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---
layout: default
title: Anomaly detection API
parent: Anomaly detection
nav_order: 1
---
# Anomaly detection API
Use these anomaly detection operations to programmatically create and manage detectors.
---
#### Table of contents
- TOC
{:toc}
---
## Create anomaly detector
Creates an anomaly detector.
This command creates a detector named `http_requests` that finds anomalies based on the sum and average number of failed HTTP requests:
#### Request
```json
POST _opensearch/_anomaly_detection/detectors
{
"name": "test-detector",
"description": "Test detector",
"time_field": "timestamp",
"indices": [
"order*"
],
"feature_attributes": [
{
"feature_name": "total_order",
"feature_enabled": true,
"aggregation_query": {
"total_order": {
"sum": {
"field": "value"
}
}
}
}
],
"filter_query": {
"bool": {
"filter": [
{
"exists": {
"field": "value",
"boost": 1
}
}
],
"adjust_pure_negative": true,
"boost": 1
}
},
"detection_interval": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"window_delay": {
"period": {
"interval": 1,
"unit": "Minutes"
}
}
}
```
#### Sample response
```json
{
"_id": "m4ccEnIBTXsGi3mvMt9p",
"_version": 1,
"_seq_no": 3,
"_primary_term": 1,
"anomaly_detector": {
"name": "test-detector",
"description": "Test detector",
"time_field": "timestamp",
"indices": [
"order*"
],
"filter_query": {
"bool": {
"filter": [
{
"exists": {
"field": "value",
"boost": 1
}
}
],
"adjust_pure_negative": true,
"boost": 1
}
},
"detection_interval": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"window_delay": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"schema_version": 0,
"feature_attributes": [
{
"feature_id": "mYccEnIBTXsGi3mvMd8_",
"feature_name": "total_order",
"feature_enabled": true,
"aggregation_query": {
"total_order": {
"sum": {
"field": "value"
}
}
}
}
]
}
}
```
To set a category field for high cardinality:
#### Request
```json
POST _opensearch/_anomaly_detection/detectors
{
"name": "Host OK Rate Detector",
"description": "ok rate",
"time_field": "@timestamp",
"indices": [
"host-cloudwatch"
],
"category_field": [
"host"
],
"feature_attributes": [
{
"feature_name": "latency_max",
"feature_enabled": true,
"aggregation_query": {
"latency_max": {
"max": {
"field": "latency"
}
}
}
}
],
"window_delay": {
"period": {
"interval": 10,
"unit": "MINUTES"
}
},
"detection_interval": {
"period": {
"interval": 1,
"unit": "MINUTES"
}
}
}
```
#### Sample response
```json
{
"_id": "4CIGoHUBTpMGN-4KzBQg",
"_version": 1,
"_seq_no": 0,
"anomaly_detector": {
"name": "Host OK Rate Detector",
"description": "ok rate",
"time_field": "@timestamp",
"indices": [
"server-metrics"
],
"filter_query": {
"match_all": {
"boost": 1
}
},
"detection_interval": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"window_delay": {
"period": {
"interval": 10,
"unit": "MINUTES"
}
},
"shingle_size": 1,
"schema_version": 2,
"feature_attributes": [
{
"feature_id": "0Kld3HUBhpHMyt2e_UHn",
"feature_name": "latency_max",
"feature_enabled": true,
"aggregation_query": {
"latency_max": {
"max": {
"field": "latency"
}
}
}
}
],
"last_update_time": 1604707601438,
"category_field": [
"host"
]
},
"_primary_term": 1
}
```
To create a historical detector:
#### Request
```json
POST _opensearch/_anomaly_detection/detectors
{
"name": "test1",
"description": "test historical detector",
"time_field": "timestamp",
"indices": [
"host-cloudwatch"
],
"filter_query": {
"match_all": {
"boost": 1
}
},
"detection_interval": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"window_delay": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"feature_attributes": [
{
"feature_name": "F1",
"feature_enabled": true,
"aggregation_query": {
"f_1": {
"sum": {
"field": "value"
}
}
}
}
],
"detection_date_range": {
"start_time": 1577840401000,
"end_time": 1606121925000
}
}
```
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
`detection_date_range` | Specify the start time and end time for a historical detector. | `object` | No
---
## Preview detector
Passes a date range to the anomaly detector to return any anomalies within that date range.
#### Request
```json
POST _opensearch/_anomaly_detection/detectors/<detectorId>/_preview
{
"period_start": 1588838250000,
"period_end": 1589443050000
}
```
#### Sample response
```json
{
"anomaly_result": [
...
