQuery:
description: >
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.
type: string
example: test-metrics:http_request_duration_seconds
name:
description: Name of the monitor
type: string
example: Production CPU Monitor
notifierIds:
description: |
List of notifier IDs that will receive alerts.
Notifiers can be email, Slack, webhook endpoints, etc.
type: array
items:
type: string
example:
- notify_slack_prod
- notify_email_oncall
notifyByGroup:
description: Whether to group notifications
type: boolean
example: false
notifyEveryRun:
description: Whether to send notifications on every check
type: boolean
example: false
operator:
description: |
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
type: string
enum:
- Below
- BelowOrEqual
- Above
- AboveOrEqual
- AboveOrBelow
example: Above
rangeMinutes:
description: |
Time window to evaluate in each check, in minutes.
For example, "last 5 minutes of data"
type: integer
format: int64
minimum: 1
example: 5
resolvable:
description: Whether the alert can be manually resolved
type: boolean
example: true
secondDelay:
description: Delay in seconds before triggering the alert
type: number
format: int64
maximum: 86400
example: 300
skipResolved:
description: Whether to skip resolved alerts
type: boolean
example: false
threshold:
description: Threshold value for triggering the alert
type: number
format: double
x-omitempty: false
example: 90
tolerance:
description: Tolerance percentage for anomaly detection
type: number
maximum: 100
example: 10
triggerAfterNPositiveResults:
description: Number of positive results needed before triggering
type: number
format: int64
example: 2
triggerFromNRuns:
description: >
Number of consecutive check runs that must fail before triggering an
alert.
Use this to avoid alerting on temporary spikes.
type: number
format: int64
example: 3
type:
description: >
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
type: string
enum:
- Threshold
- MatchEvent
- AnomalyDetection
example: Threshold
securitySchemes:
bearerAuth:
type: http
scheme: bearer
description: >-
Authenticate using an API token or personal access token (PAT). Include
the token as a Bearer token: `Authorization: Bearer `. For more
information, see [Tokens](/reference/tokens).
Auth:
description: >-
Authenticate using an API token or personal access token (PAT). Include
the token as a Bearer token: `Authorization: Bearer `. For more
information, see [Tokens](/reference/tokens).
type: oauth2
flows:
authorizationCode:
authorizationUrl: https://accounts.google.com/o/oauth2/v2/auth
tokenUrl: https://www.googleapis.com/oauth2/v4/token
scopes: {}
````