[ML] Add a new memory usage by job and by model view (#149419)

Adds a new Memory usage page to the ML app.
This contains the page which was originally called Nodes, under the
Model Management section, and introduces a new tree map chart to display
memory usage of jobs and trained models.


![image](https://user-images.githubusercontent.com/22172091/217040806-bf1b2d51-32ce-4801-8d8f-e27c3d7a9f62.png)


If kibana is running in a serverless environment, the Memory usage page
will only show the overall memory usage chart. There will be no
reference made to "nodes".

**Refactoring**
Organises related server side code under a `model_management` section.
Moves routes to a new `model_management` file.
Adds a new `isServerless` function to the client side to spoof
information we should son get from kibana to tell whether we are running
in a serverless environment.

---------

Co-authored-by: István Zoltán Szabó <istvan.szabo@elastic.co>

x-pack/plugins/ml/common/constants/locator.ts

@@ -15,7 +15,7 @@ export const ML_PAGES = {
   DATA_FRAME_ANALYTICS_SOURCE_SELECTION: 'data_frame_analytics/source_selection',
   DATA_FRAME_ANALYTICS_CREATE_JOB: 'data_frame_analytics/new_job',
   TRAINED_MODELS_MANAGE: 'trained_models',
-  TRAINED_MODELS_NODES: 'trained_models/nodes',
+  MEMORY_USAGE: 'memory_usage',
   DATA_FRAME_ANALYTICS_EXPLORATION: 'data_frame_analytics/exploration',
   DATA_FRAME_ANALYTICS_MAP: 'data_frame_analytics/map',
   /**

x-pack/plugins/ml/common/types/locator.ts

@@ -203,7 +203,7 @@ export interface TrainedModelsQueryState {
   modelId?: string;
 }
 
-export interface TrainedModelsNodesQueryState {
+export interface MemoryUsageNodesQueryState {
   nodeId?: string;
 }
 
@@ -276,7 +276,7 @@ export type MlLocatorState =
   | MlGenericUrlState
   | NotificationsUrlState
   | TrainedModelsUrlState
-  | TrainedModelsNodesUrlState;
+  | MemoryUsageUrlState;
 
 export type MlLocatorParams = MlLocatorState & SerializableRecord;
 
@@ -287,9 +287,9 @@ export type TrainedModelsUrlState = MLPageState<
   TrainedModelsQueryState | undefined
 >;
 
-export type TrainedModelsNodesUrlState = MLPageState<
-  typeof ML_PAGES.TRAINED_MODELS_NODES,
-  TrainedModelsNodesQueryState | undefined
+export type MemoryUsageUrlState = MLPageState<
+  typeof ML_PAGES.MEMORY_USAGE,
+  MemoryUsageNodesQueryState | undefined
 >;
 
 export interface NotificationsQueryState {

x-pack/plugins/ml/common/types/trained_models.ts

@@ -9,6 +9,7 @@ import type { DataFrameAnalyticsConfig } from './data_frame_analytics';
 import type { FeatureImportanceBaseline, TotalFeatureImportance } from './feature_importance';
 import type { XOR } from './common';
 import type { DeploymentState, TrainedModelType } from '../constants/trained_models';
+import type { MlSavedObjectType } from './saved_objects';
 
 export interface IngestStats {
   count: number;
@@ -236,3 +237,47 @@ export interface NodesOverviewResponse {
   _nodes: { total: number; failed: number; successful: number };
   nodes: NodeDeploymentStatsResponse[];
 }
+
+export interface MemoryUsageInfo {
+  id: string;
+  type: MlSavedObjectType;
+  size: number;
+  nodeNames: string[];
+}
+
+export interface MemoryStatsResponse {
+  _nodes: { total: number; failed: number; successful: number };
+  cluster_name: string;
+  nodes: Record<
+    string,
+    {
+      jvm: {
+        heap_max_in_bytes: number;
+        java_inference_in_bytes: number;
+        java_inference_max_in_bytes: number;
+      };
+      mem: {
+        adjusted_total_in_bytes: number;
+        total_in_bytes: number;
+        ml: {
+          data_frame_analytics_in_bytes: number;
+          native_code_overhead_in_bytes: number;
+          max_in_bytes: number;
+          anomaly_detectors_in_bytes: number;
+          native_inference_in_bytes: number;
+        };
+      };
+      transport_address: string;
+      roles: string[];
+      name: string;
+      attributes: Record<`${'ml.'}${string}`, string>;
+      ephemeral_id: string;
+    }
+  >;
+}
+
+// @ts-expect-error TrainedModelDeploymentStatsResponse missing properties from MlTrainedModelDeploymentStats
+export interface TrainedModelStatsResponse extends estypes.MlTrainedModelStats {
+  deployment_stats?: Omit<TrainedModelDeploymentStatsResponse, 'model_id'>;
+  model_size_stats?: TrainedModelModelSizeStats;
+}

x-pack/plugins/ml/public/application/app.tsx

@@ -45,6 +45,12 @@ interface AppProps {
 
 const localStorage = new Storage(window.localStorage);
 
+// temporary function to hardcode the serverless state
+// this will be replaced by the true serverless information from kibana
+export function isServerless() {
+  return false;
+}
+
 /**
  * Provides global services available across the entire ML app.
  */
@@ -54,6 +60,7 @@ export function getMlGlobalServices(httpStart: HttpStart, usageCollection?: Usag
     httpService,
     mlApiServices: mlApiServicesProvider(httpService),
     mlUsageCollection: mlUsageCollectionProvider(usageCollection),
+    isServerless,
   };
 }
 

x-pack/plugins/ml/public/application/components/ml_page/ml_page.tsx

@@ -169,7 +169,7 @@ const CommonPageWrapper: FC<CommonPageWrapperProps> = React.memo(({ pageDeps, ro
           {routeList.map((route) => {
             return (
               <Route
-                key={route.id}
+                key={route.path}
                 path={route.path}
                 exact
                 render={(props) => {

x-pack/plugins/ml/public/application/components/ml_page/side_nav.tsx

@@ -96,6 +96,15 @@ export function useSideNavItems(activeRoute: MlRoute | undefined) {
             disabled: disableLinks,
             testSubj: 'mlMainTab notifications',
           },
+          {
+            id: 'memory_usage',
+            pathId: ML_PAGES.MEMORY_USAGE,
+            name: i18n.translate('xpack.ml.navMenu.memoryUsageText', {
+              defaultMessage: 'Memory Usage',
+            }),
+            disabled: disableLinks || !canViewMlNodes,
+            testSubj: 'mlMainTab nodesOverview',
+          },
         ],
       },
       {
@@ -196,15 +205,6 @@ export function useSideNavItems(activeRoute: MlRoute | undefined) {
             disabled: disableLinks,
             testSubj: 'mlMainTab trainedModels',
           },
-          {
-            id: 'nodes_overview',
-            pathId: ML_PAGES.TRAINED_MODELS_NODES,
-            name: i18n.translate('xpack.ml.navMenu.nodesOverviewText', {
-              defaultMessage: 'Nodes',
-            }),
-            disabled: disableLinks || !canViewMlNodes,
-            testSubj: 'mlMainTab nodesOverview',
-          },
         ],
       },
       {

x-pack/plugins/ml/public/application/contexts/kibana/use_is_serverless.ts

@@ -0,0 +1,14 @@
+/*
+ * 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 { useMemo } from 'react';
+import { useMlKibana } from './kibana_context';
+
+export const useIsServerless = () => {
+  const isServerless = useMlKibana().services.mlServices.isServerless;
+  return useMemo(() => isServerless(), [isServerless]);
+};

x-pack/plugins/ml/public/application/data_frame_analytics/pages/components/analytics_selector/analytics_id_selector.tsx

@@ -27,7 +27,7 @@ import { BUILT_IN_MODEL_TAG } from '../../../../../../common/constants/data_fram
 import { useTrainedModelsApiService } from '../../../../services/ml_api_service/trained_models';
 import { GetDataFrameAnalyticsResponse } from '../../../../services/ml_api_service/data_frame_analytics';
 import { useToastNotificationService } from '../../../../services/toast_notification_service';
-import { ModelsTableToConfigMapping } from '../../../../trained_models/models_management';
+import { ModelsTableToConfigMapping } from '../../../../model_management';
 import { DataFrameAnalyticsConfig } from '../../../common';
 import { useMlApiContext } from '../../../../contexts/kibana';
 import { TrainedModelConfigResponse } from '../../../../../../common/types/trained_models';

x-pack/plugins/ml/public/application/management/jobs_list/components/jobs_list_page/space_management/columns.tsx

@@ -7,7 +7,7 @@
 import React from 'react';
 import { i18n } from '@kbn/i18n';
 import { EuiBasicTableColumn } from '@elastic/eui';
-import { TrainedModelLink } from '../../../../../trained_models/models_management';
+import { TrainedModelLink } from '../../../../../model_management';
 import type { MlSavedObjectType } from '../../../../../../../common/types/saved_objects';
 import type {
   AnalyticsManagementItems,

x-pack/plugins/ml/public/application/memory_usage/index.ts

@@ -0,0 +1,8 @@
+/*
+ * 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.
+ */
+
+export { MemoryUsagePage } from './memory_usage_page';

x-pack/plugins/ml/public/application/memory_usage/memory_item_colors.ts

@@ -0,0 +1,34 @@
+/*
+ * 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 {
+  euiPaletteComplimentary,
+  euiPaletteForTemperature,
+  euiPaletteGray,
+  euiPalettePositive,
+  euiPaletteWarm,
+} from '@elastic/eui';
+import { MlSavedObjectType } from '../../../common/types/saved_objects';
+
+type MemoryItem = MlSavedObjectType | 'jvm-heap-size' | 'estimated-available-memory';
+
+export function getMemoryItemColor(typeIn: MemoryItem) {
+  switch (typeIn) {
+    case 'anomaly-detector':
+      return euiPaletteWarm(5)[1];
+    case 'data-frame-analytics':
+      return euiPalettePositive(5)[2];
+    case 'trained-model':
+      return euiPaletteForTemperature(5)[1];
+    case 'estimated-available-memory':
+      return euiPaletteGray(5)[0];
+    case 'jvm-heap-size':
+      return euiPaletteComplimentary(5)[4];
+    default:
+      return euiPaletteGray(5)[4];
+  }
+}

x-pack/plugins/ml/public/application/memory_usage/memory_tree_map/index.ts

@@ -0,0 +1,9 @@
+/*
+ * 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.
+ */
+
+export { JobMemoryTreeMap } from './tree_map';
+export { MemoryPage } from './memory_page';

x-pack/plugins/ml/public/application/memory_usage/memory_tree_map/memory_page.tsx