{
"detector_id": "m4ccEnIBTXsGi3mvMt9p",
"data_start_time": 1588843020000,
"data_end_time": 1588843620000,
"feature_data": [
{
"feature_id": "xxokEnIBcpeWMD987A1X",
"feature_name": "total_order",
"data": 489.9929131106
}
],
"anomaly_grade": 0,
"confidence": 0.99
}
...
],
"anomaly_detector": {
"name": "test-detector",
"description": "Test detector",
"time_field": "timestamp",
"indices": [
"order*"
],
"filter_query": {
"bool": {
"filter": [
{
"exists": {
"field": "value",
"boost": 1
}
}
],
"adjust_pure_negative": true,
"boost": 1
}
},
"detection_interval": {
"period": {
"interval": 10,
"unit": "MINUTES"
}
},
"window_delay": {
"period": {
"interval": 1,
"unit": "MINUTES"
}
},
"schema_version": 0,
"feature_attributes": [
{
"feature_id": "xxokEnIBcpeWMD987A1X",
"feature_name": "total_order",
"feature_enabled": true,
"aggregation_query": {
"total_order": {
"sum": {
"field": "value"
}
}
}
}
],
"last_update_time": 1589442309241
}
}
```
If you specify a category field, each result is associated with an entity:
#### Sample response
```json
{
"anomaly_result": [
{
"detector_id": "4CIGoHUBTpMGN-4KzBQg",
"data_start_time": 1604277960000,
"data_end_time": 1604278020000,
"schema_version": 0,
"anomaly_grade": 0,
"confidence": 0.99
}
],
"entity": [
{
"name": "host",
"value": "i-00f28ec1eb8997686"
}
]
},
{
"detector_id": "4CIGoHUBTpMGN-4KzBQg",
"data_start_time": 1604278020000,
"data_end_time": 1604278080000,
"schema_version": 0,
"feature_data": [
{
"feature_id": "0Kld3HUBhpHMyt2e_UHn",
"feature_name": "latency_max",
"data": -17
}
],
"anomaly_grade": 0,
"confidence": 0.99,
"entity": [
{
"name": "host",
"value": "i-00f28ec1eb8997686"
}
]
}
...
```
---
## Start detector job
Starts a real-time or historical detector job.
#### Request
```json
POST _opensearch/_anomaly_detection/detectors/<detectorId>/_start
```
#### Sample response
```json
{
"_id" : "m4ccEnIBTXsGi3mvMt9p",
"_version" : 1,
"_seq_no" : 6,
"_primary_term" : 1
}
```
---
## Stop detector job
Stops a real-time or historical anomaly detector job.
#### Request
```json
POST _opensearch/_anomaly_detection/detectors/<detectorId>/_stop
```
#### Sample response
```json
Stopped detector: m4ccEnIBTXsGi3mvMt9p
```
---
## Search detector result
Returns all results for a search query.
#### Request
```json
GET _opensearch/_anomaly_detection/detectors/results/_search
POST _opensearch/_anomaly_detection/detectors/results/_search
{
"query": {
"bool": {
"must": {
"range": {
"anomaly_score": {
"gte": 0.6,
"lte": 1
}
}
}
}
}
}
```
#### Sample response
```json
{
"took": 9,
"timed_out": false,
"_shards": {
"total": 25,
"successful": 25,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 2,
"relation": "eq"
},
"max_score": 1,
"hits": [
{
"_index": ".opensearch-anomaly-results-history-2020.04.30-1",
"_type": "_doc",
"_id": "_KBrzXEBbpoKkFM5mStm",
"_version": 1,
"_seq_no": 58,
"_primary_term": 1,
"_score": 1,
"_source": {
"detector_id": "2KDozHEBbpoKkFM58yr6",
"anomaly_score": 0.8995068350366767,
"execution_start_time": 1588289313114,
"data_end_time": 1588289313114,
"confidence": 0.84214852704501,
"data_start_time": 1588289253114,
"feature_data": [
{
"feature_id": "X0fpzHEB5NGZmIRkXKcy",
"feature_name": "total_error",
"data": 20
}
],
"execution_end_time": 1588289313126,
"anomaly_grade": 0
}
},
{
"_index": ".opensearch-anomaly-results-history-2020.04.30-1",
"_type": "_doc",
"_id": "EqB1zXEBbpoKkFM5qyyE",
"_version": 1,
"_seq_no": 61,
"_primary_term": 1,
"_score": 1,
"_source": {
"detector_id": "2KDozHEBbpoKkFM58yr6",
"anomaly_score": 0.7086834513354907,
"execution_start_time": 1588289973113,
"data_end_time": 1588289973113,
"confidence": 0.42162017029510446,
"data_start_time": 1588289913113,
"feature_data": [
{
"feature_id": "X0fpzHEB5NGZmIRkXKcy",
"feature_name": "memory_usage",
"data": 20.0347333108
}
],
"execution_end_time": 1588289973124,
"anomaly_grade": 0
}
}
]
}
}
```
In high cardinality detectors, the result contains entities’ information.
