67 KiB
67 KiB
| layout | title | parent | nav_order |
|---|---|---|---|
| default | Anomaly detection API | Anomaly detection | 1 |
Anomaly detection API
Use these anomaly detection operations to programmatically create and manage detectors.
Table of contents
- TOC {:toc}
Create anomaly detector
Introduced 1.0 {: .label .label-purple }
Creates an anomaly detector.
This command creates a single-flow detector named test-detector that finds anomalies based on the sum of the value field:
Request
POST _plugins/_anomaly_detection/detectors
{
"name": "test-detector",
"description": "Test detector",
"time_field": "timestamp",
"indices": [
"server_log*"
],
"feature_attributes": [
{
"feature_name": "test",
"feature_enabled": true,
"aggregation_query": {
"test": {
"sum": {
"field": "value"
}
}
}
}
],
"filter_query": {
"bool": {
"filter": [
{
"range": {
"value": {
"gt": 1
}
}
}
],
"adjust_pure_negative": true,
"boost": 1
}
},
"detection_interval": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"window_delay": {
"period": {
"interval": 1,
"unit": "Minutes"
}
}
}
Sample response
{
"_id": "VEHKTXwBwf_U8gjUXY2s",
"_version": 1,
"_seq_no": 5,
"anomaly_detector": {
"name": "test-detector",
"description": "Test detector",
"time_field": "timestamp",
"indices": [
"server_log*"
],
"filter_query": {
"bool": {
"filter": [
{
"range": {
"value": {
"from": 1,
"to": null,
"include_lower": false,
"include_upper": true,
"boost": 1
}
}
}
],
"adjust_pure_negative": true,
"boost": 1
}
},
"detection_interval": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"window_delay": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"shingle_size": 8,
"schema_version": 0,
"feature_attributes": [
{
"feature_id": "U0HKTXwBwf_U8gjUXY2m",
"feature_name": "test",
"feature_enabled": true,
"aggregation_query": {
"test": {
"sum": {
"field": "value"
}
}
}
}
],
"last_update_time": 1633392680364,
"user": {
"name": "admin",
"backend_roles": [
"admin"
],
"roles": [
"own_index",
"all_access"
],
"custom_attribute_names": [],
"user_requested_tenant": "__user__"
},
"detector_type": "SINGLE_ENTITY"
},
"_primary_term": 1
}
To create a high cardinality detector by specifying a category field:
Request
POST _plugins/_anomaly_detection/detectors
{
"name": "test-hc-detector",
"description": "Test detector",
"time_field": "timestamp",
"indices": [
"server_log*"
],
"feature_attributes": [
{
"feature_name": "test",
"feature_enabled": true,
"aggregation_query": {
"test": {
"sum": {
"field": "value"
}
}
}
}
],
"filter_query": {
"bool": {
"filter": [
{
"range": {
"value": {
"gt": 1
}
}
}
],
"adjust_pure_negative": true,
"boost": 1
}
},
"detection_interval": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"window_delay": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"category_field": [
"ip"
]
}
Sample response
{
"_id": "b0HRTXwBwf_U8gjUw43R",
"_version": 1,
"_seq_no": 6,
"anomaly_detector": {
"name": "test-hc-detector",
"description": "Test detector",
"time_field": "timestamp",
"indices": [
"server_log*"
],
"filter_query": {
"bool": {
"filter": [
{
"range": {
"value": {
"from": 1,
"to": null,
"include_lower": false,
"include_upper": true,
"boost": 1
}
}
}
],
"adjust_pure_negative": true,
"boost": 1
}
},
"detection_interval": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"window_delay": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"shingle_size": 8,
"schema_version": 0,
"feature_attributes": [
{
"feature_id": "bkHRTXwBwf_U8gjUw43K",
"feature_name": "test",
"feature_enabled": true,
"aggregation_query": {
"test": {
"sum": {
"field": "value"
}
}
}
}
],
"last_update_time": 1633393165265,
"category_field": [
"ip"
],
"user": {
"name": "admin",
"backend_roles": [
"admin"
],
"roles": [
"own_index",
"all_access"
],
"custom_attribute_names": [],
"user_requested_tenant": "__user__"
},
"detector_type": "MULTI_ENTITY"
},
"_primary_term": 1
}
You can specify a maximum of two category fields:
"category_field": [
"ip"
]
"category_field": [
"ip", "error_type"
]
You can specify the following options.
| Options | Description | Type | Required |
|---|---|---|---|
name |
The name of the detector. | string |
Yes |
description |
A description of the detector. | string |
Yes |
time_field |
The name of the time field. | string |
Yes |
indices |
A list of indices to use as the data source. | list |
Yes |
feature_attributes |
Specify a feature_name, set the enabled parameter to true, and specify an aggregation query. |
list |
Yes |
filter_query |
Provide an optional filter query for your feature. | object |
No |
detection_interval |
The time interval for your anomaly detector. | object |
Yes |
window_delay |
Add extra processing time for data collection. | object |
No |
category_field |
Categorizes or slices data with a dimension. Similar to GROUP BY in SQL. |
list |
No |
Get detector
Introduced 1.0 {: .label .label-purple }
Returns all information about a detector based on the detector_id.
Request
GET _plugins/_anomaly_detection/detectors/<detectorId>
Sample response
{
"_id": "VEHKTXwBwf_U8gjUXY2s",
"_version": 1,
"_primary_term": 1,
"_seq_no": 5,
"anomaly_detector": {
"name": "test-detector",
"description": "Test detector",
"time_field": "timestamp",
"indices": [
"server_log*"
],
"filter_query": {
"bool": {
"filter": [
{
"range": {
"value": {
"from": 1,
"to": null,
"include_lower": false,
"include_upper": true,
"boost": 1
}
}
}
],
"adjust_pure_negative": true,
"boost": 1
}
},
"detection_interval": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"window_delay": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"shingle_size": 8,
"schema_version": 0,
"feature_attributes": [
{
"feature_id": "U0HKTXwBwf_U8gjUXY2m",
"feature_name": "test",
"feature_enabled": true,
"aggregation_query": {
"test": {
"sum": {
"field": "value"
}
}
}
}
],
"last_update_time": 1633392680364,
"user": {
"name": "admin",
"backend_roles": [
"admin"
],
"roles": [
"own_index",
"all_access"
],
"custom_attribute_names": [],
"user_requested_tenant": "__user__"
},
"detector_type": "SINGLE_ENTITY"
}
}
Use job=true to get real-time analysis task information.
