[ML] Adds anomaly description as an alert message for anomaly detection rule type

x-pack/plugins/ml/common/util/anomaly_description.ts

@@ -0,0 +1,69 @@
+/*
+ * Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
+ * or more contributor license agreements. Licensed under the Elastic License
+ * 2.0; you may not use this file except in compliance with the Elastic License
+ * 2.0.
+ */
+
+import { i18n } from '@kbn/i18n';
+import { capitalize } from 'lodash';
+import { getSeverity, type MlAnomaliesTableRecordExtended } from '@kbn/ml-anomaly-utils';
+
+export function getAnomalyDescription(anomaly: MlAnomaliesTableRecordExtended): {
+  anomalyDescription: string;
+  mvDescription: string | undefined;
+} {
+  const source = anomaly.source;
+
+  let anomalyDescription = i18n.translate('xpack.ml.anomalyDescription.anomalyInLabel', {
+    defaultMessage: '{anomalySeverity} anomaly in {anomalyDetector}',
+    values: {
+      anomalySeverity: capitalize(getSeverity(anomaly.severity).label),
+      anomalyDetector: anomaly.detector,
+    },
+  });
+
+  if (anomaly.entityName !== undefined) {
+    anomalyDescription += i18n.translate('xpack.ml.anomalyDescription.foundForLabel', {
+      defaultMessage: ' found for {anomalyEntityName} {anomalyEntityValue}',
+      values: {
+        anomalyEntityName: anomaly.entityName,
+        anomalyEntityValue: anomaly.entityValue,
+      },
+    });
+  }
+
+  if (
+    source.partition_field_name !== undefined &&
+    source.partition_field_name !== anomaly.entityName
+  ) {
+    anomalyDescription += i18n.translate('xpack.ml.anomalyDescription.detectedInLabel', {
+      defaultMessage: ' detected in {sourcePartitionFieldName} {sourcePartitionFieldValue}',
+      values: {
+        sourcePartitionFieldName: source.partition_field_name,
+        sourcePartitionFieldValue: source.partition_field_value,
+      },
+    });
+  }
+
+  // Check for a correlatedByFieldValue in the source which will be present for multivariate analyses
+  // where the record is anomalous due to relationship with another 'by' field value.
+  let mvDescription: string = '';
+  if (source.correlated_by_field_value !== undefined) {
+    mvDescription = i18n.translate('xpack.ml.anomalyDescription.multivariateDescription', {
+      defaultMessage:
+        'multivariate correlations found in {sourceByFieldName}; ' +
+        '{sourceByFieldValue} is considered anomalous given {sourceCorrelatedByFieldValue}',
+      values: {
+        sourceByFieldName: source.by_field_name,
+        sourceByFieldValue: source.by_field_value,
+        sourceCorrelatedByFieldValue: source.correlated_by_field_value,
+      },
+    });
+  }
+
+  return {
+    anomalyDescription,
+    mvDescription,
+  };
+}

x-pack/plugins/ml/public/application/formatters/metric_change_description.ts → x-pack/plugins/ml/common/util/metric_change_description.ts

@@ -15,8 +15,8 @@ import { i18n } from '@kbn/i18n';
 // Returns an Object containing a text message and EuiIcon type to
 // describe how the actual value compares to the typical.
 export function getMetricChangeDescription(
-  actualProp: number[] | number,
-  typicalProp: number[] | number
+  actualProp: number[] | number | undefined,
+  typicalProp: number[] | number | undefined
 ) {
   if (actualProp === undefined || typicalProp === undefined) {
     return { iconType: 'empty', message: '' };

x-pack/plugins/ml/public/application/components/anomalies_table/anomaly_details.tsx

@@ -10,11 +10,9 @@
  * of the anomalies table.
  */
 
-import React, { FC, useState, useMemo } from 'react';
+import React, { FC, useMemo, useState } from 'react';
 import { i18n } from '@kbn/i18n';
 import { FormattedMessage } from '@kbn/i18n-react';
-import { capitalize } from 'lodash';
-
 import {
   EuiFlexGroup,
   EuiFlexItem,
@@ -27,17 +25,16 @@ import {
   useEuiTheme,
 } from '@elastic/eui';
 import { isPopulatedObject } from '@kbn/ml-is-populated-object';
-import { getSeverity, type MlAnomaliesTableRecordExtended } from '@kbn/ml-anomaly-utils';
-
+import { type MlAnomaliesTableRecordExtended } from '@kbn/ml-anomaly-utils';
+import { getAnomalyDescription } from '../../../../common/util/anomaly_description';
 import { MAX_CHARS } from './anomalies_table_constants';
 import type { CategoryDefinition } from '../../services/ml_api_service/results';
 import { EntityCellFilter } from '../entity_cell';
 import { ExplorerJob } from '../../explorer/explorer_utils';
-
 import {
-  getInfluencersItems,
   AnomalyExplanationDetails,
   DetailsItems,
+  getInfluencersItems,
 } from './anomaly_details_utils';
 
