--- title: 시계열 이상 조사 description: 메트릭 시계열 요청에서 가장 심각한 이상을 조사하고 결정론적 결과를 반환합니다. 그룹화 여부와 관계없이 메트릭 쿼리가 지원됩니다. 이 API 버전은 정확히 하나의 요청을 수락하며 최대 하나의 이상을 반환합니다. breadcrumbs: 문서 > API > 시계열 이상 조사 --- > For the complete documentation index, see [llms.txt](https://dnd37xeb23o8n.cloudfront.net/jen.gilbert/astro-base/llms.txt). # 시계열 이상 조사 ## v2 (latest) {% alert level="warning" %} **Note**: This endpoint is in preview and is subject to change. If you have any feedback, contact [Datadog support](https://docs.datadoghq.com/help.md). {% /alert %} | Datadog site | API endpoint | | ----------------- | --------------------------------------------------------------------------- | | app.datadoghq.com | POST https://api.datadoghq.com/api/v2/timeseries-anomaly-investigations | | us3.datadoghq.com | POST https://api.us3.datadoghq.com/api/v2/timeseries-anomaly-investigations | | us5.datadoghq.com | POST https://api.us5.datadoghq.com/api/v2/timeseries-anomaly-investigations | | app.datadoghq.eu | POST https://api.datadoghq.eu/api/v2/timeseries-anomaly-investigations | | ap1.datadoghq.com | POST https://api.ap1.datadoghq.com/api/v2/timeseries-anomaly-investigations | | ap2.datadoghq.com | POST https://api.ap2.datadoghq.com/api/v2/timeseries-anomaly-investigations | | uk1.datadoghq.com | POST https://api.uk1.datadoghq.com/api/v2/timeseries-anomaly-investigations | | app.ddog-gov.com | POST https://api.ddog-gov.com/api/v2/timeseries-anomaly-investigations | | us2.ddog-gov.com | POST https://api.us2.ddog-gov.com/api/v2/timeseries-anomaly-investigations | ### Overview 메트릭 시계열 요청에서 가장 심각한 이상을 조사하고 결정론적 결과를 반환합니다. 그룹화 여부와 관계없이 메트릭 쿼리가 지원됩니다. 이 API 버전은 정확히 하나의 요청을 수락하며 최대 하나의 이상을 반환합니다. This endpoint requires all of the following permissions: - `timeseries_query` - `metrics_read` OAuth apps require the `timeseries_query`, `metrics_read` authorization [scope](https://dnd37xeb23o8n.cloudfront.net/jen.gilbert/astro-base/ko/api/latest/scopes.md#timeseries-anomaly-investigations) to access this endpoint. ### Request #### Body Data (required) 조사할 메트릭 시계열 요청입니다. 요청 본문은 2MiB를 초과할 수 없습니다. {% tabs %} {% tab label="Model" %} | Parent field | Field | Type | Description | | ------------ | ------------------------ | -------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | | data [*required*] | object | 메트릭 시계열의 이상을 조사하도록 요청합니다. | | data | attributes [*required*] | object | Attributes of an anomaly investigation request. | | attributes | requests [*required*] | [object] | Timeseries requests to investigate. This API version accepts exactly one request. | | requests | formulas [*required*] | [object] | Formulas to evaluate. Each formula may contain an explicit `anomalies()` call or a supported metrics expression. | | formulas | formula [*required*] | string | Formula expression referencing one or more named queries. When the expression does not contain an explicit `anomalies()` call, the endpoint applies the default Watchdog Explains anomaly detection configuration. | | formulas | limit | object | Optional formula limit accepted for compatibility with Timeseries API requests. Formula limits have no effect on timeseries queries. | | limit | count | int64 | Requested result limit. This field has no effect on a timeseries anomaly investigation. | | limit | order | enum | Sort order used when applying a formula series limit. Allowed enum values: `asc`, `desc`. | | requests | from [*required*] | int64 | Start of the investigation time window in milliseconds since the Unix epoch. | | requests | interval | int64 | Optional requested aggregation interval in milliseconds. | | requests | queries [*required*] | [object] | Metrics queries referenced by the formulas. | | queries | aggregator | string | Optional scalar aggregator accepted for request compatibility. This field is ignored for timeseries queries. | | queries | cross_org_uuids | [string] | Optional organization UUID used for a cross-organization query. Each query accepts at most one UUID; use separate queries for separate organizations. Influential-tag analysis is currently unsupported for cross-organization queries, but anomaly detection still runs. | | queries | data_source [*required*] | enum | Data source for an anomaly investigation query. Allowed enum values: `metrics`. | | queries | name [*required*] | string | Name used to reference this query from formulas. | | queries | query [*required*] | string | Datadog metrics query expression. | | requests | to [*required*] | int64 | End of the investigation time window in milliseconds since the Unix epoch. Must be later than `from`. | | data | type [*required*] | enum | Resource type for a timeseries anomaly investigation. Allowed enum values: `timeseries_anomaly_investigation`. | {% /tab %} {% tab label="Example" %} ```json { "data": { "attributes": { "requests": [ { "formulas": [ { "formula": "query1", "limit": { "count": 10, "order": "desc" } } ], "from": 1754406000000, "interval": 60000, "queries": [ { "aggregator": "avg", "cross_org_uuids": [ "00000000-0000-0000-0000-000000000000" ], "data_source": "metrics", "name": "query1", "query": "avg:system.cpu.user{env:prod} by {service}" } ], "to": 1754423940000 } ] }, "type": "timeseries_anomaly_investigation" } } ``` {% /tab %} {% /tabs %} ### Response {% tabs %} {% tab label="200" %} OK {% tabs %} {% tab label="Model" %} Response containing the anomaly investigation results and timeseries metadata. | Parent field | Field | Type | Description | | ---------------------- | --------------------------------- | --------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | | data [*required*] | object | JSON:API resource containing anomaly investigation results. | | data | attributes [*required*] | object | Attributes of an anomaly investigation response. | | attributes | results [*required*] | [object] | Results returned in the same order as the submitted requests. This API version returns exactly one result. | | results | anomalies [*required*] | [object] | Detected anomalies, ordered by significance. This API version returns at most three anomalies across the submitted request. | | anomalies | anomaly_detection [*required*] | object | Anomaly detection configuration used for the result. | | anomaly_detection | configuration_source [*required*] | enum | Source of the anomaly detection configuration. Allowed enum values: `request_formula`, `watchdog_explains_default`. | | anomaly_detection | profile [*required*] | string | Applied Watchdog Explains profile, or null when the request supplied an explicit `anomalies()` formula. The current Watchdog profile is `watchdog_explains_v1`. | | anomalies | detected_interval [*required*] | object | Inclusive time interval in milliseconds since the Unix epoch. | | detected_interval | end [*required*] | int64 | Timestamp of the final point in the interval. | | detected_interval | start [*required*] | int64 | Inclusive start of the interval. | | anomalies | display_interval [*required*] | object | Inclusive time interval in milliseconds since the Unix epoch. | | display_interval | end [*required*] | int64 | Timestamp of the final point in the interval. | | display_interval | start [*required*] | int64 | Inclusive start of the interval. | | anomalies | findings [*required*] | [] | Deterministic explanations for the anomaly, ordered by importance. | | findings | | object | Finding that attributes an anomaly to an influential tag. | | | description [*required*] | string | Deterministic explanation of the finding. | | | headline [*required*] | string | Concise, deterministic finding title. | | | tag [*required*] | object | Structured tag evidence for an influential-tag finding. | | tag | influence_type [*required*] | enum | Kind of influence a tag has on a series. Allowed enum values: `shape`, `value`. | | tag | key [*required*] | string | Influential tag key. | | tag | rating [*required*] | double | Influence rating from 1 through 5. | | tag | synonyms [*required*] | [object] | Tags grouped with this tag by Variation of Influence synonym analysis. | | synonyms | key [*required*] | string | Synonymous tag key. | | synonyms | values [*required*] | [string] | Values associated with the synonymous tag. | | tag | values [*required*] | [string] | Influential values for the tag key. | | | type [*required*] | enum | Finding category for an influential tag. Allowed enum values: `influential_tag`. | | findings | | object | Finding that describes the anomaly when completed analysis produces no displayable influential