To see an ordered set of anomaly records for an entity with an anomaly within a certain time range for a specific feature value:
#### Request
```json
POST _opensearch/_anomaly_detection/detectors/results/_search
{
"query": {
"bool": {
"filter": [
{
"term": {
"detector_id": "4CIGoHUBTpMGN-4KzBQg"
}
},
{
"range": {
"anomaly_grade": {
"gt": 0
}
}
},
{
"nested": {
"path": "entity",
"query": {
"bool": {
"must": [
{
"term": {
"entity.value": "i-00f28ec1eb8997685"
}
}
]
}
}
}
}
]
}
},
"size": 8,
"sort": [
{
"execution_end_time": {
"order": "desc"
}
}
],
"track_total_hits": true
}
```
#### Sample response
```json
{
"took": 443,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 7,
"relation": "eq"
},
"max_score": null,
"hits": [
{
"_index": ".opensearch-anomaly-results-history-2020.11.07-1",
"_type": "_doc",
"_id": "BiItoHUBTpMGN-4KARY5",
"_version": 1,
"_seq_no": 206,
"_primary_term": 1,
"_score": null,
"_source": {
"detector_id": "4CIGoHUBTpMGN-4KzBQg",
"schema_version": 2,
"anomaly_score": 2.462550517055763,
"execution_start_time": 1604710105400,
"data_end_time": 1604710094516,
"confidence": 0.8246254862573076,
"data_start_time": 1604710034516,
"feature_data": [
{
"feature_id": "0Kld3HUBhpHMyt2e_UHn",
"feature_name": "latency_max",
"data": 3526
}
],
"execution_end_time": 1604710105401,
"anomaly_grade": 0.08045977011494891,
"entity": [
{
"name": "host",
"value": "i-00f28ec1eb8997685"
}
]
},
"sort": [
1604710105401
]
},
{
"_index": ".opensearch-anomaly-results-history-2020.11.07-1",
"_type": "_doc",
"_id": "wiImoHUBTpMGN-4KlhXs",
"_version": 1,
"_seq_no": 156,
"_primary_term": 1,
"_score": null,
"_source": {
"detector_id": "4CIGoHUBTpMGN-4KzBQg",
"schema_version": 2,
"anomaly_score": 4.892453213261217,
"execution_start_time": 1604709684971,
"data_end_time": 1604709674522,
"confidence": 0.8313735633713821,
"data_start_time": 1604709614522,
"feature_data": [
{
"feature_id": "0Kld3HUBhpHMyt2e_UHn",
"feature_name": "latency_max",
"data": 5709
}
],
"execution_end_time": 1604709684971,
"anomaly_grade": 0.06542056074767538,
"entity": [
{
"name": "host",
"value": "i-00f28ec1eb8997685"
}
]
},
"sort": [
1604709684971
]
},
{
"_index": ".opensearch-anomaly-results-history-2020.11.07-1",
"_type": "_doc",
"_id": "ZiIcoHUBTpMGN-4KhhVA",
"_version": 1,
"_seq_no": 79,
"_primary_term": 1,
"_score": null,
"_source": {
"detector_id": "4CIGoHUBTpMGN-4KzBQg",
"schema_version": 2,
"anomaly_score": 3.187717536855158,
"execution_start_time": 1604709025343,
"data_end_time": 1604709014520,
"confidence": 0.8301116064308817,
"data_start_time": 1604708954520,
"feature_data": [
{
"feature_id": "0Kld3HUBhpHMyt2e_UHn",
"feature_name": "latency_max",
"data": 441
}
],
"execution_end_time": 1604709025344,
"anomaly_grade": 0.040767386091133916,
"entity": [
{
"name": "host",
"value": "i-00f28ec1eb8997685"
}
]
},
"sort": [
1604709025344
]
}
]
}
}
```
In historical detectors, specify the `detector_id`.