 interface Props {
@@ -166,56 +163,7 @@ const Contents: FC<{
 };
 
 const Description: FC<{ anomaly: MlAnomaliesTableRecordExtended }> = ({ anomaly }) => {
-  const source = anomaly.source;
-
-  let anomalyDescription = i18n.translate('xpack.ml.anomaliesTable.anomalyDetails.anomalyInLabel', {
-    defaultMessage: '{anomalySeverity} anomaly in {anomalyDetector}',
-    values: {
-      anomalySeverity: capitalize(getSeverity(anomaly.severity).label),
-      anomalyDetector: anomaly.detector,
-    },
-  });
-  if (anomaly.entityName !== undefined) {
-    anomalyDescription += i18n.translate('xpack.ml.anomaliesTable.anomalyDetails.foundForLabel', {
-      defaultMessage: ' found for {anomalyEntityName} {anomalyEntityValue}',
-      values: {
-        anomalyEntityName: anomaly.entityName,
-        anomalyEntityValue: anomaly.entityValue,
-      },
-    });
-  }
-
-  if (
-    source.partition_field_name !== undefined &&
-    source.partition_field_name !== anomaly.entityName
-  ) {
-    anomalyDescription += i18n.translate('xpack.ml.anomaliesTable.anomalyDetails.detectedInLabel', {
-      defaultMessage: ' detected in {sourcePartitionFieldName} {sourcePartitionFieldValue}',
-      values: {
-        sourcePartitionFieldName: source.partition_field_name,
-        sourcePartitionFieldValue: source.partition_field_value,
-      },
-    });
-  }
-
-  // Check for a correlatedByFieldValue in the source which will be present for multivariate analyses
-  // where the record is anomalous due to relationship with another 'by' field value.
-  let mvDescription;
-  if (source.correlated_by_field_value !== undefined) {
-    mvDescription = i18n.translate(
-      'xpack.ml.anomaliesTable.anomalyDetails.multivariateDescription',
-      {
-        defaultMessage:
-          'multivariate correlations found in {sourceByFieldName}; ' +
-          '{sourceByFieldValue} is considered anomalous given {sourceCorrelatedByFieldValue}',
-        values: {
-          sourceByFieldName: source.by_field_name,
-          sourceByFieldValue: source.by_field_value,
-          sourceCorrelatedByFieldValue: source.correlated_by_field_value,
-        },
-      }
-    );
-  }
+  const { anomalyDescription, mvDescription } = getAnomalyDescription(anomaly);
 
   return (
     <>

x-pack/plugins/ml/public/application/components/anomalies_table/description_cell.js

@@ -10,7 +10,7 @@ import React from 'react';
 
 import { EuiFlexGroup, EuiFlexItem, EuiIcon, EuiText } from '@elastic/eui';
 
-import { getMetricChangeDescription } from '../../formatters/metric_change_description';
+import { getMetricChangeDescription } from '../../../../common/util/metric_change_description';
 
 /*
  * Component for rendering the description cell in the anomalies table, which provides a

x-pack/plugins/ml/public/shared.ts

@@ -13,7 +13,7 @@ export * from '../common/types/audit_message';
 
 export * from '../common/util/validators';
 
-export * from './application/formatters/metric_change_description';
+export * from '../common/util/metric_change_description';
 export * from './application/components/field_stats_flyout';
 export * from './application/data_frame_analytics/common';
 