tags. | | | description [*required*] | string | Deterministic explanation of the finding. | | | headline [*required*] | string | Concise, deterministic finding title. | | | type [*required*] | enum | Finding category for an anomaly without a displayable influential tag. Allowed enum values: `anomaly`. | | anomalies | maximum_deviation [*required*] | object | Most anomalous point within the detected interval. | | maximum_deviation | delta_from_boundary [*required*] | double | Absolute distance between the observed value and the nearest anomaly boundary. | | maximum_deviation | timestamp [*required*] | int64 | Point timestamp in milliseconds since the Unix epoch. | | maximum_deviation | value [*required*] | double | Observed value at the point. | | anomalies | series [*required*] | object | Logical series on which the anomaly was detected. | | series | group_tags [*required*] | [string] | Tags identifying the selected group. Empty for a query without grouping. | | series | label [*required*] | string | Display label for the selected series. | | series | query_index [*required*] | int64 | Zero-based index of the caller's formula that produced the series. | | anomalies | tag_analysis [*required*] | object | Summary of optional influential-tag enrichment. Count and key fields are present only when analysis completes; enrichment availability does not affect completion of the investigation result. | | tag_analysis | analyzed_tag_keys | [string] | Tag keys analyzed. Present only when analysis completes. | | tag_analysis | status [*required*] | enum | Outcome of optional influential-tag enrichment. Allowed enum values: `complete`, `unsupported`, `failed`. | | tag_analysis | tag_keys_analyzed | int64 | Number of tag keys analyzed. Present only when analysis completes. | | tag_analysis | tag_values_analyzed | int64 | Number of tag values analyzed. Present only when analysis completes. | | anomalies | type [*required*] | enum | Direction of an anomaly relative to its expected range. Allowed enum values: `spike`, `dip`. | | results | status [*required*] | enum | Status value indicating successful completion. Allowed enum values: `complete`. | | data | id [*required*] | enum | Stable identifier for an anomaly investigation response resource. Allowed enum values: `0`. | | data | type [*required*] | enum | Resource type for a timeseries anomaly investigation. Allowed enum values: `timeseries_anomaly_investigation`. | | | meta [*required*] | object | Timeseries execution metadata for the single request accepted by this API version. | | meta | from_date [*required*] | int64 | Effective start of the timeseries query in milliseconds since the Unix epoch. | | meta | interval [*required*] | int64 | Effective timeseries interval in milliseconds. | | meta | queries [*required*] | [object] | Execution status for the request's queries. | | queries | name [*required*] | string | Query name from the request. | | queries | status [*required*] | enum | Current execution status for a named query. Allowed enum values: `running`, `done`. | | meta | res_type [*required*] | enum | Response metadata type for a timeseries anomaly investigation. Allowed enum values: `timeseries_anomaly_investigation`. | | meta | results_warnings [*required*] | [object] | Non-fatal warnings produced while executing the investigation. | | results_warnings | message [*required*] | string | Human-readable warning message. | | results_warnings | name [*required*] | string | Machine-readable warning name. | | meta | to_date [*required*] | int64 | Effective end of the timeseries query in milliseconds since the Unix epoch. | {% /tab %} {% tab label="Example" %} ```json { "data": { "attributes": { "results": [ { "anomalies": [ { "anomaly_detection": { "configuration_source": "request_formula", "profile": null }, "detected_interval": { "end": 1754406120000, "start": 1754406060000 }, "display_interval": { "end": 1754406120000, "start": 1754406060000 }, "findings": [ [] ], "maximum_deviation": { "delta_from_boundary": 7, "timestamp": 1754406090000, "value": 42 }, "series": { "group_tags": [ "service:api" ], "label": "api", "query_index": 0 }, "tag_analysis": { "analyzed_tag_keys": [ "service", "env" ], "status": "complete", "tag_keys_analyzed": 