To get the latest task:
#### Request
```json
GET _opensearch/_anomaly_detection/detectors/<detector_id>?task=true
```
To query the anomaly results with `task_id`:
#### Request
```json
GET _opensearch/_anomaly_detection/detectors/results/_search
{
"query": {
"term": {
"task_id": {
"value": "NnlV9HUBQxqfQ7vBJNzy"
}
}
}
}
```
#### Sample response
```json
{
"took": 1,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 1,
"relation": "eq"
},
"max_score": 2.1366,
"hits": [
{
"_index": ".opensearch-anomaly-detection-state",
"_type": "_doc",
"_id": "CoM8WncBtt2qvI-LZO7_",
"_version": 8,
"_seq_no": 1351,
"_primary_term": 3,
"_score": 2.1366,
"_source": {
"detector_id": "dZc8WncBgO2zoQoFWVBA",
"worker_node": "dk6-HuKQRMKm2fi8TSDHsg",
"task_progress": 0.09486946,
"last_update_time": 1612126667008,
"execution_start_time": 1612126643455,
"state": "RUNNING",
"coordinating_node": "gs213KqjS4q7H4Bmn_ZuLA",
"current_piece": 1583503800000,
"task_type": "HISTORICAL",
"started_by": "admin",
"init_progress": 1,
"is_latest": true,
"detector": {
"description": "test",
"ui_metadata": {
"features": {
"F1": {
"aggregationBy": "sum",
"aggregationOf": "value",
"featureType": "simple_aggs"
}
}
},
"detection_date_range": {
"start_time": 1580504240308,
"end_time": 1612126640308
},
"feature_attributes": [
{
"feature_id": "dJc8WncBgO2zoQoFWVAt",
"feature_enabled": true,
"feature_name": "F1",
"aggregation_query": {
"f_1": {
"sum": {
"field": "value"
}
}
}
}
],
"schema_version": 0,
"time_field": "timestamp",
"last_update_time": 1612126640448,
"indices": [
"nab_art_daily_jumpsdown"
],
"window_delay": {
"period": {
"unit": "Minutes",
"interval": 1
}
},
"detection_interval": {
"period": {
"unit": "Minutes",
"interval": 10
}
},
"name": "test-historical-detector",
"filter_query": {
"match_all": {
"boost": 1
}
},
"shingle_size": 8,
"user": {
"backend_roles": [
"admin"
],
"custom_attribute_names": [],
"roles": [
"all_access",
"own_index"
],
"name": "admin",
"user_requested_tenant": "__user__"
},
"detector_type": "HISTORICAL_SINGLE_ENTITY"
},
"user": {
"backend_roles": [
"admin"
],
"custom_attribute_names": [],
"roles": [
"all_access",
"own_index"
],
"name": "admin",
"user_requested_tenant": "__user__"
}
}
}
]
}
}
```
---
## Delete detector
Deletes a detector based on the `detector_id`.
To delete a detector, you need to first stop the detector.
#### Request
```json
DELETE _opensearch/_anomaly_detection/detectors/<detectorId>
```
#### Sample response
```json
{
"_index" : ".opensearch-anomaly-detectors",
"_type" : "_doc",
"_id" : "m4ccEnIBTXsGi3mvMt9p",
"_version" : 2,
"result" : "deleted",
"forced_refresh" : true,
"_shards" : {
"total" : 2,
"successful" : 2,
"failed" : 0
},
"_seq_no" : 6,
"_primary_term" : 1
}
```
---
## Update detector
Updates a detector with any changes, including the description or adding or removing of features.
To update a detector, you need to first stop the detector.
#### Request
```json
PUT _opensearch/_anomaly_detection/detectors/<detectorId>
{
"name": "test-detector",
"description": "Test detector",
"time_field": "timestamp",
"indices": [
"order*"
],
"feature_attributes": [
{
"feature_name": "total_order",
"feature_enabled": true,
"aggregation_query": {
"total_order": {
"sum": {
"field": "value"
}
}
}
}
],
"filter_query": {
"bool": {
"filter": [
{
"exists": {
"field": "value",
"boost": 1
}
}
],
"adjust_pure_negative": true,
"boost": 1
}
},
"detection_interval": {
"period": {
"interval": 10,
"unit": "MINUTES"
}
},
"window_delay": {
"period": {
"interval": 1,
"unit": "MINUTES"
}
}
}
```
#### Sample response
```json
{
"_id" : "m4ccEnIBTXsGi3mvMt9p",
"_version" : 2,
"_seq_no" : 4,
"_primary_term" : 1,
"anomaly_detector" : {
"name" : "test-detector",
"description" : "Test detector",
"time_field" : "timestamp",
"indices" : [
"order*"
],
"filter_query" : {
"bool" : {
"filter" : [
{
"exists" : {
"field" : "value",
"boost" : 1.0
}
}
],
"adjust_pure_negative" : true,
"boost" : 1.0
}
},
"detection_interval" : {
"period" : {
"interval" : 10,
"unit" : "Minutes"
}
},
"window_delay" : {
"period" : {
"interval" : 1,
"unit" : "Minutes"
}
},
"schema_version" : 0,
"feature_attributes" : [
{
"feature_id" : "xxokEnIBcpeWMD987A1X",
"feature_name" : "total_order",
"feature_enabled" : true,
"aggregation_query" : {
"total_order" : {
"sum" : {
"field" : "value"
}
}
}
}
]
}
}
```
To update a historical detector:
#### Request
```json
PUT _opensearch/_anomaly_detection/detectors/<detectorId>
{
"name": "test1",
"description": "test historical detector",
"time_field": "timestamp",
"indices": [
"nab_art_daily_jumpsdown"
],
"filter_query": {
"match_all": {
"boost": 1
}
},
"detection_interval": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"window_delay": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"feature_attributes": [
{
"feature_name": "F1",
"feature_enabled": true,
"aggregation_query": {
"f_1": {
"sum": {
"field": "value"
}
}
}
}
],
"detection_date_range": {
"start_time": 1577840401000,
"end_time": 1606121925000
}
}
```
---
## Get detector
Returns all information about a detector based on the `detector_id`.