Request
GET _plugins/_anomaly_detection/detectors/<detectorId>?job=true
Sample response
{
"_id": "VEHKTXwBwf_U8gjUXY2s",
"_version": 1,
"_primary_term": 1,
"_seq_no": 5,
"anomaly_detector": {
"name": "test-detector",
"description": "Test detector",
"time_field": "timestamp",
"indices": [
"server_log*"
],
"filter_query": {
"bool": {
"filter": [
{
"range": {
"value": {
"from": 1,
"to": null,
"include_lower": false,
"include_upper": true,
"boost": 1
}
}
}
],
"adjust_pure_negative": true,
"boost": 1
}
},
"detection_interval": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"window_delay": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"shingle_size": 8,
"schema_version": 0,
"feature_attributes": [
{
"feature_id": "U0HKTXwBwf_U8gjUXY2m",
"feature_name": "test",
"feature_enabled": true,
"aggregation_query": {
"test": {
"sum": {
"field": "value"
}
}
}
}
],
"last_update_time": 1633392680364,
"user": {
"name": "admin",
"backend_roles": [
"admin"
],
"roles": [
"own_index",
"all_access"
],
"custom_attribute_names": [],
"user_requested_tenant": "__user__"
},
"detector_type": "SINGLE_ENTITY"
},
"anomaly_detector_job": {
"name": "VEHKTXwBwf_U8gjUXY2s",
"schedule": {
"interval": {
"start_time": 1633393656357,
"period": 1,
"unit": "Minutes"
}
},
"window_delay": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"enabled": true,
"enabled_time": 1633393656357,
"last_update_time": 1633393656357,
"lock_duration_seconds": 60,
"user": {
"name": "admin",
"backend_roles": [
"admin"
],
"roles": [
"own_index",
"all_access"
],
"custom_attribute_names": [],
"user_requested_tenant": "__user__"
}
}
}
Use task=true to get historical analysis task information.
You can set both job=true and task=true to get information for both real-time and historical analysis tasks.
Request
GET _plugins/_anomaly_detection/detectors/<detectorId>?task=true
Sample response
{
"_id": "VEHKTXwBwf_U8gjUXY2s",
"_version": 1,
"_primary_term": 1,
"_seq_no": 5,
"anomaly_detector": {
"name": "test-detector",
"description": "Test detector",
"time_field": "timestamp",
"indices": [
"server_log*"
],
"filter_query": {
"bool": {
"filter": [
{
"range": {
"value": {
"from": 1,
"to": null,
"include_lower": false,
"include_upper": true,
"boost": 1
}
}
}
],
"adjust_pure_negative": true,
"boost": 1
}
},
"detection_interval": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"window_delay": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"shingle_size": 8,
"schema_version": 0,
"feature_attributes": [
{
"feature_id": "U0HKTXwBwf_U8gjUXY2m",
"feature_name": "test",
"feature_enabled": true,
"aggregation_query": {
"test": {
"sum": {
"field": "value"
}
}
}
}
],
"last_update_time": 1633392680364,
"user": {
"name": "admin",
"backend_roles": [
"admin"
],
"roles": [
"own_index",
"all_access"
],
"custom_attribute_names": [],
"user_requested_tenant": "__user__"
},
"detector_type": "SINGLE_ENTITY"
},
"realtime_detection_task": {
"task_id": "nkTZTXwBjd8s6RK4QlMq",
"last_update_time": 1633393776375,
"started_by": "admin",
"error": "",
"state": "RUNNING",
"detector_id": "VEHKTXwBwf_U8gjUXY2s",
"task_progress": 0,
"init_progress": 1,
"execution_start_time": 1633393656362,
"is_latest": true,
"task_type": "REALTIME_SINGLE_ENTITY",
"coordinating_node": "SWD7ihu9TaaW1zKwFZNVNg",
"detector": {
"name": "test-detector",
"description": "Test detector",
"time_field": "timestamp",
"indices": [
"server_log*"
],
"filter_query": {
"bool": {
"filter": [
{
"range": {
"value": {
"from": 1,
"to": null,
"include_lower": false,
"include_upper": true,
"boost": 1
}
}
}
],
"adjust_pure_negative": true,
"boost": 1
}
},
"detection_interval": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"window_delay": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"shingle_size": 8,
"schema_version": 0,
"feature_attributes": [
{
"feature_id": "U0HKTXwBwf_U8gjUXY2m",
"feature_name": "test",
"feature_enabled": true,
"aggregation_query": {
"test": {
"sum": {
"field": "value"
}
}
}
}
],
"last_update_time": 1633392680364,
"user": {
"name": "admin",
"backend_roles": [
"admin"
],
"roles": [
"own_index",
"all_access"
],
"custom_attribute_names": [],
"user_requested_tenant": "__user__"
},
"detector_type": "SINGLE_ENTITY"
},
"estimated_minutes_left": 0,
"user": {
"name": "admin",
"backend_roles": [
"admin"
],
"roles": [
"own_index",
"all_access"
],
"custom_attribute_names": [],
"user_requested_tenant": "__user__"
}
},
"historical_analysis_task": {
"task_id": "99DaTXwB6HknB84StRN1",
"last_update_time": 1633393797040,
"started_by": "admin",
"state": "RUNNING",
"detector_id": "VEHKTXwBwf_U8gjUXY2s",
"task_progress": 0.89285713,
"init_progress": 1,
"current_piece": 1633328940000,
"execution_start_time": 1633393751412,
"is_latest": true,
"task_type": "HISTORICAL_SINGLE_ENTITY",
"coordinating_node": "SWD7ihu9TaaW1zKwFZNVNg",
"worker_node": "2Z4q22BySEyzakYt_A0A2A",
"detector": {
"name": "test-detector",
"description": "Test detector",
"time_field": "timestamp",
"indices": [
"server_log*"
],
"filter_query": {
"bool": {
"filter": [
{
"range": {
"value": {
"from": 1,
"to": null,
"include_lower": false,
"include_upper": true,
"boost": 1
}
}
}
],
"adjust_pure_negative": true,
"boost": 1
}
},
"detection_interval": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"window_delay": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"shingle_size": 8,
"schema_version": 0,
"feature_attributes": [
{
"feature_id": "U0HKTXwBwf_U8gjUXY2m",
"feature_name": "test",
"feature_enabled": true,
"aggregation_query": {
"test": {
"sum": {
"field": "value"
}
}
}
}
],
"last_update_time": 1633392680364,
"user": {
"name": "admin",
"backend_roles": [
"admin"
],
"roles": [
"own_index",
"all_access"
],
"custom_attribute_names": [],
"user_requested_tenant": "__user__"
},
"detector_type": "SINGLE_ENTITY"
},
"detection_date_range": {
"start_time": 1632788951329,
"end_time": 1633393751329
},
"user": {
"name": "admin",
"backend_roles": [
"admin"
],
"roles": [
"own_index",
"all_access"
],
"custom_attribute_names": [],
"user_requested_tenant": "__user__"
}
}
}
Update detector
Introduced 1.0 {: .label .label-purple }
Updates a detector with any changes, including the description or adding or removing of features. To update a detector, you need to first stop both real-time detection and historical analysis.