@@ -0,0 +1,26 @@
+/*
+ * 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 { EuiCallOut, EuiSpacer } from '@elastic/eui';
+import React, { FC } from 'react';
+import { FormattedMessage } from '@kbn/i18n-react';
+import { JobMemoryTreeMap } from './tree_map';
+
+export const MemoryPage: FC = () => {
+  return (
+    <>
+      <EuiSpacer size="s" />
+      <EuiCallOut color="primary">
+        <FormattedMessage
+          id="xpack.ml.memoryUsage.treeMap.infoCallout"
+          defaultMessage="Memory usage for active machine learning jobs and trained models."
+        />
+      </EuiCallOut>
+      <JobMemoryTreeMap />
+    </>
+  );
+};

x-pack/plugins/ml/public/application/memory_usage/memory_tree_map/tree_map.tsx

@@ -0,0 +1,201 @@
+/*
+ * 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 React, { FC, useEffect, useState, useCallback, useMemo } from 'react';
+import {
+  Chart,
+  Settings,
+  Partition,
+  PartitionLayout,
+  ShapeTreeNode,
+  LIGHT_THEME,
+  DARK_THEME,
+} from '@elastic/charts';
+import { EUI_CHARTS_THEME_DARK, EUI_CHARTS_THEME_LIGHT } from '@elastic/eui/dist/eui_charts_theme';
+import { FIELD_FORMAT_IDS } from '@kbn/field-formats-plugin/common';
+import { EuiComboBox, EuiComboBoxOptionOption, EuiEmptyPrompt, EuiSpacer } from '@elastic/eui';
+import { i18n } from '@kbn/i18n';
+import { FormattedMessage } from '@kbn/i18n-react';
+import { MemoryUsageInfo } from '../../../../common/types/trained_models';
+import { JobType, MlSavedObjectType } from '../../../../common/types/saved_objects';
+import { useTrainedModelsApiService } from '../../services/ml_api_service/trained_models';
+import { LoadingWrapper } from '../../jobs/new_job/pages/components/charts/loading_wrapper';
+import { useFieldFormatter, useUiSettings } from '../../contexts/kibana';
+
+import { useRefresh } from '../../routing/use_refresh';
+import { getMemoryItemColor } from '../memory_item_colors';
+import { useToastNotificationService } from '../../services/toast_notification_service';
+
+interface Props {
+  node?: string;
+  type?: MlSavedObjectType;
+  height?: string;
+}
+
+const DEFAULT_CHART_HEIGHT = '400px';
+
+const TYPE_LABELS: Record<string, MlSavedObjectType> = {
+  [i18n.translate('xpack.ml.memoryUsage.treeMap.adLabel', {
+    defaultMessage: 'Anomaly detection jobs',
+  })]: 'anomaly-detector',
+  [i18n.translate('xpack.ml.memoryUsage.treeMap.dfaLabel', {
+    defaultMessage: 'Data frame analytics jobs',
+  })]: 'data-frame-analytics',
+  [i18n.translate('xpack.ml.memoryUsage.treeMap.modelsLabel', {
+    defaultMessage: 'Trained models',
+  })]: 'trained-model',
+} as const;
+
+const TYPE_LABELS_INVERTED = Object.entries(TYPE_LABELS).reduce<Record<MlSavedObjectType, string>>(
+  (acc, [label, type]) => {
+    acc[type] = label;
+    return acc;
+  },
+  {} as Record<MlSavedObjectType, string>
+);
+
+const TYPE_OPTIONS: EuiComboBoxOptionOption[] = Object.entries(TYPE_LABELS).map(
+  ([label, type]) => ({
+    label,
+    color: getMemoryItemColor(type),
+  })
+);
+
+export const JobMemoryTreeMap: FC<Props> = ({ node, type, height }) => {
+  const isDarkTheme = useUiSettings().get('theme:darkMode');
+  const { theme, baseTheme } = useMemo(
+    () =>
+      isDarkTheme
+        ? { theme: EUI_CHARTS_THEME_DARK, baseTheme: DARK_THEME }
+        : { theme: EUI_CHARTS_THEME_LIGHT, baseTheme: LIGHT_THEME },
+    [isDarkTheme]
+  );
+
+  const bytesFormatter = useFieldFormatter(FIELD_FORMAT_IDS.BYTES);
+  const { displayErrorToast } = useToastNotificationService();
+  const refresh = useRefresh();
+  const chartHeight = height ?? DEFAULT_CHART_HEIGHT;
+
+  const trainedModelsApiService = useTrainedModelsApiService();
+  const [allData, setAllData] = useState<MemoryUsageInfo[]>([]);
+  const [data, setData] = useState<MemoryUsageInfo[]>([]);
+  const [loading, setLoading] = useState(false);
+  const [selectedOptions, setSelectedOptions] = useState(TYPE_OPTIONS);
+
+  const filterData = useCallback(
+    (dataIn: MemoryUsageInfo[]) => {
+      const types = selectedOptions.map((o) => TYPE_LABELS[o.label]);
+      return dataIn.filter((d) => types.includes(d.type));
+    },
+    [selectedOptions]
+  );
+
+  const loadJobMemorySize = useCallback(async () => {
+    setLoading(true);
+    try {
+      const resp = await trainedModelsApiService.memoryUsage(type, node);
+      setAllData(resp);
+    } catch (error) {
+      displayErrorToast(
+        error,
+        i18n.translate('xpack.ml.memoryUsage.treeMap.fetchFailedErrorMessage', {
+          defaultMessage: 'Models memory usage fetch failed',
+        })
+      );
+    }
+    setLoading(false);
+  }, [trainedModelsApiService, type, node, displayErrorToast]);
+
+  useEffect(
+    function redrawOnFilterChange() {
+      setData(filterData(allData));
+    },
+    [selectedOptions, allData, filterData]
+  );
+
+  useEffect(
+    function updateOnTimerRefresh() {
+      loadJobMemorySize();
+    },
+    [loadJobMemorySize, refresh]
+  );
+
+  return (
+    <div
+      style={{ height: chartHeight }}
+      data-test-subj={`mlJobTreeMap ${data.length ? 'withData' : 'empty'}`}
+    >
+      <EuiSpacer size="s" />
+      <LoadingWrapper height={chartHeight} hasData={data.length > 0} loading={loading}>
+        <EuiComboBox
+          fullWidth
+          options={TYPE_OPTIONS}
+          selectedOptions={selectedOptions}
+          onChange={setSelectedOptions}
+          isClearable={false}
+        />
+
+        <EuiSpacer size="s" />
+
+        {data.length ? (
+          <Chart>
+            <Settings baseTheme={baseTheme} theme={theme.theme} />
+            <Partition<MemoryUsageInfo>
+              id="memoryUsageTreeMap"
+              data={data}
+              layout={PartitionLayout.treemap}
+              valueAccessor={(d) => d.size}
+              valueFormatter={(size: number) => bytesFormatter(size)}
+              layers={[
+                {
+                  groupByRollup: (d: MemoryUsageInfo) => d.type,
+                  nodeLabel: (d) => TYPE_LABELS_INVERTED[d as MlSavedObjectType],
+                  fillLabel: {
+                    valueFormatter: (size: number) => bytesFormatter(size),
+                  },
+                  shape: {
+                    fillColor: (d: ShapeTreeNode) => getMemoryItemColor(d.dataName as JobType),
+                  },
+                },
+                {
+                  groupByRollup: (d: MemoryUsageInfo) => d.id,
+                  nodeLabel: (d) => `${d}`,
+                  fillLabel: {
+                    valueFont: {
+                      fontWeight: 100,
+                    },
+                  },
+                  shape: {
+                    fillColor: (d: ShapeTreeNode) => {
+                      // color the shape the same as its parent.
+                      const parentId = d.parent.path[d.parent.path.length - 1].value as JobType;
+                      return getMemoryItemColor(parentId);
+                    },
+                  },
+                },
+              ]}
+            />
+          </Chart>
+        ) : (
+          <EuiEmptyPrompt
+            titleSize="xs"
+            iconType="alert"
+            data-test-subj="mlEmptyMemoryUsageTreeMap"
+            title={
+              <h2>
+                <FormattedMessage
+                  id="xpack.ml.memoryUsage.treeMap.emptyPrompt"
+                  defaultMessage="No open jobs or trained models match the current selection. "
+                />
+              </h2>
+            }
+          />
+        )}
+      </LoadingWrapper>
+    </div>
+  );
+};

x-pack/plugins/ml/public/application/memory_usage/memory_usage_page.tsx

@@ -0,0 +1,72 @@
+/*
+ * 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 React, { FC, useCallback, useState } from 'react';
+import { mlTimefilterRefresh$, useTimefilter } from '@kbn/ml-date-picker';
+import { EuiFlexGroup, EuiFlexItem, EuiTabs, EuiTab } from '@elastic/eui';
+import { FormattedMessage } from '@kbn/i18n-react';
+import { NodesList } from './nodes_overview';
+import { MlPageHeader } from '../components/page_header';
+import { MemoryPage, JobMemoryTreeMap } from './memory_tree_map';
+import { useIsServerless } from '../contexts/kibana/use_is_serverless';
+import { SavedObjectsWarning } from '../components/saved_objects_warning';
+
+enum TAB {
+  NODES,
+  MEMORY_USAGE,
+}
+
+export const MemoryUsagePage: FC = () => {
+  const serverless = useIsServerless();
+  const [selectedTab, setSelectedTab] = useState<TAB>(TAB.NODES);
+  useTimefilter({ timeRangeSelector: false, autoRefreshSelector: true });
+
+  const refresh = useCallback(() => {
+    mlTimefilterRefresh$.next({
+      lastRefresh: Date.now(),
+    });
+  }, []);
+
+  return (
+    <>
+      <MlPageHeader>
+        <EuiFlexGroup responsive={false} wrap={false} alignItems={'center'} gutterSize={'m'}>
+          <EuiFlexItem grow={false}>
+            <FormattedMessage
+              id="xpack.ml.memoryUsage.memoryUsageHeader"
+              defaultMessage="Memory Usage"
+            />
+          </EuiFlexItem>
+        </EuiFlexGroup>
+      </MlPageHeader>
+
+      <SavedObjectsWarning onCloseFlyout={refresh} />
+
+      {serverless ? (
+        <JobMemoryTreeMap />
+      ) : (
+        <>
+          <EuiTabs>
+            <EuiTab
+              isSelected={selectedTab === TAB.NODES}
+              onClick={() => setSelectedTab(TAB.NODES)}
+            >
+              <FormattedMessage id="xpack.ml.memoryUsage.nodesTab" defaultMessage="Nodes" />
+            </EuiTab>
+            <EuiTab
+              isSelected={selectedTab === TAB.MEMORY_USAGE}
+              onClick={() => setSelectedTab(TAB.MEMORY_USAGE)}
+            >
+              <FormattedMessage id="xpack.ml.memoryUsage.memoryTab" defaultMessage="Memory usage" />
+            </EuiTab>
+          </EuiTabs>
+          {selectedTab === TAB.NODES ? <NodesList /> : <MemoryPage />}
+        </>
+      )}
+    </>
+  );
+};

x-pack/plugins/ml/public/application/memory_usage/nodes_overview/expanded_row.tsx