#### Request
```json
GET _opensearch/_anomaly_detection/detectors/<detectorId>
```
#### Sample response
```json
{
"_id" : "m4ccEnIBTXsGi3mvMt9p",
"_version" : 1,
"_primary_term" : 1,
"_seq_no" : 3,
"anomaly_detector" : {
"name" : "test-detector",
"description" : "Test detector",
"time_field" : "timestamp",
"indices" : [
"order*"
],
"filter_query" : {
"bool" : {
"filter" : [
{
"exists" : {
"field" : "value",
"boost" : 1.0
}
}
],
"adjust_pure_negative" : true,
"boost" : 1.0
}
},
"detection_interval" : {
"period" : {
"interval" : 1,
"unit" : "Minutes"
}
},
"window_delay" : {
"period" : {
"interval" : 1,
"unit" : "Minutes"
}
},
"schema_version" : 0,
"feature_attributes" : [
{
"feature_id" : "mYccEnIBTXsGi3mvMd8_",
"feature_name" : "total_order",
"feature_enabled" : true,
"aggregation_query" : {
"total_order" : {
"sum" : {
"field" : "value"
}
}
}
}
],
"last_update_time" : 1589441737319
}
}
```
Use `job=true` to get anomaly detection job information.
#### Request
```json
GET _opensearch/_anomaly_detection/detectors/<detectorId>?job=true
```
#### Sample response
```json
{
"_id" : "m4ccEnIBTXsGi3mvMt9p",
"_version" : 1,
"_primary_term" : 1,
"_seq_no" : 3,
"anomaly_detector" : {
"name" : "test-detector",
"description" : "Test detector",
"time_field" : "timestamp",
"indices" : [
"order*"
],
"filter_query" : {
"bool" : {
"filter" : [
{
"exists" : {
"field" : "value",
"boost" : 1.0
}
}
],
"adjust_pure_negative" : true,
"boost" : 1.0
}
},
"detection_interval" : {
"period" : {
"interval" : 1,
"unit" : "Minutes"
}
},
"window_delay" : {
"period" : {
"interval" : 1,
"unit" : "Minutes"
}
},
"schema_version" : 0,
"feature_attributes" : [
{
"feature_id" : "mYccEnIBTXsGi3mvMd8_",
"feature_name" : "total_order",
"feature_enabled" : true,
"aggregation_query" : {
"total_order" : {
"sum" : {
"field" : "value"
}
}
}
}
],
"last_update_time" : 1589441737319
},
"anomaly_detector_job" : {
"name" : "m4ccEnIBTXsGi3mvMt9p",
"schedule" : {
"interval" : {
"start_time" : 1589442051271,
"period" : 1,
"unit" : "Minutes"
}
},
"window_delay" : {
"period" : {
"interval" : 1,
"unit" : "Minutes"
}
},
"enabled" : true,
"enabled_time" : 1589442051271,
"last_update_time" : 1589442051271,
"lock_duration_seconds" : 60
}
}
```
Use `task=true` to get historical detector task information.