2, "tag_values_analyzed": 4 }, "type": "spike" } ], "status": "complete" } ] }, "id": "0", "type": "timeseries_anomaly_investigation" }, "meta": { "from_date": 1754406000000, "interval": 60000, "queries": [ { "name": "query1", "status": "done" } ], "res_type": "timeseries_anomaly_investigation", "results_warnings": [ { "message": "Influential tag analysis failed for at least one detected anomaly.", "name": "tag_analysis_failed" } ], "to_date": 1754423940000 } } ``` {% /tab %} {% /tabs %} {% /tab %} {% tab label="400" %} Bad Request {% tabs %} {% tab label="Model" %} API error response. | Parent field | Field | Type | Description | | ------------ | ------------------- | -------- | ------------------------------------------------------------------------------- | | | errors [*required*] | [object] | A list of errors. | | errors | detail | string | A human-readable explanation specific to this occurrence of the error. | | errors | meta | object | Non-standard meta-information about the error | | errors | source | object | References to the source of the error. | | source | header | string | A string indicating the name of a single request header which caused the error. | | source | parameter | string | A string indicating which URI query parameter caused the error. | | source | pointer | string | A JSON pointer to the value in the request document that caused the error. | | errors | status | string | Status code of the response. | | errors | title | string | Short human-readable summary of the error. | {% /tab %} {% tab label="Example" %} ```json { "errors": [ { "detail": "Missing required attribute in body", "meta": {}, "source": { "header": "Authorization", "parameter": "limit", "pointer": "/data/attributes/title" }, "status": "400", "title": "Bad Request" } ] } ``` {% /tab %} {% /tabs %} {% /tab %} {% tab label="401" %} Unauthorized {% tabs %} {% tab label="Model" %} API error response. | Parent field | Field | Type | Description | | ------------ | ------------------- | -------- | ------------------------------------------------------------------------------- | | | errors [*required*] | [object] | A list of errors. | | errors | detail | string | A human-readable explanation specific to this occurrence of the error. | | errors | meta | object | Non-standard meta-information about the error | | errors | source | object | References to the source of the error. | | source | header | string | A string indicating the name of a single request header which caused the error. | | source | parameter | string | A string indicating which URI query parameter caused the error. | | source | pointer | string | A JSON pointer to the value in the request document that caused the error. | | errors | status | string | Status code of the response. | | errors | title | string | Short human-readable summary of the error. | {% /tab %} {% tab label="Example" %} ```json { "errors": [ { "detail": "Missing required attribute in body", "meta": {}, "source": { "header": "Authorization", "parameter": "limit", "pointer": "/data/attributes/title" }, "status": "400", "title": "Bad Request" } ] } ``` {% /tab %} {% /tabs %} {% /tab %} {% tab label="403" %} Forbidden {% tabs %} {% tab label="Model" %} API error response. | Parent field | Field | Type | Description | | ------------ | ------------------- | -------- | ------------------------------------------------------------------------------- | | | errors [*required*] | [object] | A list of errors. | | errors | detail | string | A human-readable explanation specific to this occurrence of the error. | | errors | meta | object | Non-standard meta-information about the error | | errors | source | object | References to the source of the error. | | source | header | string | A string indicating the name of a single request header which caused the error. | | source | parameter | string | A string indicating which URI query parameter caused the error. | | source | pointer | string | A JSON pointer to the value in the request document that caused the error. | | errors | status | string | Status code of the response. | | errors | title | string | Short human-readable summary of the error. | {% /tab %} {% tab label="Example" %} ```json { "errors": [ { "detail": "Missing required attribute in body", "meta": {}, "source": { "header": "Authorization", "parameter": "limit", "pointer": "/data/attributes/title" }, "status": "400", "title": "Bad Request" } ] } ``` {% /tab %} {% /tabs %} {% /tab %} {% tab label="413" %} Payload Too Large {% tabs %} {% tab label="Model" %} API error response. | Parent field | Field | Type | Description | | ------------ | ------------------- | -------- | ------------------------------------------------------------------------------- | | | errors [*required*] | [object] | A list of errors. | | errors | detail | string | A human-readable explanation specific to this occurrence of the error. | | errors | meta | object | Non-standard meta-information about the error | | errors | source | object | References to the source of the error. | | source | header | string | A string indicating the name of a single request header which caused the error. | | source | parameter | string | A string indicating which URI query parameter caused the error. | | source | pointer | string | A JSON pointer to the value in the request document that caused the error. | | errors | status | string | Status code of the response. | | errors | title | string | Short human-readable summary of the error. | {% /tab %} {% tab label="Example" %} ```json { "errors": [ { "detail": "Missing required attribute in body", "meta": {}, "source": { "header": "Authorization", "parameter": "limit", "pointer": "/data/attributes/title" }, "status": "400", "title": "Bad Request" } ] } ``` {% /tab %} {% /tabs %} {% /tab %} {% tab label="422" %} Unprocessable Entity {% tabs %} {% tab label="Model" %} API error response. | Parent field | Field | Type | Description | | ------------ | ------------------- | -------- | ------------------------------------------------------------------------------- | | | errors [*required*] | [object] | A list of errors. | | errors | detail | string | A human-readable explanation specific to this occurrence of the error. | | errors | meta | object | Non-standard meta-information about the error | | errors | source | object | References to the source of the error. | | source | header | string | A string indicating the name of a single request header which caused the error. | | source | parameter | string | A string indicating which URI query parameter caused the error. | | source | pointer | string | A JSON pointer to the value in the request document that caused the error. | | errors | status | string | Status code of the response. | | errors | title | string | Short human-readable summary of the error. | {% /tab %} {% tab label="Example" %} ```json { "errors": [ { "detail": "Missing required attribute in body", "meta": {}, "source": { "header": "Authorization", "parameter": "limit", "pointer": "/data/attributes/title" }, "status": "400", "title": "Bad Request" } ] } ``` {% /tab %} {% /tabs %} {% /tab %} {% tab label="429" %} Too many requests {% tabs %} {% tab label="Model" %} API error response. | Field | Type | Description | | ------------------- | -------- | ----------------- | | errors [*required*] | [string] | A list of errors. | {% /tab %} {% tab label="Example" %} ```json { "errors": [ "Bad Request" ] } ``` {% /tab %} {% /tabs %} {% /tab %} {% /tabs %} ### Code Example {% tabs %} {% tab label="Curl" %} ```bash # Set your Datadog site and credentials export DD_SITE="datadoghq.com" # Or us3.datadoghq.com, us5.datadoghq.com, datadoghq.eu, ap1.datadoghq.com, ap2.datadoghq.com, uk1.datadoghq.com, ddog-gov.com, us2.ddog-gov.com # Use a Personal Access Token or Service Access Token export DD_BEARER_TOKEN="" curl -X POST "https://api.