@@ -0,0 +1,151 @@
+/*
+ * 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 React, { FC, useState } from 'react';
+import {
+  EuiDescriptionList,
+  EuiFlexGrid,
+  EuiFlexItem,
+  EuiPanel,
+  EuiSpacer,
+  EuiTab,
+  EuiTabs,
+  EuiTitle,
+} from '@elastic/eui';
+import { FormattedMessage } from '@kbn/i18n-react';
+import { cloneDeep } from 'lodash';
+import { FIELD_FORMAT_IDS } from '@kbn/field-formats-plugin/common';
+import { css } from '@emotion/react';
+import { NodeItem } from './nodes_list';
+import { useListItemsFormatter } from '../../model_management/expanded_row';
+import { AllocatedModels } from './allocated_models';
+import { useFieldFormatter } from '../../contexts/kibana/use_field_formatter';
+import { JobMemoryTreeMap } from '../memory_tree_map';
+
+interface ExpandedRowProps {
+  item: NodeItem;
+}
+
+enum TAB {
+  DETAILS,
+  MEMORY_USAGE,
+}
+
+export const ExpandedRow: FC<ExpandedRowProps> = ({ item }) => {
+  const bytesFormatter = useFieldFormatter(FIELD_FORMAT_IDS.BYTES);
+  const [selectedTab, setSelectedTab] = useState<TAB>(TAB.DETAILS);
+
+  const formatToListItems = useListItemsFormatter();
+
+  const {
+    allocated_models: allocatedModels,
+    attributes,
+    memory_overview: memoryOverview,
+    id,
+    ...details
+  } = cloneDeep(item);
+
+  // Process node attributes
+  attributes['ml.machine_memory'] = bytesFormatter(attributes['ml.machine_memory']);
+  attributes['ml.max_jvm_size'] = bytesFormatter(attributes['ml.max_jvm_size']);
+
+  return (
+    <div
+      css={css`
+        width: 100%;
+      `}
+    >
+      <EuiTabs>
+        <EuiTab
+          isSelected={selectedTab === TAB.DETAILS}
+          onClick={() => setSelectedTab(TAB.DETAILS)}
+        >
+          <FormattedMessage
+            id="xpack.ml.trainedModels.nodesList.expandedRow.detailsTabTitle"
+            defaultMessage="Details"
+          />
+        </EuiTab>
+        <EuiTab
+          isSelected={selectedTab === TAB.MEMORY_USAGE}
+          onClick={() => setSelectedTab(TAB.MEMORY_USAGE)}
+        >
+          <FormattedMessage
+            id="xpack.ml.trainedModels.nodesList.expandedRow.memoryTabTitle"
+            defaultMessage="Memory usage"
+          />
+        </EuiTab>
+      </EuiTabs>
+
+      {selectedTab === TAB.DETAILS ? (
+        <>
+          <EuiSpacer size="s" />
+          <EuiFlexGrid columns={2} gutterSize={'s'}>
+            <EuiFlexItem>
+              <EuiPanel hasShadow={false}>
+                <EuiTitle size={'xs'}>
+                  <h5>
+                    <FormattedMessage
+                      id="xpack.ml.trainedModels.nodesList.expandedRow.detailsTitle"
+                      defaultMessage="Details"
+                    />
+                  </h5>
+                </EuiTitle>
+                <EuiSpacer size={'m'} />
+                <EuiDescriptionList
+                  compressed={true}
+                  type="column"
+                  listItems={formatToListItems(details)}
+                />
+              </EuiPanel>
+            </EuiFlexItem>
+
+            <EuiFlexItem>
+              <EuiPanel hasShadow={false}>
+                <EuiTitle size={'xs'}>
+                  <h5>
+                    <FormattedMessage
+                      id="xpack.ml.trainedModels.nodesList.expandedRow.attributesTitle"
+                      defaultMessage="Attributes"
+                    />
+                  </h5>
+                </EuiTitle>
+                <EuiSpacer size={'m'} />
+                <EuiDescriptionList
+                  compressed={true}
+                  type="column"
+                  listItems={formatToListItems(attributes)}
+                />
+              </EuiPanel>
+            </EuiFlexItem>
+          </EuiFlexGrid>
+          {allocatedModels.length > 0 ? (
+            <>
+              <EuiSpacer size={'s'} />
+              <EuiPanel hasShadow={false}>
+                <EuiTitle size={'xs'}>
+                  <h5>
+                    <FormattedMessage
+                      id="xpack.ml.trainedModels.nodesList.expandedRow.allocatedModelsTitle"
+                      defaultMessage="Allocated trained models"
+                    />
+                  </h5>
+                </EuiTitle>
+                <EuiSpacer size={'m'} />
+
+                <AllocatedModels models={allocatedModels} />
+              </EuiPanel>
+            </>
+          ) : null}
+        </>
+      ) : (
+        <>
+          <JobMemoryTreeMap node={item.name} />
+        </>
+      )}
+    </div>
+  );
+};

x-pack/plugins/ml/public/application/memory_usage/nodes_overview/memory_preview_chart.tsx

@@ -18,11 +18,11 @@ import {
   LineAnnotation,
   AnnotationDomainType,
 } from '@elastic/charts';
-import { EuiIcon, euiPaletteGray } from '@elastic/eui';
+import { EuiIcon } from '@elastic/eui';
 import { FIELD_FORMAT_IDS } from '@kbn/field-formats-plugin/common';
 import { NodeDeploymentStatsResponse } from '../../../../common/types/trained_models';
 import { useFieldFormatter } from '../../contexts/kibana/use_field_formatter';
-import { useCurrentEuiTheme } from '../../components/color_range_legend';
+import { getMemoryItemColor } from '../memory_item_colors';
 
 interface MemoryPreviewChartProps {
   memoryOverview: NodeDeploymentStatsResponse['memory_overview'];
@@ -31,42 +31,39 @@ interface MemoryPreviewChartProps {
 export const MemoryPreviewChart: FC<MemoryPreviewChartProps> = ({ memoryOverview }) => {
   const bytesFormatter = useFieldFormatter(FIELD_FORMAT_IDS.BYTES);
 
-  const { euiTheme } = useCurrentEuiTheme();
-
   const groups = useMemo(
     () => ({
       jvm: {
         name: i18n.translate('xpack.ml.trainedModels.nodesList.jvmHeapSIze', {
           defaultMessage: 'JVM heap size',
         }),
-        colour: euiTheme.euiColorVis1,
+        color: getMemoryItemColor('jvm-heap-size'),
       },
       trained_models: {
         name: i18n.translate('xpack.ml.trainedModels.nodesList.modelsMemoryUsage', {
           defaultMessage: 'Trained models',
         }),
-        colour: euiTheme.euiColorVis2,
+        color: getMemoryItemColor('trained-model'),
       },
       anomaly_detection: {
         name: i18n.translate('xpack.ml.trainedModels.nodesList.adMemoryUsage', {
           defaultMessage: 'Anomaly detection jobs',
         }),
-        colour: euiTheme.euiColorVis6,
+        color: getMemoryItemColor('anomaly-detector'),
       },
       dfa_training: {
         name: i18n.translate('xpack.ml.trainedModels.nodesList.dfaMemoryUsage', {
           defaultMessage: 'Data frame analytics jobs',
         }),
-        colour: euiTheme.euiColorVis4,
+        color: getMemoryItemColor('data-frame-analytics'),
       },
       available: {
         name: i18n.translate('xpack.ml.trainedModels.nodesList.availableMemory', {
           defaultMessage: 'Estimated available memory',
         }),
-        colour: euiPaletteGray(5)[0],
+        color: getMemoryItemColor('estimated-available-memory'),
       },
     }),
-    // eslint-disable-next-line react-hooks/exhaustive-deps
     []
   );
 
@@ -106,7 +103,7 @@ export const MemoryPreviewChart: FC<MemoryPreviewChartProps> = ({ memoryOverview
   const barSeriesColorAccessor: SeriesColorAccessor = ({ specId, yAccessor, splitAccessors }) => {
     const group = splitAccessors.get('g');
 
-    return Object.values(groups).find((v) => v.name === group)!.colour;
+    return Object.values(groups).find((v) => v.name === group)!.color;
   };
 
   return (

x-pack/plugins/ml/public/application/memory_usage/nodes_overview/nodes_list.tsx

@@ -33,7 +33,7 @@ import { useRefresh } from '../../routing/use_refresh';
 export type NodeItem = NodeDeploymentStatsResponse;
 
 interface PageUrlState {
-  pageKey: typeof ML_PAGES.TRAINED_MODELS_NODES;
+  pageKey: typeof ML_PAGES.MEMORY_USAGE;
   pageUrlState: ListingPageUrlState;
 }
 
@@ -61,7 +61,7 @@ export const NodesList: FC<NodesListProps> = ({ compactView = false }) => {
     {}
   );
   const [pageState, updatePageState] = usePageUrlState<PageUrlState>(
-    ML_PAGES.TRAINED_MODELS_NODES,
+    ML_PAGES.MEMORY_USAGE,
     getDefaultNodesListState()
   );
 

x-pack/plugins/ml/public/application/model_management/delete_models_modal.tsx

@@ -16,9 +16,9 @@ import {
   EuiButton,
 } from '@elastic/eui';
 import { FormattedMessage } from '@kbn/i18n-react';
-import { useTrainedModelsApiService } from '../../services/ml_api_service/trained_models';
-import { useToastNotificationService } from '../../services/toast_notification_service';
-import { DeleteSpaceAwareItemCheckModal } from '../../components/delete_space_aware_item_check_modal';
+import { useTrainedModelsApiService } from '../services/ml_api_service/trained_models';
+import { useToastNotificationService } from '../services/toast_notification_service';
+import { DeleteSpaceAwareItemCheckModal } from '../components/delete_space_aware_item_check_modal';
 
 interface DeleteModelsModalProps {
   modelIds: string[];

x-pack/plugins/ml/public/application/model_management/deployment_setup.tsx

@@ -30,8 +30,8 @@ import type { Observable } from 'rxjs';
 import type { CoreTheme, OverlayStart } from '@kbn/core/public';
 import { css } from '@emotion/react';
 import { numberValidator } from '@kbn/ml-agg-utils';
-import { isCloudTrial } from '../../services/ml_server_info';
-import { composeValidators, requiredValidator } from '../../../../common/util/validators';
+import { isCloudTrial } from '../services/ml_server_info';
+import { composeValidators, requiredValidator } from '../../../common/util/validators';
 
 interface DeploymentSetupProps {
   config: ThreadingParams;

x-pack/plugins/ml/public/application/model_management/expanded_row.tsx

@@ -20,6 +20,7 @@ import {
   EuiTabbedContent,
   EuiTabbedContentTab,
   EuiTitle,
+  useEuiPaddingSize,
 } from '@elastic/eui';
 import { FormattedMessage } from '@kbn/i18n-react';
 import { FIELD_FORMAT_IDS } from '@kbn/field-formats-plugin/common';
@@ -27,30 +28,38 @@ import { isPopulatedObject } from '@kbn/ml-is-populated-object';
 import { isDefined } from '@kbn/ml-is-defined';
 import type { ModelItemFull } from './models_list';
 import { ModelPipelines } from './pipelines';
-import { AllocatedModels } from '../nodes_overview/allocated_models';
-import type { AllocatedModel } from '../../../../common/types/trained_models';
-import { useFieldFormatter } from '../../contexts/kibana/use_field_formatter';
+import { AllocatedModels } from '../memory_usage/nodes_overview/allocated_models';
+import type { AllocatedModel } from '../../../common/types/trained_models';
+import { useFieldFormatter } from '../contexts/kibana/use_field_formatter';
 
 interface ExpandedRowProps {
   item: ModelItemFull;
 }
 
-const badgeFormatter = (items: string[]) => {
-  if (items.length === 0) return;
-  return (
-    <div>
-      {items.map((item) => (
-        <EuiBadge key={item} color="hollow">
-          {item}
-        </EuiBadge>
-      ))}
-    </div>
-  );
+const useBadgeFormatter = () => {
+  const xs = useEuiPaddingSize('xs');
+
+  function badgeFormatter(items: string[]) {
+    if (items.length === 0) return;
+    return (
+      <div>
+        {items.map((item) => (
+          <span css={{ marginRight: xs! }} key={item}>
+            <EuiBadge color="hollow" css={{ marginRight: xs! }}>
+              {item}
+            </EuiBadge>
+          </span>
+        ))}
+      </div>
+    );
+  }
+  return { badgeFormatter };
 };
 
 export function useListItemsFormatter() {
   const bytesFormatter = useFieldFormatter(FIELD_FORMAT_IDS.BYTES);
   const dateFormatter = useFieldFormatter(FIELD_FORMAT_IDS.DATE);
+  const { badgeFormatter } = useBadgeFormatter();
 
   const formatterDictionary: Record<string, (value: any) => JSX.Element | string | undefined> =
     useMemo(