You can't update a category field. {: .note }
Request
PUT _plugins/_anomaly_detection/detectors/<detectorId>
{
"name": "test-detector",
"description": "Test update detector",
"time_field": "timestamp",
"indices": [
"server_log*"
],
"feature_attributes": [
{
"feature_name": "test",
"feature_enabled": true,
"aggregation_query": {
"test": {
"sum": {
"field": "value"
}
}
}
}
],
"filter_query": {
"bool": {
"filter": [
{
"range": {
"value": {
"gt": 1
}
}
}
],
"adjust_pure_negative": true,
"boost": 1
}
},
"detection_interval": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"window_delay": {
"period": {
"interval": 1,
"unit": "Minutes"
}
}
}
Sample response
{
"_id": "VEHKTXwBwf_U8gjUXY2s",
"_version": 2,
"_seq_no": 7,
"anomaly_detector": {
"name": "test-detector",
"description": "Test update detector",
"time_field": "timestamp",
"indices": [
"server_log*"
],
"filter_query": {
"bool": {
"filter": [
{
"range": {
"value": {
"from": 1,
"to": null,
"include_lower": false,
"include_upper": true,
"boost": 1
}
}
}
],
"adjust_pure_negative": true,
"boost": 1
}
},
"detection_interval": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"window_delay": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"shingle_size": 8,
"schema_version": 0,
"feature_attributes": [
{
"feature_id": "3kHiTXwBwf_U8gjUlY15",
"feature_name": "test",
"feature_enabled": true,
"aggregation_query": {
"test": {
"sum": {
"field": "value"
}
}
}
}
],
"last_update_time": 1633394267522,
"user": {
"name": "admin",
"backend_roles": [
"admin"
],
"roles": [
"own_index",
"all_access"
],
"custom_attribute_names": [],
"user_requested_tenant": "__user__"
},
"detector_type": "SINGLE_ENTITY"
},
"_primary_term": 1
}
Delete detector
Introduced 1.0 {: .label .label-purple }
Deletes a detector based on the detector_id.
To delete a detector, you need to first stop both real-time detection and historical analysis.
Request
DELETE _plugins/_anomaly_detection/detectors/<detectorId>
Sample response
{
"_index": ".opendistro-anomaly-detectors",
"_type": "_doc",
"_id": "70TxTXwBjd8s6RK4j1Pj",
"_version": 2,
"result": "deleted",
"forced_refresh": true,
"_shards": {
"total": 2,
"successful": 2,
"failed": 0
},
"_seq_no": 9,
"_primary_term": 1
}
Preview detector
Introduced 1.0 {: .label .label-purple }
Passes a date range to the anomaly detector to return any anomalies within that date range.
To preview a single-flow detector:
Request
POST _plugins/_anomaly_detection/detectors/<detectorId>/_preview
{
"period_start": 1633048868000,
"period_end": 1633394468000,
"detector": {
"name": "test-detector",
"description": "Test update detector",
"time_field": "timestamp",
"indices": [
"server_log*"
],
"feature_attributes": [
{
"feature_name": "test",
"feature_enabled": true,
"aggregation_query": {
"test": {
"sum": {
"field": "value"
}
}
}
}
],
"filter_query": {
"bool": {
"filter": [
{
"range": {
"value": {
"gt": 1
}
}
}
],
"adjust_pure_negative": true,
"boost": 1
}
},
"detection_interval": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"window_delay": {
"period": {
"interval": 1,
"unit": "Minutes"
}
}
}
}
Sample response
{
"anomaly_result": [
{
"detector_id": null,
"data_start_time": 1633049280000,
"data_end_time": 1633049340000,
"schema_version": 0,
"feature_data": [
{
"feature_id": "8EHmTXwBwf_U8gjU0Y0u",
"feature_name": "test",
"data": 0
}
],
"anomaly_grade": 0,
"confidence": 0
},
...
],
"anomaly_detector": {
"name": "test-detector",
"description": "Test update detector",
"time_field": "timestamp",
"indices": [
"server_log*"
],
"filter_query": {
"bool": {
"filter": [
{
"range": {
"value": {
"from": 1,
"to": null,
"include_lower": false,
"include_upper": true,
"boost": 1
}
}
}
],
"adjust_pure_negative": true,
"boost": 1
}
},
"detection_interval": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"window_delay": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"shingle_size": 8,
"schema_version": 0,
"feature_attributes": [
{
"feature_id": "8EHmTXwBwf_U8gjU0Y0u",
"feature_name": "test",
"feature_enabled": true,
"aggregation_query": {
"test": {
"sum": {
"field": "value"
}
}
}
}
],
"detector_type": "SINGLE_ENTITY"
}
}
If you specify a category field, each result is associated with an entity:
Request
POST _plugins/_anomaly_detection/detectors/<detectorId>/_preview
{
"period_start": 1633048868000,
"period_end": 1633394468000,
"detector": {
"name": "test-detector",
"description": "Test update detector",
"time_field": "timestamp",
"indices": [
"server_log*"
],
"feature_attributes": [
{
"feature_name": "test",
"feature_enabled": true,
"aggregation_query": {
"test": {
"sum": {
"field": "value"
}
}
}
}
],
"filter_query": {
"bool": {
"filter": [
{
"range": {
"value": {
"gt": 1
}
}
}
],
"adjust_pure_negative": true,
"boost": 1
}
},
"detection_interval": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"window_delay": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"category_field": [
"error_type"
]
}
}
Sample response
{
"anomaly_result": [
{
"detector_id": null,
"data_start_time": 1633049280000,
"data_end_time": 1633049340000,
"schema_version": 0,
"feature_data": [
{
"feature_id": "tkTpTXwBjd8s6RK4DlOZ",
"feature_name": "test",
"data": 0
}
],
"anomaly_grade": 0,
"confidence": 0,
"entity": [
{
"name": "error_type",
"value": "error1"
}
]
},
...
],
"anomaly_detector": {
"name": "test-detector",
"description": "Test update detector",
"time_field": "timestamp",
"indices": [
"server_log*"
],
"filter_query": {
"bool": {
"filter": [
{
"range": {
"value": {
"from": 1,
"to": null,
"include_lower": false,
"include_upper": true,
"boost": 1
}
}
}
],
"adjust_pure_negative": true,
"boost": 1
}
},
"detection_interval": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"window_delay": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"shingle_size": 8,
"schema_version": 0,
"feature_attributes": [
{
"feature_id": "tkTpTXwBjd8s6RK4DlOZ",
"feature_name": "test",
"feature_enabled": true,
"aggregation_query": {
"test": {
"sum": {
"field": "value"
}
}
}
}
],
"category_field": [
"error_type"
],
"detector_type": "MULTI_ENTITY"
}
}
You can preview a detector with the detector ID:
POST _plugins/_anomaly_detection/detectors/_preview
{
"detector_id": "VEHKTXwBwf_U8gjUXY2s",
"period_start": 1633048868000,
"period_end": 1633394468000
}
Or:
POST _opendistro/_anomaly_detection/detectors/VEHKTXwBwf_U8gjUXY2s/_preview
{
"period_start": 1633048868000,
"period_end": 1633394468000
}
Sample response
{
"anomaly_result": [
{
"detector_id": "VEHKTXwBwf_U8gjUXY2s",
"data_start_time": 1633049280000,
"data_end_time": 1633049340000,
"schema_version": 0,
"feature_data": [
{
"feature_id": "3kHiTXwBwf_U8gjUlY15",
"feature_name": "test",
"data": 0
}
],
"anomaly_grade": 0,
"confidence": 0,
"user": {
"name": "admin",
"backend_roles": [
"admin"
],
"roles": [
"own_index",
"all_access"
],
"custom_attribute_names": [],
"user_requested_tenant": "__user__"
}
},
...