${DD_SITE}/api/v2/timeseries-anomaly-investigations" \ -H "Accept: application/json" \ -H "Content-Type: application/json" \ -H "Authorization: Bearer ${DD_BEARER_TOKEN}" \ -d @- << EOF { "data": { "attributes": { "requests": [ { "formulas": [ { "formula": "query1" } ], "from": 1754406000000, "queries": [ { "data_source": "metrics", "name": "query1", "query": "avg:system.cpu.user{env:prod} by {service}" } ], "to": 1754423940000 } ] }, "type": "timeseries_anomaly_investigation" } } EOF ``` {% /tab %} {% tab label="Go" %} ```go // Investigate a timeseries anomaly returns "OK" response package main import ( "context" "encoding/json" "fmt" "os" "github.com/DataDog/datadog-api-client-go/v2/api/datadog" "github.com/DataDog/datadog-api-client-go/v2/api/datadogV2" ) func main() { body := datadogV2.TimeseriesAnomalyInvestigationRequest{ Data: datadogV2.TimeseriesAnomalyInvestigationRequestData{ Attributes: datadogV2.TimeseriesAnomalyInvestigationRequestAttributes{ Requests: []datadogV2.TimeseriesAnomalyInvestigationTimeseriesRequest{ { Formulas: []datadogV2.TimeseriesAnomalyInvestigationFormula{ { Formula: "query1", }, }, From: 1754406000000, Queries: []datadogV2.TimeseriesAnomalyInvestigationMetricQuery{ { DataSource: datadogV2.TIMESERIESANOMALYINVESTIGATIONDATASOURCE_METRICS, Name: "query1", Query: "avg:system.cpu.user{env:prod} by {service}", }, }, To: 1754423940000, }, }, }, Type: datadogV2.TIMESERIESANOMALYINVESTIGATIONTYPE_TIMESERIES_ANOMALY_INVESTIGATION, }, } ctx := datadog.NewDefaultContext(context.Background()) ctx = context.WithValue(ctx, datadog.ContextAccessToken, os.Getenv("DD_BEARER_TOKEN")) configuration := datadog.NewConfiguration() configuration.SetUnstableOperationEnabled("v2.CreateTimeseriesAnomalyInvestigation", true) apiClient := datadog.NewAPIClient(configuration) api := datadogV2.NewTimeseriesAnomalyInvestigationsApi(apiClient) resp, r, err := api.CreateTimeseriesAnomalyInvestigation(ctx, body) if err != nil { fmt.Fprintf(os.Stderr, "Error when calling `TimeseriesAnomalyInvestigationsApi.CreateTimeseriesAnomalyInvestigation`: %v\n", err) fmt.Fprintf(os.Stderr, "Full HTTP response: %v\n", r) } responseContent, _ := json.MarshalIndent(resp, "", " ") fmt.Fprintf(os.Stdout, "Response from `TimeseriesAnomalyInvestigationsApi.CreateTimeseriesAnomalyInvestigation`:\n%s\n", responseContent) } ``` #### Instructions First [install the library and its dependencies](https://dnd37xeb23o8n.cloudfront.net/api/latest.md?code-lang=go) and then save the example to `main.go` and run following commands: ```bash DD_SITE="datadoghq.com" DD_BEARER_TOKEN="" go run "main.go" ``` {% /tab %} {% tab label="Java" %} ```java // Investigate a timeseries anomaly returns "OK" response import com.datadog.api.client.ApiClient; import com.datadog.api.client.ApiException; import com.datadog.api.client.v2.api.TimeseriesAnomalyInvestigationsApi; import com.datadog.api.client.v2.model.TimeseriesAnomalyInvestigationDataSource; import com.datadog.api.client.v2.model.TimeseriesAnomalyInvestigationFormula; import com.datadog.api.client.v2.model.TimeseriesAnomalyInvestigationMetricQuery; import com.datadog.api.client.v2.model.TimeseriesAnomalyInvestigationRequest; import com.datadog.api.client.v2.model.TimeseriesAnomalyInvestigationRequestAttributes; import com.datadog.api.client.v2.model.TimeseriesAnomalyInvestigationRequestData; import com.datadog.api.client.v2.model.TimeseriesAnomalyInvestigationResponse; import com.datadog.api.client.v2.model.TimeseriesAnomalyInvestigationTimeseriesRequest; import com.datadog.api.client.v2.model.TimeseriesAnomalyInvestigationType; import java.util.Collections; public class Example { public static void main(String[] args) { ApiClient defaultClient = ApiClient.getDefaultApiClient(); defaultClient.setAccessToken(System.getenv("DD_BEARER_TOKEN")); defaultClient.setUnstableOperationEnabled("v2.createTimeseriesAnomalyInvestigation", true); TimeseriesAnomalyInvestigationsApi apiInstance = new TimeseriesAnomalyInvestigationsApi(defaultClient); TimeseriesAnomalyInvestigationRequest body = new TimeseriesAnomalyInvestigationRequest() .data( new TimeseriesAnomalyInvestigationRequestData() .attributes( new TimeseriesAnomalyInvestigationRequestAttributes() .requests( Collections.singletonList( new TimeseriesAnomalyInvestigationTimeseriesRequest() .formulas( Collections.singletonList( new TimeseriesAnomalyInvestigationFormula() .formula("query1"))) .from(1754406000000L) .queries( Collections.singletonList( new TimeseriesAnomalyInvestigationMetricQuery() .dataSource( TimeseriesAnomalyInvestigationDataSource .METRICS) .name("query1") .query( "avg:system.cpu.user{env:prod} by" + " {service}"))) .to(1754423940000L)))) .type(TimeseriesAnomalyInvestigationType.TIMESERIES_ANOMALY_INVESTIGATION)); try { TimeseriesAnomalyInvestigationResponse result = apiInstance.createTimeseriesAnomalyInvestigation(body); System.out.println(result); } catch (ApiException e) { System.err.println( "Exception when calling" + " TimeseriesAnomalyInvestigationsApi#createTimeseriesAnomalyInvestigation"); System.err.println("Status code: " + e.getCode()); System.err.println("Reason: " + e.getResponseBody()); System.err.println("Response headers: " + e.getResponseHeaders()); e.printStackTrace(); } } } ``` #### Instructions First [install the library and its dependencies](https://dnd37xeb23o8n.cloudfront.net/api/latest.md?code-lang=java) and then save the example to `Example.java` and run following commands: ```bash DD_SITE="datadoghq.com" DD_BEARER_TOKEN="" java "Example.java" ``` {% /tab %} {% tab label="Python" %} ```python """ Investigate a timeseries anomaly returns "OK" response """ from os import environ from datadog_api_client import ApiClient, Configuration from datadog_api_client.v2.api.timeseries_anomaly_investigations_api import TimeseriesAnomalyInvestigationsApi from datadog_api_client.v2.model.timeseries_anomaly_investigation_data_source import ( TimeseriesAnomalyInvestigationDataSource, ) from datadog_api_client.v2.model.timeseries_anomaly_investigation_formula import TimeseriesAnomalyInvestigationFormula from datadog_api_client.v2.model.timeseries_anomaly_investigation_metric_query import ( TimeseriesAnomalyInvestigationMetricQuery, ) from datadog_api_client.v2.model.timeseries_anomaly_investigation_request import TimeseriesAnomalyInvestigationRequest from datadog_api_client.v2.model.timeseries_anomaly_investigation_request_attributes import ( TimeseriesAnomalyInvestigationRequestAttributes, ) from datadog_api_client.v2.model.timeseries_anomaly_investigation_request_data import ( TimeseriesAnomalyInvestigationRequestData, ) from datadog_api_client.v2.model.timeseries_anomaly_investigation_timeseries_request import ( TimeseriesAnomalyInvestigationTimeseriesRequest, ) from datadog_api_client.v2.model.timeseries_anomaly_investigation_type import TimeseriesAnomalyInvestigationType body = TimeseriesAnomalyInvestigationRequest( data=TimeseriesAnomalyInvestigationRequestData( attributes=TimeseriesAnomalyInvestigationRequestAttributes( requests=[ TimeseriesAnomalyInvestigationTimeseriesRequest( formulas=[ TimeseriesAnomalyInvestigationFormula( formula="query1", ), ], _from=1754406000000, queries=[ TimeseriesAnomalyInvestigationMetricQuery( data_source=TimeseriesAnomalyInvestigationDataSource.METRICS, name="query1", query="avg:system.cpu.user{env:prod} by {service}", ), ], to=1754423940000, ), ], ), type=TimeseriesAnomalyInvestigationType.TIMESERIES_ANOMALY_INVESTIGATION, ), ) configuration = Configuration() configuration.access_token = environ["DD_BEARER_TOKEN"] configuration.unstable_operations["create_timeseries_anomaly_investigation"] = True with ApiClient(configuration) as api_client: api_instance = TimeseriesAnomalyInvestigationsApi(api_client) response = api_instance.create_timeseries_anomaly_investigation(body=body) print(response) ``` #### Instructions First [install the library and its dependencies](https://dnd37xeb23o8n.cloudfront.net/api/latest.md?code-lang=python) and then save the example to `example.py` and run following commands: ```bash DD_SITE="datadoghq.com" DD_BEARER_TOKEN="" python3 "example.py" ``` {% /tab %} {% tab label="Ruby" %} ```ruby # Investigate a timeseries anomaly returns "OK" response require "datadog_api_client" DatadogAPIClient.configure do |config| config.access_token = ENV["DD_BEARER_TOKEN"] config.unstable_operations["v2.create_timeseries_anomaly_investigation".to_sym] = true end api_instance = DatadogAPIClient::V2::TimeseriesAnomalyInvestigationsAPI.new body = DatadogAPIClient::V2::TimeseriesAnomalyInvestigationRequest.new({ data: DatadogAPIClient::V2::TimeseriesAnomalyInvestigationRequestData.new({ attributes: DatadogAPIClient::V2::TimeseriesAnomalyInvestigationRequestAttributes.new({ requests: [ DatadogAPIClient::V2::TimeseriesAnomalyInvestigationTimeseriesRequest.new({ formulas: [ DatadogAPIClient::V2::TimeseriesAnomalyInvestigationFormula.new({ formula: "query1", }), ], from: 1754406000000, queries: [ DatadogAPIClient::V2::TimeseriesAnomalyInvestigationMetricQuery.new({ data_source: DatadogAPIClient::V2::TimeseriesAnomalyInvestigationDataSource::METRICS, name: "query1", query: "avg:system.cpu.user{env:prod} by {service}", }), ], to: 1754423940000, }), ], }), type: DatadogAPIClient::V2::TimeseriesAnomalyInvestigationType::TIMESERIES_ANOMALY_INVESTIGATION, }), }) p api_instance.create_timeseries_anomaly_investigation(body) ``` #### Instructions First [install the library and its dependencies](https://dnd37xeb23o8n.cloudfront.net/api/latest.md?code-lang=ruby) and then save the example to `example.rb` and run following commands: ```bash DD_SITE="datadoghq.com" DD_BEARER_TOKEN="" rb "example.rb" ``` {% /tab %} {% tab label="Rust" %} ```rust // Investigate a timeseries anomaly returns "OK" response use datadog_api_client::datadog; use datadog_api_client::datadogV2::api_timeseries_anomaly_investigations::TimeseriesAnomalyInvestigationsAPI; use datadog_api_client::datadogV2::model::TimeseriesAnomalyInvestigationDataSource; use datadog_api_client::datadogV2::model::TimeseriesAnomalyInvestigationFormula; use datadog_api_client::datadogV2::model::TimeseriesAnomalyInvestigationMetricQuery; use datadog_api_client::datadogV2::model::TimeseriesAnomalyInvestigationRequest; use datadog_api_client::datadogV2::model::TimeseriesAnomalyInvestigationRequestAttributes; use datadog_api_client::datadogV2::model::TimeseriesAnomalyInvestigationRequestData; use datadog_api_client::datadogV2::model::TimeseriesAnomalyInvestigationTimeseriesRequest; use datadog_api_client::datadogV2::model::TimeseriesAnomalyInvestigationType; #[tokio::main] async fn main() { let body = TimeseriesAnomalyInvestigationRequest::new(TimeseriesAnomalyInvestigationRequestData::new( TimeseriesAnomalyInvestigationRequestAttributes::new(vec![ TimeseriesAnomalyInvestigationTimeseriesRequest::new( vec![TimeseriesAnomalyInvestigationFormula::new( "query1".to_string(), )], 1754406000000, vec![TimeseriesAnomalyInvestigationMetricQuery::new( TimeseriesAnomalyInvestigationDataSource::METRICS, "query1".to_string(), "avg:system.cpu.user{env:prod} by {service}".to_string(), )], 1754423940000, ), ]), TimeseriesAnomalyInvestigationType::TIMESERIES_ANOMALY_INVESTIGATION, )); let mut configuration = datadog::Configuration::new(); configuration .set_unstable_operation_enabled("v2.create_timeseries_anomaly_investigation", true); let api = TimeseriesAnomalyInvestigationsAPI::with_config(configuration); let resp = api.create_timeseries_anomaly_investigation(body).await; if let Ok(value) = resp { println!("{:#?}", value); } else { println!("{:#?}", resp.unwrap_err()); } } ``` #### Instructions First [install the library and its dependencies](https://dnd37xeb23o8n.cloudfront.net/api/latest.md?code-lang=rust) and then save the example to `src/main.rs` and run following commands: ```bash DD_SITE="datadoghq.com" DD_API_KEY="" DD_APP_KEY="" cargo run ``` {% /tab %} {% tab label="TypeScript" %} ```typescript /** * Investigate a timeseries anomaly returns "OK" response */ import { client, v2 } from "@datadog/datadog-api-client"; const configuration = client.createConfiguration({ authMethods: { AuthZ: { accessToken: process.env.DD_BEARER_TOKEN as string, }, }, }); configuration.unstableOperations["v2.createTimeseriesAnomalyInvestigation"] = true; const apiInstance = new v2.TimeseriesAnomalyInvestigationsApi(configuration); const params: v2.TimeseriesAnomalyInvestigationsApiCreateTimeseriesAnomalyInvestigationRequest = { body: { data: { attributes: { requests: [ { formulas: [ { formula: "query1", }, ], from: 1754406000000, queries: [ { dataSource: "metrics", name: "query1", query: "avg:system.cpu.user{env:prod} by {service}", }, ], to: 1754423940000, }, ], }, type: "timeseries_anomaly_investigation", }, }, }; apiInstance .createTimeseriesAnomalyInvestigation(params) .then((data: v2.TimeseriesAnomalyInvestigationResponse) => { console.log( "API called successfully. Returned data: " + JSON.stringify(data) ); }) .catch((error: any) => console.error(error)); ``` #### Instructions First [install the library and its dependencies](https://dnd37xeb23o8n.cloudfront.net/api/latest.md?code-lang=typescript) and then save the example to `example.ts` and run following commands: ```bash DD_SITE="datadoghq.com" DD_BEARER_TOKEN="" tsc "example.ts" ``` {% /tab %} {% /tabs %}