x-pack/plugins/ml/public/application/model_management/model_actions.tsx

@@ -10,16 +10,16 @@ import { i18n } from '@kbn/i18n';
 import { isPopulatedObject } from '@kbn/ml-is-populated-object';
 import { EuiToolTip } from '@elastic/eui';
 import React, { useCallback, useMemo } from 'react';
-import { BUILT_IN_MODEL_TAG } from '../../../../common/constants/data_frame_analytics';
-import { useTrainedModelsApiService } from '../../services/ml_api_service/trained_models';
+import { BUILT_IN_MODEL_TAG } from '../../../common/constants/data_frame_analytics';
+import { useTrainedModelsApiService } from '../services/ml_api_service/trained_models';
 import { getUserConfirmationProvider } from './force_stop_dialog';
-import { useToastNotificationService } from '../../services/toast_notification_service';
+import { useToastNotificationService } from '../services/toast_notification_service';
 import { getUserInputThreadingParamsProvider } from './deployment_setup';
-import { useMlKibana, useMlLocator, useNavigateToPath } from '../../contexts/kibana';
-import { getAnalysisType } from '../../../../common/util/analytics_utils';
-import { DataFrameAnalysisConfigType } from '../../../../common/types/data_frame_analytics';
-import { ML_PAGES } from '../../../../common/constants/locator';
-import { DEPLOYMENT_STATE, TRAINED_MODEL_TYPE } from '../../../../common/constants/trained_models';
+import { useMlKibana, useMlLocator, useNavigateToPath } from '../contexts/kibana';
+import { getAnalysisType } from '../../../common/util/analytics_utils';
+import { DataFrameAnalysisConfigType } from '../../../common/types/data_frame_analytics';
+import { ML_PAGES } from '../../../common/constants/locator';
+import { DEPLOYMENT_STATE, TRAINED_MODEL_TYPE } from '../../../common/constants/trained_models';
 import { isTestable } from './test_models';
 import { ModelItem } from './models_list';
 

x-pack/plugins/ml/public/application/model_management/model_link.tsx

@@ -7,8 +7,8 @@
 
 import { EuiLink } from '@elastic/eui';
 import React, { FC } from 'react';
-import { useMlLink } from '../../contexts/kibana';
-import { ML_PAGES } from '../../../../common/constants/locator';
+import { useMlLink } from '../contexts/kibana';
+import { ML_PAGES } from '../../../common/constants/locator';
 
 export interface TrainedModelLinkProps {
   id: string;

x-pack/plugins/ml/public/application/model_management/models_list.tsx

@@ -29,25 +29,25 @@ import { usePageUrlState } from '@kbn/ml-url-state';
 import { useTimefilter } from '@kbn/ml-date-picker';
 import { useModelActions } from './model_actions';
 import { ModelsTableToConfigMapping } from '.';
-import { ModelsBarStats, StatsBar } from '../../components/stats_bar';
-import { useMlKibana } from '../../contexts/kibana';
-import { useTrainedModelsApiService } from '../../services/ml_api_service/trained_models';
+import { ModelsBarStats, StatsBar } from '../components/stats_bar';
+import { useMlKibana } from '../contexts/kibana';
+import { useTrainedModelsApiService } from '../services/ml_api_service/trained_models';
 import {
   ModelPipelines,
   TrainedModelConfigResponse,
   TrainedModelStat,
-} from '../../../../common/types/trained_models';
-import { BUILT_IN_MODEL_TAG } from '../../../../common/constants/data_frame_analytics';
+} from '../../../common/types/trained_models';
+import { BUILT_IN_MODEL_TAG } from '../../../common/constants/data_frame_analytics';
 import { DeleteModelsModal } from './delete_models_modal';
-import { ML_PAGES } from '../../../../common/constants/locator';
-import { ListingPageUrlState } from '../../../../common/types/common';
+import { ML_PAGES } from '../../../common/constants/locator';
+import { ListingPageUrlState } from '../../../common/types/common';
 import { ExpandedRow } from './expanded_row';
-import { useTableSettings } from '../../data_frame_analytics/pages/analytics_management/components/analytics_list/use_table_settings';
-import { useToastNotificationService } from '../../services/toast_notification_service';
-import { useFieldFormatter } from '../../contexts/kibana/use_field_formatter';
-import { useRefresh } from '../../routing/use_refresh';
-import { BUILT_IN_MODEL_TYPE } from '../../../../common/constants/trained_models';
-import { SavedObjectsWarning } from '../../components/saved_objects_warning';
+import { useTableSettings } from '../data_frame_analytics/pages/analytics_management/components/analytics_list/use_table_settings';
+import { useToastNotificationService } from '../services/toast_notification_service';
+import { useFieldFormatter } from '../contexts/kibana/use_field_formatter';
+import { useRefresh } from '../routing/use_refresh';
+import { BUILT_IN_MODEL_TYPE } from '../../../common/constants/trained_models';
+import { SavedObjectsWarning } from '../components/saved_objects_warning';
 import { TestTrainedModelFlyout } from './test_models';
 
 type Stats = Omit<TrainedModelStat, 'model_id'>;

x-pack/plugins/ml/public/application/model_management/pipelines/expanded_row.tsx

@@ -12,9 +12,9 @@ import { FormattedMessage } from '@kbn/i18n-react';
 import { EuiBasicTableColumn } from '@elastic/eui/src/components/basic_table/basic_table';
 import { i18n } from '@kbn/i18n';
 import { FIELD_FORMAT_IDS } from '@kbn/field-formats-plugin/common';
-import { useFieldFormatter } from '../../../contexts/kibana/use_field_formatter';
+import { useFieldFormatter } from '../../contexts/kibana/use_field_formatter';
 import { IngestStatsResponse } from './pipelines';
-import { HelpIcon } from '../../../components/help_icon';
+import { HelpIcon } from '../../components/help_icon';
 
 interface ProcessorsStatsProps {
   stats: Exclude<IngestStatsResponse, undefined>['pipelines'][string]['processors'];

x-pack/plugins/ml/public/application/model_management/pipelines/pipelines.tsx

@@ -16,7 +16,7 @@ import {
   EuiAccordion,
 } from '@elastic/eui';
 import { FormattedMessage } from '@kbn/i18n-react';
-import { useMlKibana } from '../../../contexts/kibana';
+import { useMlKibana } from '../../contexts/kibana';
 import { ModelItem } from '../models_list';
 import { ProcessorsStats } from './expanded_row';
 

x-pack/plugins/ml/public/application/model_management/test_models/models/index_input.tsx

@@ -14,7 +14,7 @@ import { EuiSpacer, EuiSelect, EuiFormRow, EuiAccordion, EuiCodeBlock } from '@e
 
 import { isPopulatedObject } from '@kbn/ml-is-populated-object';
 import { i18n } from '@kbn/i18n';
-import { useMlKibana } from '../../../../contexts/kibana';
+import { useMlKibana } from '../../../contexts/kibana';
 import { RUNNING_STATE } from './inference_base';
 import type { InferrerType } from '.';
 

x-pack/plugins/ml/public/application/model_management/test_models/models/inference_base.ts

@@ -10,9 +10,9 @@ import * as estypes from '@elastic/elasticsearch/lib/api/typesWithBodyKey';
 import { i18n } from '@kbn/i18n';
 
 import { map } from 'rxjs/operators';
-import { MLHttpFetchError } from '../../../../../../common/util/errors';
-import { SupportedPytorchTasksType } from '../../../../../../common/constants/trained_models';
-import { trainedModelsApiProvider } from '../../../../services/ml_api_service/trained_models';
+import { MLHttpFetchError } from '../../../../../common/util/errors';
+import { SupportedPytorchTasksType } from '../../../../../common/constants/trained_models';
+import { trainedModelsApiProvider } from '../../../services/ml_api_service/trained_models';
 import { getInferenceInfoComponent } from './inference_info';
 
 export type InferenceType =

x-pack/plugins/ml/public/application/model_management/test_models/models/inference_input_form/index_input.tsx

@@ -22,7 +22,7 @@ import {
 } from '@elastic/eui';
 
 import { ErrorMessage } from '../../inference_error';
-import { extractErrorMessage } from '../../../../../../../common';
+import { extractErrorMessage } from '../../../../../../common';
 import type { InferrerType } from '..';
 import { useIndexInput, InferenceInputFormIndexControls } from '../index_input';
 import { RUNNING_STATE } from '../inference_base';

x-pack/plugins/ml/public/application/model_management/test_models/models/inference_input_form/text_input.tsx

@@ -12,7 +12,7 @@ import { FormattedMessage } from '@kbn/i18n-react';
 import { EuiSpacer, EuiButton, EuiTabs, EuiTab, EuiForm } from '@elastic/eui';
 
 import { ErrorMessage } from '../../inference_error';
-import { extractErrorMessage } from '../../../../../../../common';
+import { extractErrorMessage } from '../../../../../../common';
 import type { InferrerType } from '..';
 import { OutputLoadingContent } from '../../output_loading';
 import { RUNNING_STATE } from '../inference_base';

x-pack/plugins/ml/public/application/model_management/test_models/models/ner/ner_inference.ts

@@ -7,12 +7,12 @@
 
 import * as estypes from '@elastic/elasticsearch/lib/api/typesWithBodyKey';
 import { i18n } from '@kbn/i18n';
-import { trainedModelsApiProvider } from '../../../../../services/ml_api_service/trained_models';
+import { trainedModelsApiProvider } from '../../../../services/ml_api_service/trained_models';
 import { InferenceBase, INPUT_TYPE } from '../inference_base';
 import type { InferResponse } from '../inference_base';
 import { getGeneralInputComponent } from '../text_input';
 import { getNerOutputComponent } from './ner_output';
-import { SUPPORTED_PYTORCH_TASKS } from '../../../../../../../common/constants/trained_models';
+import { SUPPORTED_PYTORCH_TASKS } from '../../../../../../common/constants/trained_models';
 
 export type FormattedNerResponse = Array<{
   value: string;

x-pack/plugins/ml/public/application/model_management/test_models/models/ner/ner_output.tsx

@@ -21,7 +21,7 @@ import {
 import {
   useCurrentEuiTheme,
   EuiThemeType,
-} from '../../../../../components/color_range_legend/use_color_range';
+} from '../../../../components/color_range_legend/use_color_range';
 import type { NerInference, NerResponse } from './ner_inference';
 import { INPUT_TYPE } from '../inference_base';
 

x-pack/plugins/ml/public/application/model_management/test_models/models/question_answering/question_answering_inference.ts

@@ -13,8 +13,8 @@ import { InferenceBase, INPUT_TYPE } from '../inference_base';
 import type { InferResponse } from '../inference_base';
 import { getQuestionAnsweringInput } from './question_answering_input';
 import { getQuestionAnsweringOutputComponent } from './question_answering_output';
-import { SUPPORTED_PYTORCH_TASKS } from '../../../../../../../common/constants/trained_models';
-import { trainedModelsApiProvider } from '../../../../../services/ml_api_service/trained_models';
+import { SUPPORTED_PYTORCH_TASKS } from '../../../../../../common/constants/trained_models';
+import { trainedModelsApiProvider } from '../../../../services/ml_api_service/trained_models';
 
 export interface RawQuestionAnsweringResponse {
   inference_results: Array<{

x-pack/plugins/ml/public/application/model_management/test_models/models/question_answering/question_answering_output.tsx

@@ -10,7 +10,7 @@ import useObservable from 'react-use/lib/useObservable';
 
 import { EuiBadge, EuiHorizontalRule } from '@elastic/eui';
 
-import { useCurrentEuiTheme } from '../../../../../components/color_range_legend/use_color_range';
+import { useCurrentEuiTheme } from '../../../../components/color_range_legend/use_color_range';
 
 import type {
   QuestionAnsweringInference,

x-pack/plugins/ml/public/application/model_management/test_models/models/raw_output.tsx

@@ -9,7 +9,7 @@ import * as estypes from '@elastic/elasticsearch/lib/api/typesWithBodyKey';
 import React, { FC } from 'react';
 import { Observable } from 'rxjs';
 import useObservable from 'react-use/lib/useObservable';
-import { MLJobEditor } from '../../../../jobs/jobs_list/components/ml_job_editor';
+import { MLJobEditor } from '../../../jobs/jobs_list/components/ml_job_editor';
 
 import type { InferrerType } from '.';
 import { NerResponse } from './ner';

x-pack/plugins/ml/public/application/model_management/test_models/models/text_classification/fill_mask_inference.ts