x-pack/plugins/ml/server/lib/alerts/alerting_service.ts

@@ -9,7 +9,7 @@ import Boom from '@hapi/boom';
 import { i18n } from '@kbn/i18n';
 import rison from '@kbn/rison';
 import type { Duration } from 'moment/moment';
-import { memoize, pick } from 'lodash';
+import { capitalize, get, memoize, pick } from 'lodash';
 import {
   FIELD_FORMAT_IDS,
   type IFieldFormat,
@@ -22,9 +22,13 @@ import {
   type MlAnomalyRecordDoc,
   type MlAnomalyResultType,
   ML_ANOMALY_RESULT_TYPE,
+  MlAnomaliesTableRecordExtended,
 } from '@kbn/ml-anomaly-utils';
 import { DEFAULT_SPACE_ID } from '@kbn/spaces-plugin/common';
 import { ALERT_REASON, ALERT_URL } from '@kbn/rule-data-utils';
+import { MlJob } from '@elastic/elasticsearch/lib/api/types';
+import { getAnomalyDescription } from '../../../common/util/anomaly_description';
+import { getMetricChangeDescription } from '../../../common/util/metric_change_description';
 import type { MlClient } from '../ml_client';
 import type {
   MlAnomalyDetectionAlertParams,
@@ -184,6 +188,8 @@ export function alertingServiceProvider(
 ) {
   type FieldFormatters = AwaitReturnType<ReturnType<typeof getFormatters>>;
 
+  let jobs: MlJob[] = [];
+
   /**
    * Provides formatters based on the data view of the datafeed index pattern
    * and set of default formatters for fallback.
@@ -397,6 +403,72 @@ export function alertingServiceProvider(
     return alertInstanceKey;
   };
 
+  const getAlertMessage = (
+    resultType: MlAnomalyResultType,
+    source: Record<string, unknown>
+  ): string => {
+    let message = i18n.translate('xpack.ml.alertTypes.anomalyDetectionAlertingRule.alertMessage', {
+      defaultMessage:
+        'Alerts are raised based on real-time scores. Remember that scores may be adjusted over time as data continues to be analyzed.',
+    });
+
+    if (resultType === ML_ANOMALY_RESULT_TYPE.RECORD) {
+      const recordSource = source as MlAnomalyRecordDoc;
+
+      const detectorsByJob = jobs.reduce((acc, job) => {
+        acc[job.job_id] = job.analysis_config.detectors.reduce((innterAcc, detector) => {
+          innterAcc[detector.detector_index!] = detector.detector_description;
+          return innterAcc;
+        }, {} as Record<number, string | undefined>);
+        return acc;
+      }, {} as Record<string, Record<number, string | undefined>>);
+
+      const detectorDescription = get(detectorsByJob, [
+        recordSource.job_id,
+        recordSource.detector_index,
+      ]);
+
+      const record = {
+        source: recordSource,
+        detector: detectorDescription ?? recordSource.function_description,
+        severity: recordSource.record_score,
+      } as MlAnomaliesTableRecordExtended;
+      const entityName = getEntityFieldName(recordSource);
+      if (entityName !== undefined) {
+        record.entityName = entityName;
+        record.entityValue = getEntityFieldValue(recordSource);
+      }
+
+      const { anomalyDescription, mvDescription } = getAnomalyDescription(record);
+
+      const anomalyDescriptionSummary = `${anomalyDescription}${
+        mvDescription ? ` (${mvDescription})` : ''
+      }`;
+
+      let actual = recordSource.actual;
+      let typical = recordSource.typical;
+      if (
+        (!isDefined(actual) || !isDefined(typical)) &&
+        Array.isArray(recordSource.causes) &&
+        recordSource.causes.length === 1
+      ) {
+        actual = recordSource.causes[0].actual;
+        typical = recordSource.causes[0].typical;
+      }
+
+      let metricChangeDescription = '';
+      if (isDefined(actual) && isDefined(typical)) {
+        metricChangeDescription = capitalize(getMetricChangeDescription(actual, typical).message);
+      }
+
+      message = `${anomalyDescriptionSummary}. ${
+        metricChangeDescription ? `${metricChangeDescription}.` : ''
+      }`;
+    }
+
+    return message;
+  };
+
   /**
    * Returns a callback for formatting elasticsearch aggregation response
    * to the alert-as-data document.
@@ -419,14 +491,10 @@ export function alertingServiceProvider(
       const topAnomaly = requestedAnomalies[0];
       const timestamp = topAnomaly._source.timestamp;
 
