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https://github.com/elastic/kibana.git
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[APM] Revert multi-metric ML job. (#114961)
This commit is contained in:
parent
8aeaa5a2ff
commit
008421f170
12 changed files with 77 additions and 212 deletions
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@ -33,8 +33,6 @@ export function getSeverityColor(score: number) {
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return mlGetSeverityColor(score);
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}
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export const ML_TRANSACTION_LATENCY_DETECTOR_INDEX = 0;
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export const ML_ERRORS = {
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INVALID_LICENSE: i18n.translate(
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'xpack.apm.anomaly_detection.error.invalid_license',
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@ -1,25 +0,0 @@
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/*
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* Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
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* or more contributor license agreements. Licensed under the Elastic License
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* 2.0; you may not use this file except in compliance with the Elastic License
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* 2.0.
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*/
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export function apmMlAnomalyQuery(detectorIndex: 0 | 1 | 2) {
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return [
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{
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bool: {
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filter: [
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{
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terms: {
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result_type: ['model_plot', 'record'],
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},
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},
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{
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term: { detector_index: detectorIndex },
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},
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],
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},
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},
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];
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}
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@ -5,21 +5,21 @@
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* 2.0.
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*/
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import Boom from '@hapi/boom';
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import { Logger } from 'kibana/server';
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import { snakeCase } from 'lodash';
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import moment from 'moment';
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import uuid from 'uuid/v4';
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import { snakeCase } from 'lodash';
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import Boom from '@hapi/boom';
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import moment from 'moment';
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import { ML_ERRORS } from '../../../common/anomaly_detection';
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import {
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METRICSET_NAME,
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PROCESSOR_EVENT,
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} from '../../../common/elasticsearch_fieldnames';
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import { ProcessorEvent } from '../../../common/processor_event';
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import { environmentQuery } from '../../../common/utils/environment_query';
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import { withApmSpan } from '../../utils/with_apm_span';
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import { Setup } from '../helpers/setup_request';
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import {
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TRANSACTION_DURATION,
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PROCESSOR_EVENT,
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} from '../../../common/elasticsearch_fieldnames';
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import { APM_ML_JOB_GROUP, ML_MODULE_ID_APM_TRANSACTION } from './constants';
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import { withApmSpan } from '../../utils/with_apm_span';
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import { getAnomalyDetectionJobs } from './get_anomaly_detection_jobs';
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export async function createAnomalyDetectionJobs(
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@ -92,8 +92,8 @@ async function createAnomalyDetectionJob({
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query: {
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bool: {
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filter: [
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{ term: { [PROCESSOR_EVENT]: ProcessorEvent.metric } },
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{ term: { [METRICSET_NAME]: 'transaction' } },
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{ term: { [PROCESSOR_EVENT]: ProcessorEvent.transaction } },
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{ exists: { field: TRANSACTION_DURATION } },
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...environmentQuery(environment),
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],
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},
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@ -105,7 +105,7 @@ async function createAnomalyDetectionJob({
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job_tags: {
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environment,
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// identifies this as an APM ML job & facilitates future migrations
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apm_ml_version: 3,
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apm_ml_version: 2,
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},
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},
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},
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@ -11,11 +11,7 @@ import { estypes } from '@elastic/elasticsearch';
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import { ESSearchResponse } from '../../../../../../src/core/types/elasticsearch';
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import { MlPluginSetup } from '../../../../ml/server';
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import { PromiseReturnType } from '../../../../observability/typings/common';
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import {
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getSeverity,
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ML_ERRORS,
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ML_TRANSACTION_LATENCY_DETECTOR_INDEX,
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} from '../../../common/anomaly_detection';
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import { getSeverity, ML_ERRORS } from '../../../common/anomaly_detection';
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import { ENVIRONMENT_ALL } from '../../../common/environment_filter_values';
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import { getServiceHealthStatus } from '../../../common/service_health_status';
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import {
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@ -26,7 +22,6 @@ import { rangeQuery } from '../../../../observability/server';
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import { withApmSpan } from '../../utils/with_apm_span';
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import { getMlJobsWithAPMGroup } from '../anomaly_detection/get_ml_jobs_with_apm_group';
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import { Setup } from '../helpers/setup_request';
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import { apmMlAnomalyQuery } from '../../../common/utils/apm_ml_anomaly_query';
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export const DEFAULT_ANOMALIES: ServiceAnomaliesResponse = {
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mlJobIds: [],
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@ -61,7 +56,7 @@ export async function getServiceAnomalies({
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query: {
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bool: {
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filter: [
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...apmMlAnomalyQuery(ML_TRANSACTION_LATENCY_DETECTOR_INDEX),
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{ terms: { result_type: ['model_plot', 'record'] } },
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...rangeQuery(
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Math.min(end - 30 * 60 * 1000, start),
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end,
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@ -12,8 +12,6 @@ import { rangeQuery } from '../../../../../observability/server';
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import { asMutableArray } from '../../../../common/utils/as_mutable_array';
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import { withApmSpan } from '../../../utils/with_apm_span';
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import { Setup } from '../../helpers/setup_request';
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import { apmMlAnomalyQuery } from '../../../../common/utils/apm_ml_anomaly_query';
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import { ML_TRANSACTION_LATENCY_DETECTOR_INDEX } from '../../../../common/anomaly_detection';
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export type ESResponse = Exclude<
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PromiseReturnType<typeof anomalySeriesFetcher>,
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@ -42,7 +40,7 @@ export function anomalySeriesFetcher({