@@ -13,8 +13,8 @@ import type { TextClassificationResponse, RawTextClassificationResponse } from '
 import { processResponse, processInferenceResult } from './common';
 import { getGeneralInputComponent } from '../text_input';
 import { getFillMaskOutputComponent } from './fill_mask_output';
-import { SUPPORTED_PYTORCH_TASKS } from '../../../../../../../common/constants/trained_models';
-import { trainedModelsApiProvider } from '../../../../../services/ml_api_service/trained_models';
+import { SUPPORTED_PYTORCH_TASKS } from '../../../../../../common/constants/trained_models';
+import { trainedModelsApiProvider } from '../../../../services/ml_api_service/trained_models';
 
 const MASK = '[MASK]';
 

x-pack/plugins/ml/public/application/model_management/test_models/models/text_classification/lang_ident_inference.ts

@@ -13,7 +13,7 @@ import { processInferenceResult, processResponse } from './common';
 import { getGeneralInputComponent } from '../text_input';
 import { getLangIdentOutputComponent } from './lang_ident_output';
 import type { TextClassificationResponse, RawTextClassificationResponse } from './common';
-import { trainedModelsApiProvider } from '../../../../../services/ml_api_service/trained_models';
+import { trainedModelsApiProvider } from '../../../../services/ml_api_service/trained_models';
 
 export class LangIdentInference extends InferenceBase<TextClassificationResponse> {
   protected inferenceType: InferenceType = 'classification';

x-pack/plugins/ml/public/application/model_management/test_models/models/text_classification/text_classification_inference.ts

@@ -12,8 +12,8 @@ import { processInferenceResult, processResponse } from './common';
 import type { TextClassificationResponse, RawTextClassificationResponse } from './common';
 import { getGeneralInputComponent } from '../text_input';
 import { getTextClassificationOutputComponent } from './text_classification_output';
-import { SUPPORTED_PYTORCH_TASKS } from '../../../../../../../common/constants/trained_models';
-import { trainedModelsApiProvider } from '../../../../../services/ml_api_service/trained_models';
+import { SUPPORTED_PYTORCH_TASKS } from '../../../../../../common/constants/trained_models';
+import { trainedModelsApiProvider } from '../../../../services/ml_api_service/trained_models';
 
 export class TextClassificationInference extends InferenceBase<TextClassificationResponse> {
   protected inferenceType = SUPPORTED_PYTORCH_TASKS.TEXT_CLASSIFICATION;

x-pack/plugins/ml/public/application/model_management/test_models/models/text_classification/zero_shot_classification_inference.ts

@@ -9,14 +9,14 @@ import { i18n } from '@kbn/i18n';
 import { BehaviorSubject } from 'rxjs';
 import { map } from 'rxjs/operators';
 import { estypes } from '@elastic/elasticsearch';
-import { trainedModelsApiProvider } from '../../../../../services/ml_api_service/trained_models';
+import { trainedModelsApiProvider } from '../../../../services/ml_api_service/trained_models';
 import { InferenceBase, INPUT_TYPE } from '../inference_base';
 import { processInferenceResult, processResponse } from './common';
 import type { TextClassificationResponse, RawTextClassificationResponse } from './common';
 
 import { getZeroShotClassificationInput } from './zero_shot_classification_input';
 import { getTextClassificationOutputComponent } from './text_classification_output';
-import { SUPPORTED_PYTORCH_TASKS } from '../../../../../../../common/constants/trained_models';
+import { SUPPORTED_PYTORCH_TASKS } from '../../../../../../common/constants/trained_models';
 
 export class ZeroShotClassificationInference extends InferenceBase<TextClassificationResponse> {
   protected inferenceType = SUPPORTED_PYTORCH_TASKS.ZERO_SHOT_CLASSIFICATION;

x-pack/plugins/ml/public/application/model_management/test_models/models/text_embedding/text_embedding_inference.ts

@@ -11,8 +11,8 @@ import { InferenceBase, INPUT_TYPE } from '../inference_base';
 import type { InferResponse } from '../inference_base';
 import { getGeneralInputComponent } from '../text_input';
 import { getTextEmbeddingOutputComponent } from './text_embedding_output';
-import { SUPPORTED_PYTORCH_TASKS } from '../../../../../../../common/constants/trained_models';
-import { trainedModelsApiProvider } from '../../../../../services/ml_api_service/trained_models';
+import { SUPPORTED_PYTORCH_TASKS } from '../../../../../../common/constants/trained_models';
+import { trainedModelsApiProvider } from '../../../../services/ml_api_service/trained_models';
 
 export interface RawTextEmbeddingResponse {
   inference_results: Array<{ predicted_value: number[] }>;

x-pack/plugins/ml/public/application/model_management/test_models/selected_model.tsx

@@ -23,8 +23,8 @@ import { TextEmbeddingInference } from './models/text_embedding';
 import {
   TRAINED_MODEL_TYPE,
   SUPPORTED_PYTORCH_TASKS,
-} from '../../../../../common/constants/trained_models';
-import { useMlApiContext } from '../../../contexts/kibana';
+} from '../../../../common/constants/trained_models';
+import { useMlApiContext } from '../../contexts/kibana';
 import { InferenceInputForm } from './models/inference_input_form';
 import { InferrerType } from './models';
 import { INPUT_TYPE } from './models/inference_base';

x-pack/plugins/ml/public/application/model_management/test_models/test_flyout.tsx

@@ -22,7 +22,7 @@ import {
 
 import { SelectedModel } from './selected_model';
 import { INPUT_TYPE } from './models/inference_base';
-import { useTrainedModelsApiService } from '../../../services/ml_api_service/trained_models';
+import { useTrainedModelsApiService } from '../../services/ml_api_service/trained_models';
 
 interface Props {
   modelId: string;

x-pack/plugins/ml/public/application/model_management/test_models/utils.ts

@@ -9,8 +9,8 @@ import {
   TRAINED_MODEL_TYPE,
   DEPLOYMENT_STATE,
   SUPPORTED_PYTORCH_TASKS,
-} from '../../../../../common/constants/trained_models';
-import type { SupportedPytorchTasksType } from '../../../../../common/constants/trained_models';
+} from '../../../../common/constants/trained_models';
+import type { SupportedPytorchTasksType } from '../../../../common/constants/trained_models';
 import type { ModelItem } from '../models_list';
 
 const PYTORCH_TYPES = Object.values(SUPPORTED_PYTORCH_TASKS);

x-pack/plugins/ml/public/application/overview/overview_page.tsx

@@ -19,11 +19,13 @@ import { SavedObjectsWarning } from '../components/saved_objects_warning';
 import { UpgradeWarning } from '../components/upgrade';
 import { HelpMenu } from '../components/help_menu';
 import { useMlKibana } from '../contexts/kibana';
-import { NodesList } from '../trained_models/nodes_overview';
+import { NodesList } from '../memory_usage/nodes_overview';
 import { MlPageHeader } from '../components/page_header';
 import { PageTitle } from '../components/page_title';
+import { useIsServerless } from '../contexts/kibana/use_is_serverless';
 
 export const OverviewPage: FC = () => {
+  const serverless = useIsServerless();
   const canViewMlNodes = checkPermission('canViewMlNodes');
 
   const disableCreateAnomalyDetectionJob = !checkPermission('canCreateJob') || !mlNodesAvailable();
@@ -62,7 +64,7 @@ export const OverviewPage: FC = () => {
 
       <GettingStartedCallout />
 
-      {canViewMlNodes ? (
+      {canViewMlNodes && serverless === false ? (
         <>
           <EuiPanel hasShadow={false} hasBorder>
             <NodesList compactView />

x-pack/plugins/ml/public/application/routing/routes/index.ts

@@ -17,3 +17,4 @@ export * from './explorer';
 export * from './access_denied';
 export * from './trained_models';
 export * from './notifications';
+export * from './memory_usage';

x-pack/plugins/ml/public/application/routing/routes/memory_usage.tsx

@@ -0,0 +1,53 @@
+/*
+ * 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 React, { FC } from 'react';
+import { i18n } from '@kbn/i18n';
+import { ML_PAGES } from '../../../locator';
+import { NavigateToPath } from '../../contexts/kibana';
+import { MlRoute, PageLoader, PageProps, createPath } from '../router';
+import { useResolver } from '../use_resolver';
+import { basicResolvers } from '../resolvers';
+import { getBreadcrumbWithUrlForApp } from '../breadcrumbs';
+import { MemoryUsagePage } from '../../memory_usage';
+
+export const nodesListRouteFactory = (
+  navigateToPath: NavigateToPath,
+  basePath: string
+): MlRoute => ({
+  path: createPath(ML_PAGES.MEMORY_USAGE),
+  render: (props, deps) => <PageWrapper {...props} deps={deps} />,
+  title: i18n.translate('xpack.ml.modelManagement.memoryUsage.docTitle', {
+    defaultMessage: 'Memory Usage',
+  }),
+  breadcrumbs: [
+    getBreadcrumbWithUrlForApp('ML_BREADCRUMB', navigateToPath, basePath),
+    {
+      text: i18n.translate('xpack.ml.trainedModelsBreadcrumbs.nodeOverviewLabel', {
+        defaultMessage: 'Memory Usage',
+      }),
+    },
+  ],
+  enableDatePicker: true,
+});
+
+const PageWrapper: FC<PageProps> = ({ location, deps }) => {
+  const { context } = useResolver(
+    undefined,
+    undefined,
+    deps.config,
+    deps.dataViewsContract,
+    deps.getSavedSearchDeps,
+    basicResolvers(deps)
+  );
+
+  return (
+    <PageLoader context={context}>
+      <MemoryUsagePage />
+    </PageLoader>
+  );
+};

x-pack/plugins/ml/public/application/routing/routes/trained_models/index.ts

@@ -6,4 +6,3 @@
  */
 
 export * from './models_list';
-export * from './nodes_list';

x-pack/plugins/ml/public/application/routing/routes/trained_models/models_list.tsx

@@ -15,7 +15,7 @@ import { createPath, MlRoute, PageLoader, PageProps } from '../../router';
 import { useResolver } from '../../use_resolver';
 import { basicResolvers } from '../../resolvers';
 import { getBreadcrumbWithUrlForApp } from '../../breadcrumbs';
-import { ModelsList } from '../../../trained_models/models_management';
+import { ModelsList } from '../../../model_management';
 import { MlPageHeader } from '../../../components/page_header';
 
 export const modelsListRouteFactory = (
@@ -52,7 +52,6 @@ const PageWrapper: FC<PageProps> = ({ location, deps }) => {
   );
   return (
     <PageLoader context={context}>
-      <ModelsList />
       <MlPageHeader>
         <EuiFlexGroup responsive={false} wrap={false} alignItems={'center'} gutterSize={'m'}>
           <EuiFlexItem grow={false}>
@@ -63,6 +62,7 @@ const PageWrapper: FC<PageProps> = ({ location, deps }) => {
           </EuiFlexItem>
         </EuiFlexGroup>
       </MlPageHeader>
+      <ModelsList />
     </PageLoader>
   );
 };

x-pack/plugins/ml/public/application/routing/routes/trained_models/nodes_list.tsx