+      const message = getAlertMessage(resultType, topAnomaly._source);
+
       return {
-        [ALERT_REASON]: i18n.translate(
-          'xpack.ml.alertTypes.anomalyDetectionAlertingRule.alertMessage',
-          {
-            defaultMessage:
-              'Alerts are raised based on real-time scores. Remember that scores may be adjusted over time as data continues to be analyzed.',
-          }
-        ),
+        [ALERT_REASON]: message,
         job_id: [...new Set(requestedAnomalies.map((h) => h._source.job_id))][0],
         is_interim: requestedAnomalies.some((h) => h._source.is_interim),
         anomaly_timestamp: timestamp,
@@ -495,14 +563,12 @@ export function alertingServiceProvider(
       const alertInstanceKey = getAlertInstanceKey(topAnomaly._source);
       const timestamp = topAnomaly._source.timestamp;
       const bucketSpanInSeconds = topAnomaly._source.bucket_span;
+      const message = getAlertMessage(resultType, topAnomaly._source);
 
       return {
         count: aggTypeResults.doc_count,
         key: v.key,
-        message: i18n.translate('xpack.ml.alertTypes.anomalyDetectionAlertingRule.alertMessage', {
-          defaultMessage:
-            'Alerts are raised based on real-time scores. Remember that scores may be adjusted over time as data continues to be analyzed.',
-        }),
+        message,
         alertInstanceKey,
         jobIds: [...new Set(requestedAnomalies.map((h) => h._source.job_id))],
         isInterim: requestedAnomalies.some((h) => h._source.is_interim),
@@ -564,6 +630,8 @@ export function alertingServiceProvider(
     // Extract jobs from group ids and make sure provided jobs assigned to a current space
     const jobsResponse = (await mlClient.getJobs({ job_id: jobAndGroupIds.join(',') })).jobs;
 
+    jobs = jobsResponse;
+
     if (jobsResponse.length === 0) {
       // Probably assigned groups don't contain any jobs anymore.
       throw new Error("Couldn't find the job with provided id");
@@ -699,6 +767,9 @@ export function alertingServiceProvider(
     // Extract jobs from group ids and make sure provided jobs assigned to a current space
     const jobsResponse = (await mlClient.getJobs({ job_id: jobAndGroupIds.join(',') })).jobs;
 
+    // Cache jobs response
+    jobs = jobsResponse;
+
     if (jobsResponse.length === 0) {
       // Probably assigned groups don't contain any jobs anymore.
       return;

x-pack/plugins/translations/translations/fr-FR.json

@@ -24189,13 +24189,9 @@
     "xpack.ml.annotationsTable.howToCreateAnnotationDescription": "Pour créer une annotation, ouvrir le {linkToSingleMetricView}",
     "xpack.ml.anomaliesTable.anomalyDetails.anomalyDescriptionListMoreLinkText": "et {othersCount} en plus",
     "xpack.ml.anomaliesTable.anomalyDetails.anomalyExplanationTitle": "Explication des anomalies {learnMoreLink}",
-    "xpack.ml.anomaliesTable.anomalyDetails.anomalyInLabel": "{anomalySeverity} anomalie dans {anomalyDetector}",
     "xpack.ml.anomaliesTable.anomalyDetails.anomalyTimeRangeLabel": "{anomalyTime} à {anomalyEndTime}",
     "xpack.ml.anomaliesTable.anomalyDetails.causeValuesDescription": "{causeEntityValue} (actuel {actualValue}, typique {typicalValue}, probabilité {probabilityValue})",
     "xpack.ml.anomaliesTable.anomalyDetails.causeValuesTitle": "Valeurs {causeEntityName}",
-    "xpack.ml.anomaliesTable.anomalyDetails.detectedInLabel": " détecté dans {sourcePartitionFieldName} {sourcePartitionFieldValue}",
-    "xpack.ml.anomaliesTable.anomalyDetails.foundForLabel": " trouvé pour {anomalyEntityName} {anomalyEntityValue}",
-    "xpack.ml.anomaliesTable.anomalyDetails.multivariateDescription": "corrélations multi-variable trouvées dans {sourceByFieldName} ; {sourceByFieldValue} est considérée comme une anomalie étant donné {sourceCorrelatedByFieldValue}",
     "xpack.ml.anomaliesTable.anomalyDetails.regexDescriptionTooltip": "L'expression normale qui est utilisée pour rechercher des valeurs correspondant à la catégorie (peut être tronquée à une limite de caractères max de {maxChars})",
     "xpack.ml.anomaliesTable.anomalyDetails.termsDescriptionTooltip": "Une liste des jetons communs séparés par un espace correspondant aux valeurs de la catégorie (peut être tronquée à une limite de caractères max. de {maxChars})",
     "xpack.ml.anomaliesTable.anomalyExplanationDetails.anomalyType.dip": "Baisse sur {anomalyLength, plural, one {# compartiment} many {# compartiments} other {# compartiments}}",