#### Request
```json
GET _opensearch/_anomaly_detection/detectors/<detectorId>?task=true
```
#### Sample response
```json
{
"_id": "BwzKQXcB89DLS7G9rg7Y",
"_version": 1,
"_primary_term": 2,
"_seq_no": 10,
"anomaly_detector": {
"name": "test-ylwu1",
"description": "test",
"time_field": "timestamp",
"indices": [
"nab*"
],
"filter_query": {
"match_all": {
"boost": 1
}
},
"detection_interval": {
"period": {
"interval": 10,
"unit": "Minutes"
}
},
"window_delay": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"shingle_size": 8,
"schema_version": 0,
"feature_attributes": [
{
"feature_id": "BgzKQXcB89DLS7G9rg7G",
"feature_name": "F1",
"feature_enabled": true,
"aggregation_query": {
"f_1": {
"sum": {
"field": "value"
}
}
}
}
],
"ui_metadata": {
"features": {
"F1": {
"aggregationBy": "sum",
"aggregationOf": "value",
"featureType": "simple_aggs"
}
}
},
"last_update_time": 1611716538071,
"user": {
"name": "admin",
"backend_roles": [
"admin"
],
"roles": [
"all_access",
"own_index"
],
"custom_attribute_names": [],
"user_requested_tenant": "__user__"
},
"detector_type": "HISTORICAL_SINGLE_ENTITY",
"detection_date_range": {
"start_time": 1580094137997,
"end_time": 1611716537997
}
},
"anomaly_detection_task": {
"task_id": "sgxaRXcB89DLS7G9RfIO",
"last_update_time": 1611776648699,
"started_by": "admin",
"state": "FINISHED",
"detector_id": "BwzKQXcB89DLS7G9rg7Y",
"task_progress": 1,
"init_progress": 1,
"current_piece": 1611716400000,
"execution_start_time": 1611776279822,
"execution_end_time": 1611776648679,
"is_latest": true,
"task_type": "HISTORICAL",
"coordinating_node": "gs213KqjS4q7H4Bmn_ZuLA",
"worker_node": "PgfR3JhbT7yJMx7bwQ6E3w",
"detector": {
"name": "test-ylwu1",
"description": "test",
"time_field": "timestamp",
"indices": [
"nab*"
],
"filter_query": {
"match_all": {
"boost": 1
}
},
"detection_interval": {
"period": {
"interval": 10,
"unit": "Minutes"
}
},
"window_delay": {
"period": {
"interval": 1,
"unit": "Minutes"
}
},
"shingle_size": 8,
"schema_version": 0,
"feature_attributes": [
{
"feature_id": "BgzKQXcB89DLS7G9rg7G",
"feature_name": "F1",
"feature_enabled": true,
"aggregation_query": {
"f_1": {
"sum": {
"field": "value"
}
}
}
}
],
"ui_metadata": {
"features": {
"F1": {
"aggregationBy": "sum",
"aggregationOf": "value",
"featureType": "simple_aggs"
}
}
},
"last_update_time": 1611716538071,
"user": {
"name": "admin",
"backend_roles": [
"admin"
],
"roles": [
"all_access",
"own_index"
],
"custom_attribute_names": [],
"user_requested_tenant": "__user__"
},
"detector_type": "HISTORICAL_SINGLE_ENTITY",
"detection_date_range": {
"start_time": 1580094137997,
"end_time": 1611716537997
}
},
"user": {
"name": "admin",
"backend_roles": [
"admin"
],
"roles": [
"all_access",
"own_index"
],
"custom_attribute_names": [],
"user_requested_tenant": "__user__"
}
}
}
```
---
## Search detector
Returns all anomaly detectors for a search query.
#### Request
```json
GET _opensearch/_anomaly_detection/detectors/_search
POST _opensearch/_anomaly_detection/detectors/_search
Sample Input:
{
"query": {
"match": {
"name": "test-detector"
}
}
}
```
#### Sample response
```json
{
"took": 13,
"timed_out": false,
"_shards": {
"total": 5,
"successful": 5,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 994,
"relation": "eq"
},
"max_score": 3.5410638,
"hits": [
{
"_index": ".opensearch-anomaly-detectors",
"_type": "_doc",
"_id": "m4ccEnIBTXsGi3mvMt9p",
"_version": 2,
"_seq_no": 221,
"_primary_term": 1,
"_score": 3.5410638,
"_source": {
"name": "test-detector",
"description": "Test detector",
"time_field": "timestamp",
"indices": [
"order*"
],
"filter_query": {
"bool": {
"filter": [
{
"exists": {
"field": "value",
"boost": 1
}
}
],
"adjust_pure_negative": true,
"boost": 1
}
},
"detection_interval": {
"period": {
"interval": 10,
"unit": "MINUTES"
}
},
"window_delay": {
"period": {
"interval": 1,
"unit": "MINUTES"
}
},
"schema_version": 0,
"feature_attributes": [
{
"feature_id": "xxokEnIBcpeWMD987A1X",
"feature_name": "total_order",
"feature_enabled": true,
"aggregation_query": {
"total_order": {
"sum": {
"field": "value"
}
}
}
}
],
"last_update_time": 1589442309241
}
}
]
}
}
```
---
## Get detector stats
Provides information about how the plugin is performing.