@@ -1,68 +0,0 @@
-/*
- * 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 React, { FC } from 'react';
-import { FormattedMessage } from '@kbn/i18n-react';
-import { i18n } from '@kbn/i18n';
-import { EuiFlexGroup, EuiFlexItem } from '@elastic/eui';
-import { useTimefilter } from '@kbn/ml-date-picker';
-import { ML_PAGES } from '../../../../locator';
-import { NavigateToPath } from '../../../contexts/kibana';
-import { createPath, MlRoute, PageLoader, PageProps } from '../../router';
-import { useResolver } from '../../use_resolver';
-import { basicResolvers } from '../../resolvers';
-import { getBreadcrumbWithUrlForApp } from '../../breadcrumbs';
-import { NodesList } from '../../../trained_models/nodes_overview';
-import { MlPageHeader } from '../../../components/page_header';
-
-export const nodesListRouteFactory = (
-  navigateToPath: NavigateToPath,
-  basePath: string
-): MlRoute => ({
-  path: createPath(ML_PAGES.TRAINED_MODELS_NODES),
-  render: (props, deps) => <PageWrapper {...props} deps={deps} />,
-  title: i18n.translate('xpack.ml.modelManagement.nodesOverview.docTitle', {
-    defaultMessage: 'Nodes',
-  }),
-  breadcrumbs: [
-    getBreadcrumbWithUrlForApp('ML_BREADCRUMB', navigateToPath, basePath),
-    getBreadcrumbWithUrlForApp('TRAINED_MODELS', navigateToPath, basePath),
-    {
-      text: i18n.translate('xpack.ml.trainedModelsBreadcrumbs.nodeOverviewLabel', {
-        defaultMessage: 'Nodes',
-      }),
-    },
-  ],
-  enableDatePicker: true,
-});
-
-const PageWrapper: FC<PageProps> = ({ location, deps }) => {
-  const { context } = useResolver(
-    undefined,
-    undefined,
-    deps.config,
-    deps.dataViewsContract,
-    deps.getSavedSearchDeps,
-    basicResolvers(deps)
-  );
-  useTimefilter({ timeRangeSelector: false, autoRefreshSelector: true });
-  return (
-    <PageLoader context={context}>
-      <MlPageHeader>
-        <EuiFlexGroup responsive={false} wrap={false} alignItems={'center'} gutterSize={'m'}>
-          <EuiFlexItem grow={false}>
-            <FormattedMessage
-              id="xpack.ml.modelManagement.nodesOverviewHeader"
-              defaultMessage="Nodes"
-            />
-          </EuiFlexItem>
-        </EuiFlexGroup>
-      </MlPageHeader>
-      <NodesList />
-    </PageLoader>
-  );
-};

x-pack/plugins/ml/public/application/services/ml_api_service/trained_models.ts

@@ -9,6 +9,7 @@ import * as estypes from '@elastic/elasticsearch/lib/api/typesWithBodyKey';
 
 import { useMemo } from 'react';
 import { HttpFetchQuery } from '@kbn/core/public';
+import { MlSavedObjectType } from '../../../../common/types/saved_objects';
 import { HttpService } from '../http_service';
 import { basePath } from '.';
 import { useMlKibana } from '../../contexts/kibana';
@@ -17,6 +18,7 @@ import type {
   ModelPipelines,
   TrainedModelStat,
   NodesOverviewResponse,
+  MemoryUsageInfo,
 } from '../../../../common/types/trained_models';
 
 export interface InferenceQueryParams {
@@ -119,7 +121,7 @@ export function trainedModelsApiProvider(httpService: HttpService) {
 
     getTrainedModelsNodesOverview() {
       return httpService.http<NodesOverviewResponse>({
-        path: `${apiBasePath}/trained_models/nodes_overview`,
+        path: `${apiBasePath}/model_management/nodes_overview`,
         method: 'GET',
       });
     },
@@ -185,6 +187,14 @@ export function trainedModelsApiProvider(httpService: HttpService) {
         body,
       });
     },
+
+    memoryUsage(type?: MlSavedObjectType, node?: string, showClosedJobs = false) {
+      return httpService.http<MemoryUsageInfo[]>({
+        path: `${apiBasePath}/model_management/memory_usage`,
+        method: 'GET',
+        query: { type, node, showClosedJobs },
+      });
+    },
   };
 }
 

x-pack/plugins/ml/public/application/trained_models/nodes_overview/expanded_row.tsx

@@ -1,113 +0,0 @@
-/*
- * 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 React, { FC } from 'react';
-import {
-  EuiDescriptionList,
-  EuiFlexGrid,
-  EuiFlexItem,
-  EuiPanel,
-  EuiSpacer,
-  EuiTitle,
-} from '@elastic/eui';
-import { FormattedMessage } from '@kbn/i18n-react';
-import { cloneDeep } from 'lodash';
-import { FIELD_FORMAT_IDS } from '@kbn/field-formats-plugin/common';
-import { css } from '@emotion/react';
-import { NodeItem } from './nodes_list';
-import { useListItemsFormatter } from '../models_management/expanded_row';
-import { AllocatedModels } from './allocated_models';
-import { useFieldFormatter } from '../../contexts/kibana/use_field_formatter';
-
-interface ExpandedRowProps {
-  item: NodeItem;
-}
-
-export const ExpandedRow: FC<ExpandedRowProps> = ({ item }) => {
-  const bytesFormatter = useFieldFormatter(FIELD_FORMAT_IDS.BYTES);
-
-  const formatToListItems = useListItemsFormatter();
-
-  const {
-    allocated_models: allocatedModels,
-    attributes,
-    memory_overview: memoryOverview,
-    id,
-    ...details
-  } = cloneDeep(item);
-
-  // Process node attributes
-  attributes['ml.machine_memory'] = bytesFormatter(attributes['ml.machine_memory']);
-  attributes['ml.max_jvm_size'] = bytesFormatter(attributes['ml.max_jvm_size']);
-
-  return (
-    <div
-      css={css`
-        width: 100%;
-      `}
-    >
-      <EuiFlexGrid columns={2} gutterSize={'s'}>
-        <EuiFlexItem>
-          <EuiPanel>
-            <EuiTitle size={'xs'}>
-              <h5>
-                <FormattedMessage
-                  id="xpack.ml.trainedModels.nodesList.expandedRow.detailsTitle"
-                  defaultMessage="Details"
-                />
-              </h5>
-            </EuiTitle>
-            <EuiSpacer size={'m'} />
-            <EuiDescriptionList
-              compressed={true}
-              type="column"
-              listItems={formatToListItems(details)}
-            />
-          </EuiPanel>
-        </EuiFlexItem>
-
-        <EuiFlexItem>
-          <EuiPanel>
-            <EuiTitle size={'xs'}>
-              <h5>
-                <FormattedMessage
-                  id="xpack.ml.trainedModels.nodesList.expandedRow.attributesTitle"
-                  defaultMessage="Attributes"
-                />
-              </h5>
-            </EuiTitle>
-            <EuiSpacer size={'m'} />
-            <EuiDescriptionList
-              compressed={true}
-              type="column"
-              listItems={formatToListItems(attributes)}
-            />
-          </EuiPanel>
-        </EuiFlexItem>
-      </EuiFlexGrid>
-
-      {allocatedModels.length > 0 ? (
-        <>
-          <EuiSpacer size={'s'} />
-          <EuiPanel>
-            <EuiTitle size={'xs'}>
-              <h5>
-                <FormattedMessage
-                  id="xpack.ml.trainedModels.nodesList.expandedRow.allocatedModelsTitle"
-                  defaultMessage="Allocated models"
-                />
-              </h5>
-            </EuiTitle>
-            <EuiSpacer size={'m'} />
-
-            <AllocatedModels models={allocatedModels} />
-          </EuiPanel>
-        </>
-      ) : null}
-    </div>
-  );
-};

x-pack/plugins/ml/public/locator/formatters/trained_models.ts

@@ -6,10 +6,7 @@
  */
 
 import { setStateToKbnUrl } from '@kbn/kibana-utils-plugin/public';
-import type {
-  TrainedModelsNodesUrlState,
-  TrainedModelsUrlState,
-} from '../../../common/types/locator';
+import type { MemoryUsageUrlState, TrainedModelsUrlState } from '../../../common/types/locator';
 import { ML_PAGES } from '../../../common/constants/locator';
 import type { AppPageState, ListingPageUrlState } from '../../../common/types/common';
 
@@ -41,11 +38,11 @@ export function formatTrainedModelsManagementUrl(
   return url;
 }
 
-export function formatTrainedModelsNodesManagementUrl(
+export function formatMemoryUsageUrl(
   appBasePath: string,
-  mlUrlGeneratorState: TrainedModelsNodesUrlState['pageState']
+  mlUrlGeneratorState: MemoryUsageUrlState['pageState']
 ): string {
-  let url = `${appBasePath}/${ML_PAGES.TRAINED_MODELS_NODES}`;
+  let url = `${appBasePath}/${ML_PAGES.MEMORY_USAGE}`;
   if (mlUrlGeneratorState) {
     const { nodeId } = mlUrlGeneratorState;
     if (nodeId) {
@@ -54,7 +51,7 @@ export function formatTrainedModelsNodesManagementUrl(
       };
 
       const queryState: AppPageState<ListingPageUrlState> = {
-        [ML_PAGES.TRAINED_MODELS_NODES]: nodesListState,
+        [ML_PAGES.MEMORY_USAGE]: nodesListState,
       };
 
       url = setStateToKbnUrl<AppPageState<ListingPageUrlState>>(

x-pack/plugins/ml/public/locator/ml_locator.ts

@@ -29,7 +29,7 @@ import {
 } from './formatters';
 import {
   formatTrainedModelsManagementUrl,
-  formatTrainedModelsNodesManagementUrl,
+  formatMemoryUsageUrl,
 } from './formatters/trained_models';
 
 export type { MlLocatorParams, MlLocator };
@@ -74,8 +74,8 @@ export class MlLocatorDefinition implements LocatorDefinition<MlLocatorParams> {
       case ML_PAGES.TRAINED_MODELS_MANAGE:
         path = formatTrainedModelsManagementUrl('', params.pageState);
         break;
-      case ML_PAGES.TRAINED_MODELS_NODES:
-        path = formatTrainedModelsNodesManagementUrl('', params.pageState);
+      case ML_PAGES.MEMORY_USAGE:
+        path = formatMemoryUsageUrl('', params.pageState);
         break;
       case ML_PAGES.ANOMALY_DETECTION_CREATE_JOB:
       case ML_PAGES.ANOMALY_DETECTION_CREATE_JOB_RECOGNIZER:

x-pack/plugins/ml/public/register_helper/register_search_links/search_deep_links.ts

@@ -49,11 +49,11 @@ const MODEL_MANAGEMENT_DEEP_LINK: AppDeepLink = {
       path: `/${ML_PAGES.TRAINED_MODELS_MANAGE}`,
     },
     {
-      id: 'mlNodesOverviewDeepLink',
-      title: i18n.translate('xpack.ml.deepLink.nodesOverview', {
-        defaultMessage: 'Nodes',
+      id: 'mlMemoryUsageDeepLink',
+      title: i18n.translate('xpack.ml.deepLink.memoryUsage', {
+        defaultMessage: 'Memory usage',
       }),
-      path: `/${ML_PAGES.TRAINED_MODELS_NODES}`,
+      path: `/${ML_PAGES.MEMORY_USAGE}`,
     },
   ],
 };

x-pack/plugins/ml/server/models/data_frame_analytics/index.ts

@@ -6,5 +6,4 @@
  */
 
 export { analyticsAuditMessagesProvider } from './analytics_audit_messages';
-export { modelsProvider } from './models_provider';
 export { AnalyticsManager } from './analytics_manager';