],
"anomaly_detector": {
"name": "test-detector",
"description": "Test update detector",
"time_field": "timestamp",
"indices": [
"server_log*"
],
"filter_query": {
"bool": {
"filter": [
{
"range": {
"value": {
"from": 1,
"to": null,
"include_lower": false,
"include_upper": true,
"boost": 1
}
}
}
],
"adjust_pure_negative": true,
"boost": 1
}
},
"detection_interval": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"window_delay": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"shingle_size": 8,
"schema_version": 0,
"feature_attributes": [
{
"feature_id": "3kHiTXwBwf_U8gjUlY15",
"feature_name": "test",
"feature_enabled": true,
"aggregation_query": {
"test": {
"sum": {
"field": "value"
}
}
}
}
],
"last_update_time": 1633394267522,
"user": {
"name": "admin",
"backend_roles": [
"admin"
],
"roles": [
"own_index",
"all_access"
],
"custom_attribute_names": [],
"user_requested_tenant": "__user__"
},
"detector_type": "SINGLE_ENTITY"
}
}
Start detector job
Introduced 1.0 {: .label .label-purple }
Starts a real-time or historical anomaly detector job.
To start a real-time detector job:
Request
POST _plugins/_anomaly_detection/detectors/<detectorId>/_start
Sample response
{
"_id": "VEHKTXwBwf_U8gjUXY2s",
"_version": 3,
"_seq_no": 6,
"_primary_term": 1
}
The _id represents the real-time job ID, which is the same as the detector ID.
To start historical analysis:
POST _plugins/_anomaly_detection/detectors/<detectorId>/_start
{
"start_time": 1633048868000,
"end_time": 1633394468000
}
Sample response
{
"_id": "f9DsTXwB6HknB84SoRTY",
"_version": 1,
"_seq_no": 958,
"_primary_term": 1
}
The _id represents the historical batch task ID, which is a random universally unique identifier (UUID).
Stop detector job
Introduced 1.0 {: .label .label-purple }
Stops a real-time or historical anomaly detector job.
To stop a real-time detector job:
Request
POST _plugins/_anomaly_detection/detectors/<detectorId>/_stop
Sample response
{
"_id": "VEHKTXwBwf_U8gjUXY2s",
"_version": 0,
"_seq_no": 0,
"_primary_term": 0
}
To stop historical analysis:
POST _plugins/_anomaly_detection/detectors/<detectorId>/_stop?historical=true
Sample response
{
"_id": "f9DsTXwB6HknB84SoRTY",
"_version": 0,
"_seq_no": 0,
"_primary_term": 0
}
Search detector
Introduced 1.0 {: .label .label-purple }
Returns all anomaly detectors for a search query.
To search detectors using the server_log* index:
Request
GET _plugins/_anomaly_detection/detectors/_search
POST _plugins/_anomaly_detection/detectors/_search
{
"query": {
"wildcard": {
"indices": {
"value": "server_log*"
}
}
}
}
Sample response
{
"took": 2,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 4,
"relation": "eq"
},
"max_score": 1,
"hits": [
{
"_index": ".opendistro-anomaly-detectors",
"_type": "_doc",
"_id": "Zi5zTXwBwf_U8gjUTfJG",
"_version": 1,
"_seq_no": 1,
"_primary_term": 1,
"_score": 1,
"_source": {
"name": "test",
"description": "test",
"time_field": "timestamp",
"indices": [
"server_log"
],
"filter_query": {
"match_all": {
"boost": 1
}
},
"detection_interval": {
"period": {
"interval": 5,
"unit": "Minutes"
}
},
"window_delay": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"shingle_size": 8,
"schema_version": 0,
"feature_attributes": [
{
"feature_id": "ZS5zTXwBwf_U8gjUTfIn",
"feature_name": "test_feature",
"feature_enabled": true,
"aggregation_query": {
"test_feature": {
"sum": {
"field": "value"
}
}
}
}
],
"last_update_time": 1633386974533,
"category_field": [
"error_type"
],
"user": {
"name": "admin",
"backend_roles": [
"admin"
],
"roles": [
"own_index",
"all_access"
],
"custom_attribute_names": [],
"user_requested_tenant": "__user__"
},
"detector_type": "MULTI_ENTITY"
}
},
...
]
}
}
Search detector tasks
Introduced 1.1 {: .label .label-purple }
Searches detector tasks.
To search for the latest detector task for a high cardinality detector:
Request
GET _plugins/_anomaly_detection/detectors/tasks/_search
POST _plugins/_anomaly_detection/detectors/tasks/_search
{
"query": {
"bool": {
"filter": [
{
"term": {
"detector_id": "Zi5zTXwBwf_U8gjUTfJG"
}
},
{
"term": {
"task_type": "HISTORICAL_HC_DETECTOR"
}
},
{
"term": {
"is_latest": "true"
}
}
]
}
}
}
Sample response
{
"took": 1,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 1,
"relation": "eq"
},
"max_score": 0,
"hits": [
{
"_index": ".opendistro-anomaly-detection-state",
"_type": "_doc",
"_id": "fm-RTXwBYwCbWecgB753",
"_version": 34,
"_seq_no": 928,
"_primary_term": 1,
"_score": 0,
"_source": {
"detector_id": "Zi5zTXwBwf_U8gjUTfJG",
"error": "",
"detection_date_range": {
"start_time": 1630794960000,
"end_time": 1633386960000
},
"task_progress": 1,
"last_update_time": 1633389090738,
"execution_start_time": 1633388922742,
"state": "FINISHED",
"coordinating_node": "2Z4q22BySEyzakYt_A0A2A",
"task_type": "HISTORICAL_HC_DETECTOR",
"execution_end_time": 1633389090738,
"started_by": "admin",
"init_progress": 0,
"is_latest": true,
"detector": {
"category_field": [
"error_type"
],
"description": "test",
"ui_metadata": {
"features": {
"test_feature": {
"aggregationBy": "sum",
"aggregationOf": "value",
"featureType": "simple_aggs"
}
},
"filters": []
},
"feature_attributes": [
{
"feature_id": "ZS5zTXwBwf_U8gjUTfIn",
"feature_enabled": true,
"feature_name": "test_feature",
"aggregation_query": {
"test_feature": {
"sum": {
"field": "value"
}
}
}
}
],
"schema_version": 0,
"time_field": "timestamp",
"last_update_time": 1633386974533,
"indices": [
"server_log"
],
"window_delay": {