x-pack/plugins/translations/translations/ja-JP.json

@@ -24204,13 +24204,9 @@
     "xpack.ml.annotationsTable.howToCreateAnnotationDescription": "注釈を作成するには、{linkToSingleMetricView} を開きます",
     "xpack.ml.anomaliesTable.anomalyDetails.anomalyDescriptionListMoreLinkText": "他{othersCount}件",
     "xpack.ml.anomaliesTable.anomalyDetails.anomalyExplanationTitle": "異常の説明{learnMoreLink}",
-    "xpack.ml.anomaliesTable.anomalyDetails.anomalyInLabel": "{anomalyDetector} の {anomalySeverity} の異常",
     "xpack.ml.anomaliesTable.anomalyDetails.anomalyTimeRangeLabel": "{anomalyTime}から{anomalyEndTime}",
     "xpack.ml.anomaliesTable.anomalyDetails.causeValuesDescription": "{causeEntityValue} (実際値 {actualValue}、通常値 {typicalValue}、確率 {probabilityValue})",
     "xpack.ml.anomaliesTable.anomalyDetails.causeValuesTitle": "{causeEntityName}値",
-    "xpack.ml.anomaliesTable.anomalyDetails.detectedInLabel": " {sourcePartitionFieldName} {sourcePartitionFieldValue} で検知",
-    "xpack.ml.anomaliesTable.anomalyDetails.foundForLabel": " {anomalyEntityName} {anomalyEntityValue}に対して見つかりました",
-    "xpack.ml.anomaliesTable.anomalyDetails.multivariateDescription": "{sourceByFieldName} で多変量相関が見つかりました; {sourceByFieldValue} は {sourceCorrelatedByFieldValue} のため異例とみなされます",
     "xpack.ml.anomaliesTable.anomalyDetails.regexDescriptionTooltip": "カテゴリーが一致する値を検索するのに使用される正規表現です（{maxChars}文字の制限で切り捨てられている可能性があります）",
     "xpack.ml.anomaliesTable.anomalyDetails.termsDescriptionTooltip": "カテゴリーの値で一致している共通のトークンのスペース区切りのリストです（{maxChars}文字の制限で切り捨てられている可能性があります）",
     "xpack.ml.anomaliesTable.anomalyExplanationDetails.anomalyType.dip": "{anomalyLength, plural, other {#個のバケット}}でディップ",

x-pack/plugins/translations/translations/zh-CN.json

@@ -24203,13 +24203,9 @@
     "xpack.ml.annotationsTable.howToCreateAnnotationDescription": "要创建注释，请打开 {linkToSingleMetricView}",
     "xpack.ml.anomaliesTable.anomalyDetails.anomalyDescriptionListMoreLinkText": "及另外 {othersCount} 个",
     "xpack.ml.anomaliesTable.anomalyDetails.anomalyExplanationTitle": "异常解释 {learnMoreLink}",
-    "xpack.ml.anomaliesTable.anomalyDetails.anomalyInLabel": "{anomalyDetector} 中的 {anomalySeverity} 异常",
     "xpack.ml.anomaliesTable.anomalyDetails.anomalyTimeRangeLabel": "{anomalyTime} 至 {anomalyEndTime}",
     "xpack.ml.anomaliesTable.anomalyDetails.causeValuesDescription": "{causeEntityValue}（实际 {actualValue}典型 {typicalValue}可能性 {probabilityValue}）",
     "xpack.ml.anomaliesTable.anomalyDetails.causeValuesTitle": "{causeEntityName} 值",
-    "xpack.ml.anomaliesTable.anomalyDetails.detectedInLabel": " 在 {sourcePartitionFieldName} {sourcePartitionFieldValue} 检测到",
-    "xpack.ml.anomaliesTable.anomalyDetails.foundForLabel": " 已为 {anomalyEntityName} {anomalyEntityValue} 找到",
-    "xpack.ml.anomaliesTable.anomalyDetails.multivariateDescription": "{sourceByFieldName} 中找到多变量关联；如果{sourceCorrelatedByFieldValue}，{sourceByFieldValue} 将被视为有异常",
     "xpack.ml.anomaliesTable.anomalyDetails.regexDescriptionTooltip": "用于搜索匹配该类别的值（可能已截短至最大字符限制 {maxChars}）的正则表达式",
     "xpack.ml.anomaliesTable.anomalyDetails.termsDescriptionTooltip": "该类别的值（可能已截短至最大字符限制（{maxChars}）中匹配的常见令牌的空格分隔列表",
     "xpack.ml.anomaliesTable.anomalyExplanationDetails.anomalyType.dip": "{anomalyLength, plural, other {# 个存储桶}}上出现谷值",