x-pack/plugins/ml/server/models/data_frame_analytics/models_provider.ts

@@ -1,220 +0,0 @@
-/*
- * 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 type { IScopedClusterClient } from '@kbn/core/server';
-import { pick } from 'lodash';
-import {
-  MlTrainedModelStats,
-  NodesInfoNodeInfo,
-} from '@elastic/elasticsearch/lib/api/typesWithBodyKey';
-import { isDefined } from '@kbn/ml-is-defined';
-import type {
-  NodeDeploymentStatsResponse,
-  PipelineDefinition,
-  NodesOverviewResponse,
-} from '../../../common/types/trained_models';
-import type { MlClient } from '../../lib/ml_client';
-import {
-  TrainedModelDeploymentStatsResponse,
-  TrainedModelModelSizeStats,
-} from '../../../common/types/trained_models';
-
-export type ModelService = ReturnType<typeof modelsProvider>;
-
-const NODE_FIELDS = ['attributes', 'name', 'roles'] as const;
-
-export type RequiredNodeFields = Pick<NodesInfoNodeInfo, typeof NODE_FIELDS[number]>;
-
-// @ts-expect-error TrainedModelDeploymentStatsResponse missing properties from MlTrainedModelDeploymentStats
-interface TrainedModelStatsResponse extends MlTrainedModelStats {
-  deployment_stats?: Omit<TrainedModelDeploymentStatsResponse, 'model_id'>;
-  model_size_stats?: TrainedModelModelSizeStats;
-}
-
-export interface MemoryStatsResponse {
-  _nodes: { total: number; failed: number; successful: number };
-  cluster_name: string;
-  nodes: Record<
-    string,
-    {
-      jvm: {
-        heap_max_in_bytes: number;
-        java_inference_in_bytes: number;
-        java_inference_max_in_bytes: number;
-      };
-      mem: {
-        adjusted_total_in_bytes: number;
-        total_in_bytes: number;
-        ml: {
-          data_frame_analytics_in_bytes: number;
-          native_code_overhead_in_bytes: number;
-          max_in_bytes: number;
-          anomaly_detectors_in_bytes: number;
-          native_inference_in_bytes: number;
-        };
-      };
-      transport_address: string;
-      roles: string[];
-      name: string;
-      attributes: Record<`${'ml.'}${string}`, string>;
-      ephemeral_id: string;
-    }
-  >;
-}
-
-export function modelsProvider(client: IScopedClusterClient, mlClient: MlClient) {
-  return {
-    /**
-     * Retrieves the map of model ids and aliases with associated pipelines.
-     * @param modelIds - Array of models ids and model aliases.
-     */
-    async getModelsPipelines(modelIds: string[]) {
-      const modelIdsMap = new Map<string, Record<string, PipelineDefinition> | null>(
-        modelIds.map((id: string) => [id, null])
-      );
-
-      try {
-        const body = await client.asCurrentUser.ingest.getPipeline();
-
-        for (const [pipelineName, pipelineDefinition] of Object.entries(body)) {
-          const { processors } = pipelineDefinition as { processors: Array<Record<string, any>> };
-
-          for (const processor of processors) {
-            const id = processor.inference?.model_id;
-            if (modelIdsMap.has(id)) {
-              const obj = modelIdsMap.get(id);
-              if (obj === null) {
-                modelIdsMap.set(id, { [pipelineName]: pipelineDefinition });
-              } else {
-                obj![pipelineName] = pipelineDefinition;
-              }
-            }
-          }
-        }
-      } catch (error) {
-        if (error.statusCode === 404) {
-          // ES returns 404 when there are no pipelines
-          // Instead, we should return the modelIdsMap and a 200
-          return modelIdsMap;
-        }
-        throw error;
-      }
-
-      return modelIdsMap;
-    },
-
-    /**
-     * Provides the ML nodes overview with allocated models.
-     */
-    async getNodesOverview(): Promise<NodesOverviewResponse> {
-      // TODO set node_id to ml:true when elasticsearch client is updated.
-      const response = (await mlClient.getMemoryStats()) as MemoryStatsResponse;
-
-      const { trained_model_stats: trainedModelStats } = await mlClient.getTrainedModelsStats({
-        size: 10000,
-      });
-
-      const mlNodes = Object.entries(response.nodes).filter(([, node]) =>
-        node.roles.includes('ml')
-      );
-
-      const nodeDeploymentStatsResponses: NodeDeploymentStatsResponse[] = mlNodes.map(
-        ([nodeId, node]) => {
-          const nodeFields = pick(node, NODE_FIELDS) as RequiredNodeFields;
-
-          nodeFields.attributes = nodeFields.attributes;
-
-          const allocatedModels = (trainedModelStats as TrainedModelStatsResponse[])
-            .filter(
-              (d) =>
-                isDefined(d.deployment_stats) &&
-                isDefined(d.deployment_stats.nodes) &&
-                d.deployment_stats.nodes.some((n) => Object.keys(n.node)[0] === nodeId)
-            )
-            .map((d) => {
-              const modelSizeState = d.model_size_stats;
-              const deploymentStats = d.deployment_stats;
-
-              if (!deploymentStats || !modelSizeState) {
-                throw new Error('deploymentStats or modelSizeState not defined');
-              }
-
-              const { nodes, ...rest } = deploymentStats;
-
-              const { node: tempNode, ...nodeRest } = nodes.find(
-                (v) => Object.keys(v.node)[0] === nodeId
-              )!;
-              return {
-                model_id: d.model_id,
-                ...rest,
-                ...modelSizeState,
-                node: nodeRest,
-              };
-            });
-
-          const modelsMemoryUsage = allocatedModels.map((v) => {
-            return {
-              model_id: v.model_id,
-              model_size: v.required_native_memory_bytes,
-            };
-          });
-
-          const memoryRes = {
-            adTotalMemory: node.mem.ml.anomaly_detectors_in_bytes,
-            dfaTotalMemory: node.mem.ml.data_frame_analytics_in_bytes,
-            trainedModelsTotalMemory: node.mem.ml.native_inference_in_bytes,
-          };
-
-          for (const key of Object.keys(memoryRes)) {
-            if (memoryRes[key as keyof typeof memoryRes] > 0) {
-              /**
-               * The amount of memory needed to load the ML native code shared libraries. The assumption is that the first
-               * ML job to run on a given node will do this, and then subsequent ML jobs on the same node will reuse the
-               * same already-loaded code.
-               */
-              memoryRes[key as keyof typeof memoryRes] += node.mem.ml.native_code_overhead_in_bytes;
-              break;
-            }
-          }
-
-          return {
-            id: nodeId,
-            ...nodeFields,
-            allocated_models: allocatedModels,
-            memory_overview: {
-              machine_memory: {
-                total: node.mem.adjusted_total_in_bytes,
-                jvm: node.jvm.heap_max_in_bytes,
-              },
-              anomaly_detection: {
-                total: memoryRes.adTotalMemory,
-              },
-              dfa_training: {
-                total: memoryRes.dfaTotalMemory,
-              },
-              trained_models: {
-                total: memoryRes.trainedModelsTotalMemory,
-                by_model: modelsMemoryUsage,
-              },
-              ml_max_in_bytes: node.mem.ml.max_in_bytes,
-            },
-          };
-        }
-      );
-
-      return {
-        // TODO preserve _nodes from the response when getMemoryStats method is updated to support ml:true filter
-        _nodes: {
-          ...response._nodes,
-          total: mlNodes.length,
-          successful: mlNodes.length,
-        },
-        nodes: nodeDeploymentStatsResponses,
-      };
-    },
-  };
-}

x-pack/plugins/ml/server/models/model_management/index.ts

@@ -0,0 +1,9 @@
+/*
+ * 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.
+ */
+
+export { modelsProvider } from './models_provider';
+export { MemoryUsageService } from './memory_usage';

x-pack/plugins/ml/server/models/model_management/memory_usage.test.ts

@@ -5,16 +5,12 @@
  * 2.0.
  */
 
-import { MemoryStatsResponse, ModelService, modelsProvider } from './models_provider';
-import { IScopedClusterClient } from '@kbn/core/server';
-import { MlClient } from '../../lib/ml_client';
+import { MemoryUsageService } from './memory_usage';
+import type { MlClient } from '../../lib/ml_client';
 import mockResponse from './__mocks__/mock_deployment_response.json';
+import type { MemoryStatsResponse } from '../../../common/types/trained_models';
 
 describe('Model service', () => {
-  const client = {
-    asInternalUser: {},
-  } as unknown as jest.Mocked<IScopedClusterClient>;
-
   const mlClient = {
     getTrainedModelsStats: jest.fn(() => {
       return Promise.resolve({
@@ -137,10 +133,10 @@ describe('Model service', () => {
     }),
   } as unknown as jest.Mocked<MlClient>;
 
-  let service: ModelService;
+  let service: MemoryUsageService;
 
   beforeEach(() => {
-    service = modelsProvider(client, mlClient);
+    service = new MemoryUsageService(mlClient);
   });
 
   afterEach(() => {});