"period": {
"unit": "Minutes",
"interval": 1
}
},
"detection_interval": {
"period": {
"unit": "Minutes",
"interval": 5
}
},
"name": "testhc",
"filter_query": {
"match_all": {
"boost": 1
}
},
"shingle_size": 8,
"user": {
"backend_roles": [
"admin"
],
"custom_attribute_names": [],
"roles": [
"own_index",
"all_access"
],
"name": "admin",
"user_requested_tenant": "__user__"
},
"detector_type": "MULTI_ENTITY"
},
"user": {
"backend_roles": [
"admin"
],
"custom_attribute_names": [],
"roles": [
"own_index",
"all_access"
],
"name": "admin",
"user_requested_tenant": "__user__"
}
}
}
]
}
}
To search for the latest entity-level task for a high cardinality detector:
Request
GET _plugins/_anomaly_detection/detectors/tasks/_search
POST _plugins/_anomaly_detection/detectors/tasks/_search
{
"query": {
"bool": {
"filter": [
{
"term": {
"detector_id": "Zi5zTXwBwf_U8gjUTfJG"
}
},
{
"term": {
"task_type": "HISTORICAL_HC_ENTITY"
}
},
{
"term": {
"is_latest": "true"
}
}
]
}
},
"sort": [
{
"execution_start_time": {
"order": "desc"
}
}
],
"size": 100
}
To search for all entity-level batch task stats:
Request
GET _plugins/_anomaly_detection/detectors/tasks/_search
POST _plugins/_anomaly_detection/detectors/tasks/_search
{
"size": 0,
"query": {
"bool": {
"filter": [
{
"term": {
"detector_id": {
"value": "Zi5zTXwBwf_U8gjUTfJG",
"boost": 1
}
}
},
{
"term": {
"parent_task_id": {
"value": "fm-RTXwBYwCbWecgB753",
"boost": 1
}
}
},
{
"terms": {
"task_type": [
"HISTORICAL_HC_ENTITY"
],
"boost": 1
}
}
]
}
},
"aggs": {
"test": {
"terms": {
"field": "state",
"size": 100
}
}
}
}
Sample response
{
"took": 2,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 32,
"relation": "eq"
},
"max_score": null,
"hits": []
},
"aggregations": {
"test": {
"doc_count_error_upper_bound": 0,
"sum_other_doc_count": 0,
"buckets": [
{
"key": "FINISHED",
"doc_count": 32
}
]
}
}
}
Search detector result
Introduced 1.0 {: .label .label-purple }
Returns all results for a search query.
To search anomaly results for grade greater than 0 for real-time analysis:
Request
GET _plugins/_anomaly_detection/detectors/results/_search
POST _plugins/_anomaly_detection/detectors/results/_search
{
"query": {
"bool": {
"filter": [
{
"term": {
"detector_id": "Zi5zTXwBwf_U8gjUTfJG"
}
},
{
"range": {
"anomaly_grade": {
"gt": 0
}
}
}
],
"must_not": [
{
"exists": {
"field": "task_id"
}
}
]
}
}
}
Because real-time analysis doesn't have a batch task, the task ID in the anomaly result is null.
Sample response
{
"took": 4,
"timed_out": false,
"_shards": {
"total": 3,
"successful": 3,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 90,
"relation": "eq"
},
"max_score": 0,
"hits": [
{
"_index": ".opendistro-anomaly-results-history-2021.10.04-1",
"_type": "_doc",
"_id": "686KTXwB6HknB84SMr6G",
"_version": 1,
"_seq_no": 103622,
"_primary_term": 1,
"_score": 0,
"_source": {
"detector_id": "Zi5zTXwBwf_U8gjUTfJG",
"confidence": 0.918886275269358,
"model_id": "Zi5zTXwBwf_U8gjUTfJG_entity_error16",
"schema_version": 4,
"anomaly_score": 1.1093755891885446,
"execution_start_time": 1633388475001,
"data_end_time": 1633388414989,
"data_start_time": 1633388114989,
"feature_data": [
{
"feature_id": "ZS5zTXwBwf_U8gjUTfIn",
"feature_name": "test_feature",
"data": 0.532
}
],
"execution_end_time": 1633388475014,
"user": {
"backend_roles": [
"admin"
],
"custom_attribute_names": [],
"roles": [
"own_index",
"all_access"
],
"name": "admin",
"user_requested_tenant": "__user__"
},
"anomaly_grade": 0.031023547546561225,
"entity": [
{
"name": "error_type",
"value": "error16"
}
]
}
},
...
]
}
}
You can run historical analysis as many times as you like. So, multiple tasks might exist for the same detector.
You can search for the latest historical batch task first and then search the historical batch task results.
To search anomaly results for grade greater than 0 for historical analysis with the task_id:
Request
GET _plugins/_anomaly_detection/detectors/results/_search
POST _plugins/_anomaly_detection/detectors/results/_search
{
"query": {
"bool": {
"filter": [
{
"term": {
"detector_id": "Zi5zTXwBwf_U8gjUTfJG"
}
},
{
"range": {
"anomaly_grade": {
"gt": 0
}
}
},
{
"term": {
"task_id": "fm-RTXwBYwCbWecgB753"
}
}
]
}
}
}
Sample response
{
"took": 915,
"timed_out": false,
"_shards": {
"total": 3,
"successful": 3,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 4115,
"relation": "eq"
},
"max_score": 0,
"hits": [
{
"_index": ".opendistro-anomaly-results-history-2021.10.04-1",
"_type": "_doc",
"_id": "VRyRTXwBDx7vzPBV8jYC",
"_version": 1,
"_seq_no": 149657,
"_primary_term": 1,
"_score": 0,
"_source": {
"detector_id": "Zi5zTXwBwf_U8gjUTfJG",
"confidence": 0.9642989263957601,
"task_id": "fm-RTXwBYwCbWecgB753",
"model_id": "Zi5zTXwBwf_U8gjUTfJG_entity_error24",
"schema_version": 4,
"anomaly_score": 1.2260712437521946,
"execution_start_time": 1633388982692,
"data_end_time": 1631721300000,
"data_start_time": 1631721000000,
"feature_data": [
{
"feature_id": "ZS5zTXwBwf_U8gjUTfIn",
"feature_name": "test_feature",
"data": 10
}
],
"execution_end_time": 1633388982709,
"user": {
"backend_roles": [
"admin"
],
"custom_attribute_names": [],
"roles": [
"own_index",
"all_access"
],
"name": "admin",
"user_requested_tenant": "__user__"
},
"anomaly_grade": 0.14249628345655782,
"entity": [
{
"name": "error_type",
"value": "error1"
}
]
}
},
...
]
}
}
Get detector stats
Introduced 1.0 {: .label .label-purple }
Provides information about how the plugin is performing.
