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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
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Introduced 1.0
{: .label .label-purple }
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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 _plugins/_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 _plugins/_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
}
```
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
---
## Preview detector
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Introduced 1.0
{: .label .label-purple }
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Passes a date range to the anomaly detector to return any anomalies within that date range.
#### Request
```json
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POST _plugins/_anomaly_detection/detectors/_preview
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{
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"period_start": 1612982516000,
"period_end": 1614278539000,
"detector": {
"name": "test-detector",
"description": "test nab_art_daily_jumpsdown",
"time_field": "timestamp",
"indices": [
"nab_art_daily_jumpsdown"
],
"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"
}
}
}
}
]
}
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}
```
#### 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"
}
]
}
...
```
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Or, you can specify the detector ID:
```json
POST _plugins/_anomaly_detection/detectors/_preview
{
"detector_id": "sYkUvHcBiZv51f-Lv8QN",
"period_start": 1612982516000,
"period_end": 1614278539000
}
```
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---
## Start detector job
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Introduced 1.0
{: .label .label-purple }
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Starts a real-time or historical anomaly detector job.
#### Request
```json
POST _plugins/_anomaly_detection/detectors/< detectorId > /_start
```
#### Sample response
```json
{
"_id" : "m4ccEnIBTXsGi3mvMt9p",
"_version" : 1,
"_seq_no" : 6,
"_primary_term" : 1
}
```
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To start historical analysis:
```json
POST _plugins/_anomaly_detection/detectors/< detectorId > /_start
{
"start_time": 1503168590000,
"end_time": 1617301324000
}
```
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---
## Stop detector job
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Introduced 1.0
{: .label .label-purple }
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Stops a real-time or historical anomaly detector job.
#### Request
```json
POST _plugins/_anomaly_detection/detectors/< detectorId > /_stop
```
#### Sample response
```json
Stopped detector: m4ccEnIBTXsGi3mvMt9p
```
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To stop historical analysis:
```jsom
POST _plugins/_anomaly_detection/detectors/< detectorId > /_stop?historical=true
```
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---
## Search detector result
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Introduced 1.0
{: .label .label-purple }
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Returns all results for a search query.
#### Request
```json
GET _plugins/_anomaly_detection/detectors/results/_search
POST _plugins/_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": ".opendistro-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": ".opendistro-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 entity 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 _plugins/_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": ".opendistro-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": ".opendistro-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": ".opendistro-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
]
}
]
}
}
```
To query the anomaly results with `task_id` :
#### Request
```json
GET _plugins/_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": ".opendistro-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
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Introduced 1.0
{: .label .label-purple }
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Deletes a detector based on the `detector_id` .
To delete a detector, you need to first stop the detector.
#### Request
```json
DELETE _plugins/_anomaly_detection/detectors/< detectorId >
```
#### Sample response
```json
{
"_index" : ".opendistro-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
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Introduced 1.0
{: .label .label-purple }
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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 _plugins/_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 _plugins/_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
2021-07-26 19:14:22 -04:00
Introduced 1.0
{: .label .label-purple }
2021-05-28 13:48:19 -04:00
Returns all information about a detector based on the `detector_id` .
#### Request
```json
GET _plugins/_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 _plugins/_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 _plugins/_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
2021-07-26 19:14:22 -04:00
Introduced 1.0
{: .label .label-purple }
2021-05-28 13:48:19 -04:00
Returns all anomaly detectors for a search query.
#### Request
```json
GET _plugins/_anomaly_detection/detectors/_search
POST _plugins/_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": ".opendistro-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
2021-07-26 19:14:22 -04:00
Introduced 1.0
{: .label .label-purple }
2021-05-28 13:48:19 -04:00
Provides information about how the plugin is performing.
#### Request
```json
GET _plugins/_anomaly_detection/stats
GET _plugins/_anomaly_detection/< nodeId > /stats
GET _plugins/_anomaly_detection/< nodeId > /stats/< stat >
GET _plugins/_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
2021-07-26 19:14:22 -04:00
Introduced 1.0
{: .label .label-purple }
2021-05-28 13:48:19 -04:00
Create a monitor to set up alerts for the detector.
#### Request
```json
POST _plugins/_alerting/monitors
{
"type": "monitor",
"name": "test-monitor",
"enabled": true,
"schedule": {
"period": {
"interval": 20,
"unit": "MINUTES"
}
},
"inputs": [
{
"search": {
"indices": [
".opendistro-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": [
".opendistro-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
2021-07-26 19:14:22 -04:00
Introduced 1.0
{: .label .label-purple }
2021-05-28 13:48:19 -04:00
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 _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
```json
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",
"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 _plugins/_anomaly_detection/detectors/< detectorId > /_profile/total_size_in_bytes
{
"total_size_in_bytes" : 13369344
}
```
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.
#### Request
```json
GET /_plugins/_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’ `last_sample_timestamp` and `last_active_timestamp` .
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.
`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’
#### Request
```json
GET /_plugins/_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 _plugins/_anomaly_detection/detectors/< detectorId > /_profile?_all
GET _plugins/_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"
}
}
```
---