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query: {
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bool: {
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filter: [
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...apmMlAnomalyQuery(ML_TRANSACTION_LATENCY_DETECTOR_INDEX),
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{ terms: { result_type: ['model_plot', 'record'] } },
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{ term: { partition_field_value: serviceName } },
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{ term: { by_field_value: transactionType } },
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...rangeQuery(start, end, 'timestamp'),
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@ -1,29 +1,29 @@
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{
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"id": "apm_transaction",
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"title": "APM",
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"description": "Detect anomalies in transactions from your APM services for metric data.",
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"description": "Detect anomalies in transactions from your APM services.",
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"type": "Transaction data",
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"logoFile": "logo.json",
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"defaultIndexPattern": "apm-*-metric,metrics-apm*",
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"defaultIndexPattern": "apm-*-transaction",
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"query": {
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"bool": {
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"filter": [
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{ "term": { "processor.event": "metric" } },
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{ "term": { "metricset.name": "transaction" } }
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{ "term": { "processor.event": "transaction" } },
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{ "exists": { "field": "transaction.duration" } }
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]
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}
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},
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"jobs": [
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{
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"id": "apm_metrics",
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"file": "apm_metrics.json"
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"id": "high_mean_transaction_duration",
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"file": "high_mean_transaction_duration.json"
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}
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],
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"datafeeds": [
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{
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"id": "datafeed-apm_metrics",
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"file": "datafeed_apm_metrics.json",
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"job_id": "apm_metrics"
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"id": "datafeed-high_mean_transaction_duration",
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"file": "datafeed_high_mean_transaction_duration.json",
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"job_id": "high_mean_transaction_duration"
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}
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]
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}
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@ -1,53 +0,0 @@
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{
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"job_type": "anomaly_detector",
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"groups": [
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"apm"
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],
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"description": "Detects anomalies in transaction duration, throughput and error percentage for metric data.",
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"analysis_config": {
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"bucket_span": "15m",
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"summary_count_field_name" : "doc_count",
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"detectors" : [
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{
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"detector_description" : "high duration by transaction type for an APM service",
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"function" : "high_mean",
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"field_name" : "transaction_duration",
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"by_field_name" : "transaction.type",
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"partition_field_name" : "service.name"
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},
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{
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"detector_description" : "transactions per minute for an APM service",
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"function" : "mean",
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"field_name" : "transactions_per_min",
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"by_field_name" : "transaction.type",
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"partition_field_name" : "service.name"
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},
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{
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"detector_description" : "percent failed for an APM service",
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"function" : "high_mean",
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"field_name" : "transaction_failure_percentage",
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"by_field_name" : "transaction.type",
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"partition_field_name" : "service.name"
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}
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],
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"influencers" : [
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"transaction.type",
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"service.name"
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]
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},
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"analysis_limits": {
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"model_memory_limit": "32mb"
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},
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"data_description": {
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"time_field" : "@timestamp",
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"time_format" : "epoch_ms"
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},
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"model_plot_config": {
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"enabled" : true,
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"annotations_enabled" : true
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},
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"results_index_name" : "custom-apm",
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"custom_settings": {
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"created_by": "ml-module-apm-transaction"
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}
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}
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@ -1,95 +0,0 @@
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{
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"job_id": "JOB_ID",
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"indices": [
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"INDEX_PATTERN_NAME"
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],
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"chunking_config" : {
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"mode" : "off"
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},
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"query": {
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"bool": {
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"filter": [
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{ "term": { "processor.event": "metric" } },
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{ "term": { "metricset.name": "transaction" } }
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]
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}
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},
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"aggregations" : {
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"buckets" : {
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"composite" : {
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"size" : 5000,
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"sources" : [
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{
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"date" : {
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"date_histogram" : {
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"field" : "@timestamp",
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"fixed_interval" : "90s"
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}
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}
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},
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{
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"transaction.type" : {
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"terms" : {
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"field" : "transaction.type"
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}
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}
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},
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{
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"service.name" : {
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"terms" : {
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"field" : "service.name"
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}