To get all stats:
Request
GET _plugins/_anomaly_detection/stats
Sample response
{
"anomaly_detectors_index_status": "green",
"anomaly_detection_state_status": "green",
"single_entity_detector_count": 2,
"detector_count": 5,
"multi_entity_detector_count": 3,
"anomaly_detection_job_index_status": "green",
"models_checkpoint_index_status": "green",
"anomaly_results_index_status": "green",
"nodes": {
"2Z4q22BySEyzakYt_A0A2A": {
"ad_execute_request_count": 95,
"models": [
{
"detector_id": "WTBnTXwBjd8s6RK4b1Sz",
"model_type": "rcf",
"last_used_time": 1633398197185,
"model_id": "WTBnTXwBjd8s6RK4b1Sz_model_rcf_0",
"last_checkpoint_time": 1633396573679
},
...
],
"ad_canceled_batch_task_count": 0,
"ad_hc_execute_request_count": 75,
"ad_hc_execute_failure_count": 0,
"model_count": 28,
"ad_execute_failure_count": 1,
"ad_batch_task_failure_count": 0,
"ad_total_batch_task_execution_count": 27,
"ad_executing_batch_task_count": 3
},
"SWD7ihu9TaaW1zKwFZNVNg": {
"ad_execute_request_count": 12,
"models": [
{
"detector_id": "Zi5zTXwBwf_U8gjUTfJG",
"model_type": "entity",
"last_used_time": 1633398375008,
"model_id": "Zi5zTXwBwf_U8gjUTfJG_entity_error13",
"last_checkpoint_time": 1633392973682,
"entity": [
{
"name": "error_type",
"value": "error13"
}
]
},
...
],
"ad_canceled_batch_task_count": 1,
"ad_hc_execute_request_count": 0,
"ad_hc_execute_failure_count": 0,
"model_count": 15,
"ad_execute_failure_count": 2,
"ad_batch_task_failure_count": 0,
"ad_total_batch_task_execution_count": 27,
"ad_executing_batch_task_count": 4
},
"TQDUXEzyTJyV0H6_T4hYUw": {
"ad_execute_request_count": 0,
"models": [
{
"detector_id": "Zi5zTXwBwf_U8gjUTfJG",
"model_type": "entity",
"last_used_time": 1633398375004,
"model_id": "Zi5zTXwBwf_U8gjUTfJG_entity_error24",
"last_checkpoint_time": 1633388177359,
"entity": [
{
"name": "error_type",
"value": "error24"
}
]
},
...
],
"ad_canceled_batch_task_count": 0,
"ad_hc_execute_request_count": 0,
"ad_hc_execute_failure_count": 0,
"model_count": 22,
"ad_execute_failure_count": 0,
"ad_batch_task_failure_count": 0,
"ad_total_batch_task_execution_count": 28,
"ad_executing_batch_task_count": 3
}
}
}
The model_count parameter shows the total number of models running on each node’s memory.
For historical analysis, you see the values for the following fields:
ad_total_batch_task_execution_countad_executing_batch_task_countad_canceled_batch_task_countad_batch_task_failure_count
If haven't run any historical analysis, these values show up as 0.
To get all stats for a specific node:
Request
GET _plugins/_anomaly_detection/<nodeId>/stats
To get specific stats for a node:
Request
GET _plugins/_anomaly_detection/<nodeId>/stats/<stat>
GET _plugins/_anomaly_detection/<nodeId>/stats/ad_execute_request_count
Sample response
{
"nodes": {
"SWD7ihu9TaaW1zKwFZNVNg": {
"ad_execute_request_count": 12
}
}
}
To get a specific type of stats:
Request
GET _plugins/_anomaly_detection/stats/<stat>
GET _plugins/_anomaly_detection/stats/ad_executing_batch_task_count
Sample response
{
"nodes": {
"2Z4q22BySEyzakYt_A0A2A": {
"ad_executing_batch_task_count": 3
},
"SWD7ihu9TaaW1zKwFZNVNg": {
"ad_executing_batch_task_count": 3
},
"TQDUXEzyTJyV0H6_T4hYUw": {
"ad_executing_batch_task_count": 4
}
}
}
Profile detector
Introduced 1.0 {: .label .label-purple }
Returns information related to the current state of the detector and memory usage, including current errors and shingle size, to help troubleshoot the detector.
This command helps locate logs by identifying the nodes that run the anomaly detector job for each detector.
It also helps track the initialization percentage, the required shingles, and the estimated time left.
Request
GET _plugins/_anomaly_detection/detectors/<detectorId>/_profile/
GET _plugins/_anomaly_detection/detectors/<detectorId>/_profile?_all=true
GET _plugins/_anomaly_detection/detectors/<detectorId>/_profile/<type>
GET _plugins/_anomaly_detection/detectors/<detectorId>/_profile/<type1>,<type2>
Sample Responses
GET _plugins/_anomaly_detection/detectors/<detectorId>/_profile
{
"state": "DISABLED",
"error": "Stopped detector: AD models memory usage exceeds our limit."
}
GET _plugins/_anomaly_detection/detectors/<detectorId>/_profile?_all=true&pretty
{
"state": "RUNNING",
"error": "",
"models": [
{
"model_id": "3Dh6TXwBwf_U8gjURE0F_entity_KSLSh0Wv05RQXiBAQHTEZg",
"entity": [
{
"name": "ip",
"value": "192.168.1.1"
},
{
"name": "error_type",
"value": "error8"
}
],
"model_size_in_bytes": 403491,
"node_id": "2Z4q22BySEyzakYt_A0A2A"
},
...
],
"total_size_in_bytes": 12911712,
"init_progress": {
"percentage": "100%"
},
"total_entities": 33,
"active_entities": 32,
"ad_task": {
"ad_task": {
"task_id": "D3I5TnwBYwCbWecg7lN9",
"last_update_time": 1633399993685,
"started_by": "admin",
"state": "RUNNING",
"detector_id": "3Dh6TXwBwf_U8gjURE0F",
"task_progress": 0,
"init_progress": 0,
"execution_start_time": 1633399991933,
"is_latest": true,
"task_type": "HISTORICAL_HC_DETECTOR",
"coordinating_node": "2Z4q22BySEyzakYt_A0A2A",
"detector": {
"name": "testhc-mc",
"description": "test",
"time_field": "timestamp",
"indices": [
"server_log"
],
"filter_query": {
"match_all": {
"boost": 1
}
},
"detection_interval": {
"period": {
"interval": 5,
"unit": "Minutes"
}
},
"window_delay": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"shingle_size": 8,
"schema_version": 0,
"feature_attributes": [
{
"feature_id": "2zh6TXwBwf_U8gjUQ039",
"feature_name": "test",
"feature_enabled": true,
"aggregation_query": {
"test": {
"sum": {
"field": "value"
}
}
}
}
],
"ui_metadata": {
"features": {
"test": {
"aggregationBy": "sum",
"aggregationOf": "value",
"featureType": "simple_aggs"
}
},
"filters": []
},
"last_update_time": 1633387430916,
"category_field": [
"ip",
"error_type"
],
"user": {
"name": "admin",
"backend_roles": [
"admin"
],
"roles": [
"own_index",
"all_access"
],
"custom_attribute_names": [],
"user_requested_tenant": "__user__"
},
"detector_type": "MULTI_ENTITY"
},
"detection_date_range": {
"start_time": 1632793800000,
"end_time": 1633398600000
},
"user": {
"name": "admin",
"backend_roles": [
"admin"
],
"roles": [
"own_index",
"all_access"
],
"custom_attribute_names": [],
"user_requested_tenant": "__user__"
}
},
"node_id": "2Z4q22BySEyzakYt_A0A2A",
"task_id": "D3I5TnwBYwCbWecg7lN9",
"task_type": "HISTORICAL_HC_DETECTOR",
"detector_task_slots": 10,
"total_entities_count": 32,
"pending_entities_count": 22,
"running_entities_count": 10,
"running_entities": [ """[{"name":"ip","value":"192.168.1.1"},{"name":"error_type","value":"error9"}]""",
...],
"entity_task_profiles": [
{
"shingle_size": 8,
"rcf_total_updates": 1994,
"threshold_model_trained": true,
"threshold_model_training_data_size": 0,
"model_size_in_bytes": 1593240,
"node_id": "2Z4q22BySEyzakYt_A0A2A",
"entity": [
{
"name": "ip",
"value": "192.168.1.1"
},
{
"name": "error_type",
"value": "error7"
}
],
"task_id": "E3I5TnwBYwCbWecg9FMm",
"task_type": "HISTORICAL_HC_ENTITY"
},
...