#### Request
```json
GET _opensearch/_anomaly_detection/stats
GET _opensearch/_anomaly_detection/<nodeId>/stats
GET _opensearch/_anomaly_detection/<nodeId>/stats/<stat>
GET _opensearch/_anomaly_detection/stats/<stat>
```
#### Sample response
```json
{
"_nodes" : {
"total" : 3,
"successful" : 3,
"failed" : 0
},
"cluster_name" : "multi-node-run",
"anomaly_detectors_index_status" : "green",
"detector_count" : 1,
"models_checkpoint_index_status" : "green",
"anomaly_results_index_status" : "green",
"nodes" : {
"IgWDUfzFRzW0FWAXM5FGJw" : {
"ad_execute_request_count" : 8,
"ad_execute_failure_count" : 7,
"models" : [
{
"detector_id" : "m4ccEnIBTXsGi3mvMt9p",
"model_type" : "rcf",
"model_id" : "m4ccEnIBTXsGi3mvMt9p_model_rcf_0"
},
{
"detector_id" : "m4ccEnIBTXsGi3mvMt9p",
"model_type" : "threshold",
"model_id" : "m4ccEnIBTXsGi3mvMt9p_model_threshold"
}
]
},
"y7YUQWukQEWOYbfdEq13hQ" : {
"ad_execute_request_count" : 0,
"ad_execute_failure_count" : 0,
"models" : [ ]
},
"cDcGNsPoRAyRMlPP1m-vZw" : {
"ad_execute_request_count" : 0,
"ad_execute_failure_count" : 0,
"models" : [
{
"detector_id" : "m4ccEnIBTXsGi3mvMt9p",
"model_type" : "rcf",
"model_id" : "m4ccEnIBTXsGi3mvMt9p_model_rcf_2"
},
{
"detector_id" : "m4ccEnIBTXsGi3mvMt9p",
"model_type" : "rcf",
"model_id" : "m4ccEnIBTXsGi3mvMt9p_model_rcf_1"
}
]
}
}
}
```
Historical detectors contain additional fields:
#### Sample response
```json
{
"anomaly_detectors_index_status": "yellow",
"anomaly_detection_state_status": "yellow",
"historical_detector_count": 3,
"detector_count": 7,
"anomaly_detection_job_index_status": "yellow",
"models_checkpoint_index_status": "yellow",
"anomaly_results_index_status": "yellow",
"nodes": {
"Mz9HDZnuQwSCw0UiisxwWg": {
"ad_execute_request_count": 0,
"models": [],
"ad_canceled_batch_task_count": 2,
"ad_hc_execute_request_count": 0,
"ad_hc_execute_failure_count": 0,
"ad_execute_failure_count": 0,
"ad_batch_task_failure_count": 0,
"ad_executing_batch_task_count": 1,
"ad_total_batch_task_count": 8
}
}
}
```
---
## Create monitor
Create a monitor to set up alerts for the detector.
#### Request
```json
POST _opensearch/_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
```json
{
"_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
}
}
```
---
## Profile detector
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
```json
GET _opensearch/_anomaly_detection/detectors/<detectorId>/_profile/
GET _opensearch/_anomaly_detection/detectors/<detectorId>/_profile?_all=true
GET _opensearch/_anomaly_detection/detectors/<detectorId>/_profile/<type>
GET /_opensearch/_anomaly_detection/detectors/<detectorId>/_profile/<type1>,<type2>
```
#### Sample Responses
```json
GET _opensearch/_anomaly_detection/detectors/<detectorId>/_profile
{
"state":"DISABLED",
"error":"Stopped detector: AD models memory usage exceeds our limit."
}
GET _opensearch/_anomaly_detection/detectors/<detectorId>/_profile?_all=true&pretty
{
"state": "RUNNING",
"models": [
{
"model_id": "cneh7HEBHPICjJIdXdrR_model_rcf_2",
"model_size_in_bytes": 4456448,
"node_id": "VS29z70PSzOdHiEw4SoV9Q"
},
{
"model_id": "cneh7HEBHPICjJIdXdrR_model_rcf_1",
"model_size_in_bytes": 4456448,
"node_id": "VS29z70PSzOdHiEw4SoV9Q"
},
{
"model_id": "cneh7HEBHPICjJIdXdrR_model_threshold",
"node_id": "Og23iUroTdKrkwS-y89zLw"
},
{
"model_id": "cneh7HEBHPICjJIdXdrR_model_rcf_0",
"model_size_in_bytes": 4456448,
"node_id": "Og23iUroTdKrkwS-y89zLw"
}
],
"shingle_size": 8,
"coordinating_node": "Og23iUroTdKrkwS-y89zLw",
"total_size_in_bytes": 13369344,
"init_progress": {
"percentage": "70%",
"estimated_minutes_left": 77,
"needed_shingles": 77
}
}
GET _opensearch/_anomaly_detection/detectors/<detectorId>/_profile/total_size_in_bytes
{
"total_size_in_bytes" : 13369344
}
```
If you have configured the category field, you can see the number of unique values in the field and also all the active entities with models running in memory.