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}
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}
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]
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},
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"aggs" : {
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"@timestamp" : {
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"max" : {
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"field" : "@timestamp"
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}
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},
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"transactions_per_min" : {
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"rate" : {
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"unit" : "minute"
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}
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},
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"transaction_duration" : {
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"avg" : {
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"field" : "transaction.duration.histogram"
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}
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},
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"error_count" : {
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"filter" : {
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"term" : {
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"event.outcome" : "failure"
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}
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},
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"aggs" : {
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"actual_error_count" : {
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"value_count" : {
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"field" : "event.outcome"
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}
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}
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}
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},
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"success_count" : {
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"filter" : {
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"term" : {
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"event.outcome" : "success"
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}
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}
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},
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"transaction_failure_percentage" : {
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"bucket_script" : {
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"buckets_path" : {
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"failure_count" : "error_count>_count",
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"success_count" : "success_count>_count"
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},
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"script" : "if ((params.failure_count + params.success_count)==0){return 0;}else{return params.failure_count/(params.failure_count + params.success_count);}"
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}
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}
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}
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}
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}
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}
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@ -0,0 +1,14 @@
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{
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"job_id": "JOB_ID",
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"indices": [
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"INDEX_PATTERN_NAME"
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],
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"query": {
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"bool": {
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"filter": [
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{ "term": { "processor.event": "transaction" } },
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{ "exists": { "field": "transaction.duration.us" } }
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]
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}
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}
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}
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@ -0,0 +1,35 @@
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{
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"job_type": "anomaly_detector",
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"groups": [
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"apm"
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],
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"description": "Detect transaction duration anomalies across transaction types for your APM services.",
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"analysis_config": {
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"bucket_span": "15m",
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"detectors": [
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{
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"detector_description": "high duration by transaction type for an APM service",
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"function": "high_mean",
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"field_name": "transaction.duration.us",
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"by_field_name": "transaction.type",
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"partition_field_name": "service.name"
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}
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],
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"influencers": [
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"transaction.type",
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"service.name"
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]
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},
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"analysis_limits": {
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"model_memory_limit": "32mb"
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},
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"data_description": {
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"time_field": "@timestamp"
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},
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"model_plot_config": {
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"enabled": true
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},
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"custom_settings": {
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"created_by": "ml-module-apm-transaction"
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}
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}
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@ -44,7 +44,7 @@ export default ({ getService }: FtrProviderContext) => {
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user: USER.ML_POWERUSER,
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expected: {
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responseCode: 200,
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moduleIds: ['apm_jsbase', 'apm_nodejs'],
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moduleIds: ['apm_jsbase', 'apm_transaction', 'apm_nodejs'],
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},
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},
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{
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@ -187,11 +187,9 @@ export default ({ getService }: FtrProviderContext) => {
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dashboards: [] as string[],
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},
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},
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// Set startDatafeed and estimateModelMemory to false for the APM transaction test
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// until there is a new data set available with metric data.
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{
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testTitleSuffix:
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'for apm_transaction with prefix, startDatafeed false and estimateModelMemory false',
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'for apm_transaction with prefix, startDatafeed true and estimateModelMemory true',
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sourceDataArchive: 'x-pack/test/functional/es_archives/ml/module_apm',
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indexPattern: { name: 'ft_module_apm', timeField: '@timestamp' },
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module: 'apm_transaction',
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@ -199,14 +197,14 @@ export default ({ getService }: FtrProviderContext) => {
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requestBody: {
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prefix: 'pf5_',
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indexPatternName: 'ft_module_apm',
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startDatafeed: false,
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estimateModelMemory: false,
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startDatafeed: true,
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end: Date.now(),
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},
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expected: {
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responseCode: 200,
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jobs: [
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{
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jobId: 'pf5_apm_metrics',
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jobId: 'pf5_high_mean_transaction_duration',
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jobState: JOB_STATE.CLOSED,
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datafeedState: DATAFEED_STATE.STOPPED,
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},
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