]
},
"model_count": 32
}
GET _plugins/_anomaly_detection/detectors/<detectorId>/_profile/total_size_in_bytes
{
"total_size_in_bytes": 13369344
}
You can see the ad_task field only for historical analysis.
The model_count parameter shows the total number of models that a detector runs on each node’s memory. This is useful if you have several models running on your cluster and want to know the count.
If you configured the category field, you can see the number of unique values in the field and all active entities with models running in memory.
You can use this data to estimate how much memory is required for anomaly detection so you can decide how to size your cluster. For example, if a detector has one million entities and only 10 of them are active in memory, you need to scale your cluster up or out.
For a single-entity detector:
Sample response
{
"state": "INIT",
"total_size_in_bytes": 0,
"init_progress": {
"percentage": "0%",
"needed_shingles": 128
},
"ad_task": {
"ad_task": {
"task_id": "cfUNOXwBFLNqSEcxAlde",
"last_update_time": 1633044731640,
"started_by": "admin",
"state": "RUNNING",
"detector_id": "qL4NOXwB__6eNorTAKtJ",
"task_progress": 0.49603173,
"init_progress": 1,
"current_piece": 1632739800000,
"execution_start_time": 1633044726365,
"is_latest": true,
"task_type": "HISTORICAL_SINGLE_ENTITY",
"coordinating_node": "bCtWtxWPThq0BIn5P5I4Xw",
"worker_node": "dIyavWhmSYWGz65b4u-lpQ",
"detector": {
"name": "detector1",
"description": "test",
"time_field": "timestamp",
"indices": [
"server_log"
],
"filter_query": {
"match_all": {
"boost": 1
}
},
"detection_interval": {
"period": {
"interval": 5,
"unit": "Minutes"
}
},
"window_delay": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"shingle_size": 8,
"schema_version": 0,
"feature_attributes": [
{
"feature_id": "p74NOXwB__6eNorTAKss",
"feature_name": "test-feature",
"feature_enabled": true,
"aggregation_query": {
"test_feature": {
"sum": {
"field": "value"
}
}
}
}
],
"ui_metadata": {
"features": {
"test-feature": {
"aggregationBy": "sum",
"aggregationOf": "value",
"featureType": "simple_aggs"
}
},
"filters": []
},
"last_update_time": 1633044725832,
"user": {
"name": "admin",
"backend_roles": [
"admin"
],
"roles": [
"own_index",
"all_access"
],
"custom_attribute_names": [],
"user_requested_tenant": "__user__"
},
"detector_type": "SINGLE_ENTITY"
},
"detection_date_range": {
"start_time": 1632439925885,
"end_time": 1633044725885
},
"user": {
"name": "admin",
"backend_roles": [
"admin"
],
"roles": [
"own_index",
"all_access"
],
"custom_attribute_names": [],
"user_requested_tenant": "__user__"
}
},
"shingle_size": 8,
"rcf_total_updates": 1994,
"threshold_model_trained": true,
"threshold_model_training_data_size": 0,
"model_size_in_bytes": 1593240,
"node_id": "dIyavWhmSYWGz65b4u-lpQ",
"detector_task_slots": 1
}
}
The total_entities parameter shows you the total number of entities including the number of category fields for a detector.
Getting the total count of entities is an expensive operation for real-time analysis of a detector with more than one category field. By default, for a real-time detection profile, a detector counts the number of entities up to a value of 10,000. For historical analysis, the anomaly detection plugin only detects the top 1,000 entities by default and caches the top entities in memory, so it doesn't cost much to get the total count of entities for historical analysis.
The profile operation also provides information about each entity, such as the entity’s last_sample_timestamp and last_active_timestamp. last_sample_timestamp shows the last document in the input data source index containing the entity, while last_active_timestamp shows the timestamp when the entity’s model was last seen in the model cache.
If there are no anomaly results for an entity, either the entity doesn't have any sample data or its model is removed from the model cache.
Request
GET _plugins/_anomaly_detection/detectors/<detectorId>/_profile?_all=true
{
"entity": [
{
"name": "host",
"value": "i-00f28ec1eb8997686"
}
]
}
Sample Responses
{
"category_field": "host",
"value": "i-00f28ec1eb8997686",
"is_active": true,
"last_active_timestamp": 1604026394879,
"last_sample_timestamp": 1604026394879,
"init_progress": {
"percentage": "100%"
},
"model": {
"model_id": "TFUdd3UBBwIAGQeRh5IS_entity_i-00f28ec1eb8997686",
"model_size_in_bytes": 712480,
"node_id": "MQ-bTBW3Q2uU_2zX3pyEQg"
},
"state": "RUNNING"
}
To get profile information for only historical analysis, specify ad_task.
Specifying _all is an expensive operation for multi-category high cardinality detectors.