You can use this data to estimate the memory required for anomaly detection to help decide the size of your cluster.
For example, if a detector has one million entities and only 10 of them are active in memory, then you need to scale up or scale out your cluster.
#### Request
```json
GET /_opensearch/_anomaly_detection/detectors/<detectorId>/_profile?_all=true&pretty
{
"state": "RUNNING",
"models": [
{
"model_id": "T4c3dXUBj-2IZN7itix__entity_i-00f28ec1eb8997684",
"model_size_in_bytes": 712480,
"node_id": "g6pmr547QR-CfpEvO67M4g"
},
{
"model_id": "T4c3dXUBj-2IZN7itix__entity_i-00f28ec1eb8997685",
"model_size_in_bytes": 712480,
"node_id": "g6pmr547QR-CfpEvO67M4g"
},
{
"model_id": "T4c3dXUBj-2IZN7itix__entity_i-00f28ec1eb8997686",
"model_size_in_bytes": 712480,
"node_id": "g6pmr547QR-CfpEvO67M4g"
},
{
"model_id": "T4c3dXUBj-2IZN7itix__entity_i-00f28ec1eb8997680",
"model_size_in_bytes": 712480,
"node_id": "g6pmr547QR-CfpEvO67M4g"
},
{
"model_id": "T4c3dXUBj-2IZN7itix__entity_i-00f28ec1eb8997681",
"model_size_in_bytes": 712480,
"node_id": "g6pmr547QR-CfpEvO67M4g"
},
{
"model_id": "T4c3dXUBj-2IZN7itix__entity_i-00f28ec1eb8997682",
"model_size_in_bytes": 712480,
"node_id": "g6pmr547QR-CfpEvO67M4g"
},
{
"model_id": "T4c3dXUBj-2IZN7itix__entity_i-00f28ec1eb8997683",
"model_size_in_bytes": 712480,
"node_id": "g6pmr547QR-CfpEvO67M4g"
}
],
"total_size_in_bytes": 4987360,
"init_progress": {
"percentage": "100%"
},
"total_entities": 7,
"active_entities": 7
}
```
The `profile` operation also provides information about each entity, such as the entity’s `last_sample_timestamp` and `last_active_timestamp`.
No anomaly results for an entity indicates that either the entity doesn't have any sample data or its model is removed from the model cache.
`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.
#### Request
```json
GET /_opensearch/_anomaly_detection/detectors/<detectorId>/_profile?_all=true&entity=i-00f28ec1eb8997686
{
"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"
}
```
For a historical detector, specify `_all` or `ad_task` to see information about its latest task:
#### Request
```json
GET _opensearch/_anomaly_detection/detectors/<detectorId>/_profile?_all
GET _opensearch/_anomaly_detection/detectors/<detectorId>/_profile/ad_task
```
#### Sample Responses
```json
{
"ad_task": {
"ad_task": {
"task_id": "JXxyG3YBv5IHYYfMlFS2",
"last_update_time": 1606778263543,
"state": "STOPPED",
"detector_id": "SwvxCHYBPhugfWD9QAL6",
"task_progress": 0.010480972,
"init_progress": 1,
"current_piece": 1578140400000,
"execution_start_time": 1606778262709,
"is_latest": true,
"task_type": "HISTORICAL",
"detector": {
"name": "historical_test1",
"description": "test",
"time_field": "timestamp",
"indices": [
"nab_art_daily_jumpsdown"
],
"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": "zgvyCHYBPhugfWD9Ap_F",
"feature_name": "sum",
"feature_enabled": true,
"aggregation_query": {
"sum": {
"sum": {
"field": "value"
}
}
}
},
{
"feature_id": "zwvyCHYBPhugfWD9Ap_G",
"feature_name": "max",
"feature_enabled": true,
"aggregation_query": {
"max": {
"max": {
"field": "value"
}
}
}
}
],
"ui_metadata": {
"features": {
"max": {
"aggregationBy": "max",
"aggregationOf": "value",
"featureType": "simple_aggs"
},
"sum": {
"aggregationBy": "sum",
"aggregationOf": "value",
"featureType": "simple_aggs"
}
},
"filters": [],
"filterType": "simple_filter"
},
"last_update_time": 1606467935713,
"detector_type": "HISTORICAL_SIGLE_ENTITY",
"detection_date_range": {
"start_time": 1577840400000,
"end_time": 1606463775000
}
}
},
"shingle_size": 8,
"rcf_total_updates": 1994,
"threshold_model_trained": true,
"threshold_model_training_data_size": 0,
"node_id": "Q9yznwxvTz-yJxtz7rJlLg"
}
}
```
---
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