Request
GET _plugins/_anomaly_detection/detectors/<detectorId>/_profile?_all
GET _plugins/_anomaly_detection/detectors/<detectorId>/_profile/ad_task
Sample Responses
{
"ad_task": {
"ad_task": {
"task_id": "CHI0TnwBYwCbWecgqgRA",
"last_update_time": 1633399648413,
"started_by": "admin",
"state": "RUNNING",
"detector_id": "3Dh6TXwBwf_U8gjURE0F",
"task_progress": 0,
"init_progress": 0,
"execution_start_time": 1633399646784,
"is_latest": true,
"task_type": "HISTORICAL_HC_DETECTOR",
"coordinating_node": "2Z4q22BySEyzakYt_A0A2A",
"detector": {
"name": "testhc-mc",
"description": "test",
"time_field": "timestamp",
"indices": [
"server_log"
],
"filter_query": {
"match_all": {
"boost": 1
}
},
"detection_interval": {
"period": {
"interval": 5,
"unit": "Minutes"
}
},
"window_delay": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"shingle_size": 8,
"schema_version": 0,
"feature_attributes": [
{
"feature_id": "2zh6TXwBwf_U8gjUQ039",
"feature_name": "test",
"feature_enabled": true,
"aggregation_query": {
"test": {
"sum": {
"field": "value"
}
}
}
}
],
"ui_metadata": {
"features": {
"test": {
"aggregationBy": "sum",
"aggregationOf": "value",
"featureType": "simple_aggs"
}
},
"filters": []
},
"last_update_time": 1633387430916,
"category_field": [
"ip",
"error_type"
],
"user": {
"name": "admin",
"backend_roles": [
"admin"
],
"roles": [
"own_index",
"all_access"
],
"custom_attribute_names": [],
"user_requested_tenant": "__user__"
},
"detector_type": "MULTI_ENTITY"
},
"detection_date_range": {
"start_time": 1632793800000,
"end_time": 1633398600000
},
"user": {
"name": "admin",
"backend_roles": [
"admin"
],
"roles": [
"own_index",
"all_access"
],
"custom_attribute_names": [],
"user_requested_tenant": "__user__"
}
},
"node_id": "2Z4q22BySEyzakYt_A0A2A",
"task_id": "CHI0TnwBYwCbWecgqgRA",
"task_type": "HISTORICAL_HC_DETECTOR",
"detector_task_slots": 10,
"total_entities_count": 32,
"pending_entities_count": 22,
"running_entities_count": 10,
"running_entities" : [
"""[{"name":"ip","value":"192.168.1.1"},{"name":"error_type","value":"error9"}]""",
...
],
"entity_task_profiles": [
{
"shingle_size": 8,
"rcf_total_updates": 994,
"threshold_model_trained": true,
"threshold_model_training_data_size": 0,
"model_size_in_bytes": 1593240,
"node_id": "2Z4q22BySEyzakYt_A0A2A",
"entity": [
{
"name": "ip",
"value": "192.168.1.1"
},
{
"name": "error_type",
"value": "error6"
}
],
"task_id": "9XI0TnwBYwCbWecgsAd6",
"task_type": "HISTORICAL_HC_ENTITY"
},
...
]
}
}
Delete detector results
Introduced 1.1 {: .label .label-purple }
Deletes the results of a detector based on a query.
Request
DELETE _plugins/_anomaly_detection/detectors/results
{
"query": {
"bool": {
"filter": [
{
"term": {
"detector_id": {
"value": "rlDtOHwBD5tpxlbyW7Nt"
}
}
},
{
"term": {
"task_id": {
"value": "TM3tOHwBCi2h__AOXlyQ"
}
}
},
{
"range": {
"data_start_time": {
"lte": 1632441600000
}
}
}
]
}
}
}
Sample response
{
"took": 48,
"timed_out": false,
"total": 28,
"updated": 0,
"created": 0,
"deleted": 28,
"batches": 1,
"version_conflicts": 0,
"noops": 0,
"retries": {
"bulk": 0,
"search": 0
},
"throttled_millis": 0,
"requests_per_second": -1,
"throttled_until_millis": 0,
"failures": []
}
Create monitor
Introduced 1.0 {: .label .label-purple }
Create a monitor to set up alerts for the detector.
Request
POST _plugins/_alerting/monitors
{
"type": "monitor",
"name": "test-monitor",
"enabled": true,
"schedule": {
"period": {
"interval": 20,
"unit": "MINUTES"
}
},
"inputs": [
{
"search": {
"indices": [
".opensearch-anomaly-results*"
],
"query": {
"size": 1,
"query": {
"bool": {
"filter": [
{
"range": {
"data_end_time": {
"from": "{{period_end}}||-20m",
"to": "{{period_end}}",
"include_lower": true,
"include_upper": true,
"boost": 1
}
}
},
{
"term": {
"detector_id": {
"value": "m4ccEnIBTXsGi3mvMt9p",
"boost": 1
}
}
}
],
"adjust_pure_negative": true,
"boost": 1
}
},
"sort": [
{
"anomaly_grade": {
"order": "desc"
}
},
{
"confidence": {
"order": "desc"
}
}
],
"aggregations": {
"max_anomaly_grade": {
"max": {
"field": "anomaly_grade"
}
}
}
}
}
}
],
"triggers": [
{
"name": "test-trigger",
"severity": "1",
"condition": {
"script": {
"source": "return ctx.results[0].aggregations.max_anomaly_grade.value != null && ctx.results[0].aggregations.max_anomaly_grade.value > 0.7 && ctx.results[0].hits.hits[0]._source.confidence > 0.7",
"lang": "painless"
}
},
"actions": [
{
"name": "test-action",
"destination_id": "ld7912sBlQ5JUWWFThoW",
"message_template": {
"source": "This is my message body."
},
"throttle_enabled": false,
"subject_template": {
"source": "TheSubject"
}
}
]
}
]
}
Sample response
{
"_id": "OClTEnIBmSf7y6LP11Jz",
"_version": 1,
"_seq_no": 10,
"_primary_term": 1,
"monitor": {
"type": "monitor",
"schema_version": 1,
"name": "test-monitor",
"enabled": true,
"enabled_time": 1589445384043,
"schedule": {
"period": {
"interval": 20,
"unit": "MINUTES"
}
},
"inputs": [
{
"search": {
"indices": [
".opensearch-anomaly-results*"
],
"query": {
"size": 1,
"query": {
"bool": {
"filter": [
{
"range": {
"data_end_time": {
"from": "{{period_end}}||-20m",
"to": "{{period_end}}",
"include_lower": true,
"include_upper": true,
"boost": 1
}
}
},
{
"term": {
"detector_id": {
"value": "m4ccEnIBTXsGi3mvMt9p",
"boost": 1
}
}
}
],
"adjust_pure_negative": true,
"boost": 1
}
},
"sort": [
{
"anomaly_grade": {
"order": "desc"
}
},
{
"confidence": {
"order": "desc"
}
}
],
"aggregations": {
"max_anomaly_grade": {
"max": {
"field": "anomaly_grade"
}
}
}
}
}
}
],
"triggers": [
{
"id": "NilTEnIBmSf7y6LP11Jr",
"name": "test-trigger",
"severity": "1",
"condition": {
"script": {
"source": "return ctx.results[0].aggregations.max_anomaly_grade.value != null && ctx.results[0].aggregations.max_anomaly_grade.value > 0.7 && ctx.results[0].hits.hits[0]._source.confidence > 0.7",
"lang": "painless"
}
},
"actions": [
{
"id": "NylTEnIBmSf7y6LP11Jr",
"name": "test-action",
"destination_id": "ld7912sBlQ5JUWWFThoW",
"message_template": {
"source": "This is my message body.",
"lang": "mustache"
},
"throttle_enabled": false,
"subject_template": {
"source": "TheSubject",
"lang": "mustache"
}
}
]
}
],
"last_update_time": 1589445384043
}
}