x-pack/plugins/ml/server/models/model_management/memory_usage.ts

@@ -0,0 +1,277 @@
+/*
+ * 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 type * as estypes from '@elastic/elasticsearch/lib/api/typesWithBodyKey';
+import numeral from '@elastic/numeral';
+import { pick } from 'lodash';
+import { isDefined } from '@kbn/ml-is-defined';
+import type {
+  MemoryUsageInfo,
+  TrainedModelStatsResponse,
+  MemoryStatsResponse,
+} from '../../../common/types/trained_models';
+
+import type { JobStats } from '../../../common/types/anomaly_detection_jobs';
+import type { MlSavedObjectType } from '../../../common/types/saved_objects';
+import type { MlClient } from '../../lib/ml_client';
+import type {
+  NodeDeploymentStatsResponse,
+  NodesOverviewResponse,
+} from '../../../common/types/trained_models';
+
+// @ts-expect-error numeral missing value
+const AD_EXTRA_MEMORY = numeral('10MB').value();
+// @ts-expect-error numeral missing value
+const DFA_EXTRA_MEMORY = numeral('5MB').value();
+
+const NODE_FIELDS = ['attributes', 'name', 'roles'] as const;
+
+export type RequiredNodeFields = Pick<estypes.NodesInfoNodeInfo, typeof NODE_FIELDS[number]>;
+
+export class MemoryUsageService {
+  constructor(private readonly mlClient: MlClient) {}
+
+  public async getMemorySizes(itemType?: MlSavedObjectType, node?: string, showClosedJobs = false) {
+    let memories: MemoryUsageInfo[] = [];
+
+    switch (itemType) {
+      case 'anomaly-detector':
+        memories = await this.getADJobsSizes();
+        break;
+      case 'data-frame-analytics':
+        memories = await this.getDFAJobsSizes();
+        break;
+      case 'trained-model':
+        memories = await this.getTrainedModelsSizes();
+        break;
+      default:
+        memories = [
+          ...(await this.getADJobsSizes()),
+          ...(await this.getDFAJobsSizes()),
+          ...(await this.getTrainedModelsSizes()),
+        ];
+        break;
+    }
+    return memories.filter((m) => nodeFilter(m, node, showClosedJobs));
+  }
+
+  private async getADJobsSizes() {
+    const jobs = await this.mlClient.getJobStats();
+    return jobs.jobs.map(this.getADJobMemorySize);
+  }
+
+  private async getTrainedModelsSizes() {
+    const [models, stats] = await Promise.all([
+      this.mlClient.getTrainedModels(),
+      this.mlClient.getTrainedModelsStats(),
+    ]);
+    const statsMap = stats.trained_model_stats.reduce<Record<string, estypes.MlTrainedModelStats>>(
+      (acc, cur) => {
+        acc[cur.model_id] = cur;
+        return acc;
+      },
+      {}
+    );
+
+    return models.trained_model_configs.map((m) =>
+      this.getTrainedModelMemorySize(m, statsMap[m.model_id])
+    );
+  }
+
+  private async getDFAJobsSizes() {
+    const [jobs, jobsStats] = await Promise.all([
+      this.mlClient.getDataFrameAnalytics(),
+      this.mlClient.getDataFrameAnalyticsStats(),
+    ]);
+    const statsMap = jobsStats.data_frame_analytics.reduce<
+      Record<string, estypes.MlDataframeAnalytics>
+    >((acc, cur) => {
+      acc[cur.id] = cur;
+      return acc;
+    }, {});
+
+    return jobs.data_frame_analytics.map((j) => this.getDFAJobMemorySize(j, statsMap[j.id]));
+  }
+
+  private getADJobMemorySize(jobStats: JobStats): MemoryUsageInfo {
+    let memory = 0;
+    switch (jobStats.model_size_stats.assignment_memory_basis) {
+      case 'model_memory_limit':
+        memory = (jobStats.model_size_stats.model_bytes_memory_limit as number) ?? 0;
+        break;
+      case 'current_model_bytes':
+        memory = jobStats.model_size_stats.model_bytes as number;
+        break;
+      case 'peak_model_bytes':
+        memory = (jobStats.model_size_stats.peak_model_bytes as number) ?? 0;
+        break;
+    }
+
+    const size = memory + AD_EXTRA_MEMORY;
+    const nodeName = jobStats.node?.name;
+    return {
+      id: jobStats.job_id,
+      type: 'anomaly-detector',
+      size,
+      nodeNames: nodeName ? [nodeName] : [],
+    };
+  }
+
+  private getDFAJobMemorySize(
+    job: estypes.MlDataframeAnalyticsSummary,
+    jobStats: estypes.MlDataframeAnalytics
+  ): MemoryUsageInfo {
+    const mml = job.model_memory_limit ?? '0mb';
+    // @ts-expect-error numeral missing value
+    const memory = numeral(mml.toUpperCase()).value();
+    const size = memory + DFA_EXTRA_MEMORY;
+    const nodeName = jobStats.node?.name;
+    return {
+      id: jobStats.id,
+      type: 'data-frame-analytics',
+      size,
+      nodeNames: nodeName ? [nodeName] : [],
+    };
+  }
+
+  private getTrainedModelMemorySize(
+    trainedModel: estypes.MlTrainedModelConfig,
+    trainedModelStats: estypes.MlTrainedModelStats
+  ): MemoryUsageInfo {
+    const memory = trainedModelStats.model_size_stats.required_native_memory_bytes;
+
+    const size = memory + AD_EXTRA_MEMORY;
+    const nodes = (trainedModelStats.deployment_stats?.nodes ??
+      []) as estypes.MlTrainedModelDeploymentNodesStats[];
+    return {
+      id: trainedModelStats.model_id,
+      type: 'trained-model',
+      size,
+      nodeNames: nodes.map((n) => Object.values(n.node)[0].name),
+    };
+  }
+
+  /**
+   * Provides the ML nodes overview with allocated models.
+   */
+  async getNodesOverview(): Promise<NodesOverviewResponse> {
+    // TODO set node_id to ml:true when elasticsearch client is updated.
+    const response = (await this.mlClient.getMemoryStats()) as MemoryStatsResponse;
+
+    const { trained_model_stats: trainedModelStats } = await this.mlClient.getTrainedModelsStats({
+      size: 10000,
+    });
+
+    const mlNodes = Object.entries(response.nodes).filter(([, node]) => node.roles.includes('ml'));
+
+    const nodeDeploymentStatsResponses: NodeDeploymentStatsResponse[] = mlNodes.map(
+      ([nodeId, node]) => {
+        const nodeFields = pick(node, NODE_FIELDS) as RequiredNodeFields;
+
+        nodeFields.attributes = nodeFields.attributes;
+
+        const allocatedModels = (trainedModelStats as TrainedModelStatsResponse[])
+          .filter(
+            (d) =>
+              isDefined(d.deployment_stats) &&
+              isDefined(d.deployment_stats.nodes) &&
+              d.deployment_stats.nodes.some((n) => Object.keys(n.node)[0] === nodeId)
+          )
+          .map((d) => {
+            const modelSizeState = d.model_size_stats;
+            const deploymentStats = d.deployment_stats;
+
+            if (!deploymentStats || !modelSizeState) {
+              throw new Error('deploymentStats or modelSizeState not defined');
+            }
+
+            const { nodes, ...rest } = deploymentStats;
+
+            const { node: tempNode, ...nodeRest } = nodes.find(
+              (v) => Object.keys(v.node)[0] === nodeId
+            )!;
+            return {
+              model_id: d.model_id,
+              ...rest,
+              ...modelSizeState,
+              node: nodeRest,
+            };
+          });
+
+        const modelsMemoryUsage = allocatedModels.map((v) => {
+          return {
+            model_id: v.model_id,
+            model_size: v.required_native_memory_bytes,
+          };
+        });
+
+        const memoryRes = {
+          adTotalMemory: node.mem.ml.anomaly_detectors_in_bytes,
+          dfaTotalMemory: node.mem.ml.data_frame_analytics_in_bytes,
+          trainedModelsTotalMemory: node.mem.ml.native_inference_in_bytes,
+        };
+
+        for (const key of Object.keys(memoryRes)) {
+          if (memoryRes[key as keyof typeof memoryRes] > 0) {
+            /**
+             * The amount of memory needed to load the ML native code shared libraries. The assumption is that the first
+             * ML job to run on a given node will do this, and then subsequent ML jobs on the same node will reuse the
+             * same already-loaded code.
+             */
+            memoryRes[key as keyof typeof memoryRes] += node.mem.ml.native_code_overhead_in_bytes;
+            break;
+          }
+        }
+
+        return {
+          id: nodeId,
+          ...nodeFields,
+          allocated_models: allocatedModels,
+          memory_overview: {
+            machine_memory: {
+              total: node.mem.adjusted_total_in_bytes,
+              jvm: node.jvm.heap_max_in_bytes,
+            },
+            anomaly_detection: {
+              total: memoryRes.adTotalMemory,
+            },
+            dfa_training: {
+              total: memoryRes.dfaTotalMemory,
+            },
+            trained_models: {
+              total: memoryRes.trainedModelsTotalMemory,
+              by_model: modelsMemoryUsage,
+            },
+            ml_max_in_bytes: node.mem.ml.max_in_bytes,
+          },
+        };
+      }
+    );
+
+    return {
+      // TODO preserve _nodes from the response when getMemoryStats method is updated to support ml:true filter
+      _nodes: {
+        ...response._nodes,
+        total: mlNodes.length,
+        successful: mlNodes.length,
+      },
+      nodes: nodeDeploymentStatsResponses,
+    };
+  }
+}
+
+function nodeFilter(m: MemoryUsageInfo, node?: string, showClosedJobs = false) {
+  if (m.nodeNames.length === 0) {
+    return showClosedJobs;
+  }
+
+  if (node === undefined) {
+    return true;
+  }
+
+  return m.nodeNames.includes(node);
+}

x-pack/plugins/ml/server/models/model_management/models_provider.ts

@@ -0,0 +1,55 @@
+/*
+ * 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 type { IScopedClusterClient } from '@kbn/core/server';
+
+import type { PipelineDefinition } from '../../../common/types/trained_models';
+
+export type ModelService = ReturnType<typeof modelsProvider>;
+
+export function modelsProvider(client: IScopedClusterClient) {
+  return {
+    /**
+     * Retrieves the map of model ids and aliases with associated pipelines.
+     * @param modelIds - Array of models ids and model aliases.
+     */
+    async getModelsPipelines(modelIds: string[]) {
+      const modelIdsMap = new Map<string, Record<string, PipelineDefinition> | null>(
+        modelIds.map((id: string) => [id, null])
+      );
+
+      try {
+        const body = await client.asCurrentUser.ingest.getPipeline();
+
+        for (const [pipelineName, pipelineDefinition] of Object.entries(body)) {
+          const { processors } = pipelineDefinition as { processors: Array<Record<string, any>> };
+
+          for (const processor of processors) {
+            const id = processor.inference?.model_id;
+            if (modelIdsMap.has(id)) {
+              const obj = modelIdsMap.get(id);
+              if (obj === null) {
+                modelIdsMap.set(id, { [pipelineName]: pipelineDefinition });
+              } else {
+                obj![pipelineName] = pipelineDefinition;
+              }
+            }
+          }
+        }
+      } catch (error) {
+        if (error.statusCode === 404) {
+          // ES returns 404 when there are no pipelines
+          // Instead, we should return the modelIdsMap and a 200
+          return modelIdsMap;
+        }
+        throw error;
+      }
+
+      return modelIdsMap;
+    },
+  };
+}

x-pack/plugins/ml/server/plugin.ts

@@ -47,6 +47,7 @@ import { jobServiceRoutes } from './routes/job_service';
 import { savedObjectsRoutes } from './routes/saved_objects';
 import { jobValidationRoutes } from './routes/job_validation';
 import { resultsServiceRoutes } from './routes/results_service';
+import { modelManagementRoutes } from './routes/model_management';
 import { systemRoutes } from './routes/system';
 import { MlLicense } from '../common/license';
 import { createSharedServices, SharedServices } from './shared_services';
@@ -217,6 +218,7 @@ export class MlServerPlugin
     jobRoutes(routeInit);
     jobServiceRoutes(routeInit);
     managementRoutes(routeInit);
+    modelManagementRoutes(routeInit);
     resultsServiceRoutes(routeInit);
     jobValidationRoutes(routeInit);
     savedObjectsRoutes(routeInit, {

x-pack/plugins/ml/server/routes/apidoc.json

@@ -170,7 +170,6 @@
     "GetTrainedModel",
     "GetTrainedModelStats",
     "GetTrainedModelStatsById",
-    "GetTrainedModelsNodesOverview",
     "GetTrainedModelPipelines",
     "StartTrainedModelDeployment",
     "UpdateTrainedModelDeployment",
@@ -184,6 +183,10 @@
     "PreviewAlert",
 
     "Management",
-    "ManagementList"
+    "ManagementList",
+
+    "ModelManagement",
+    "GetModelManagementNodesOverview",
+    "GetModelManagementMemoryUsage"
   ]
 }

x-pack/plugins/ml/server/routes/model_management.ts

@@ -0,0 +1,98 @@
+/*
+ * 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.
+ */
+
+/*
+ * 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 { schema } from '@kbn/config-schema';
+import { RouteInitialization } from '../types';
+import { wrapError } from '../client/error_wrapper';
+
+import { MemoryUsageService } from '../models/model_management';
+import { itemTypeLiterals } from './schemas/saved_objects';
+
+export function modelManagementRoutes({ router, routeGuard }: RouteInitialization) {
+  /**
+   * @apiGroup ModelManagement
+   *
+   * @api {get} /api/ml/model_management/nodes_overview Get node overview about the models allocation
+   * @apiName GetModelManagementNodesOverview
+   * @apiDescription Retrieves the list of ML nodes with memory breakdown and allocated models info
+   */
+  router.get(
+    {
+      path: '/api/ml/model_management/nodes_overview',
+      validate: {},
+      options: {
+        tags: [
+          'access:ml:canViewMlNodes',
+          'access:ml:canGetDataFrameAnalytics',
+          'access:ml:canGetJobs',
+          'access:ml:canGetTrainedModels',
+        ],
+      },
+    },
+    routeGuard.fullLicenseAPIGuard(async ({ client, mlClient, response }) => {
+      try {
+        const memoryUsageService = new MemoryUsageService(mlClient);
+        const result = await memoryUsageService.getNodesOverview();
+        return response.ok({
+          body: result,
+        });
+      } catch (e) {
+        return response.customError(wrapError(e));
+      }
+    })
+  );
+
+  /**
+   * @apiGroup ModelManagement
+   *
+   * @api {get} /api/ml/model_management/memory_usage Memory usage for jobs and trained models
+   * @apiName GetModelManagementMemoryUsage
+   * @apiDescription Returns the memory usage for jobs and trained models
+   */
+  router.get(
+    {
+      path: '/api/ml/model_management/memory_usage',
+      validate: {
+        query: schema.object({
+          type: schema.maybe(itemTypeLiterals),
+          node: schema.maybe(schema.string()),
+          showClosedJobs: schema.maybe(schema.boolean()),
+        }),
+      },
+      options: {
+        tags: [
+          'access:ml:canViewMlNodes',
+          'access:ml:canGetDataFrameAnalytics',
+          'access:ml:canGetJobs',
+          'access:ml:canGetTrainedModels',
+        ],
+      },
+    },
+
+    routeGuard.fullLicenseAPIGuard(async ({ mlClient, response, request }) => {
+      try {
+        const memoryUsageService = new MemoryUsageService(mlClient);
+        return response.ok({
+          body: await memoryUsageService.getMemorySizes(
+            request.query.type,
+            request.query.node,
+            request.query.showClosedJobs
+          ),
+        });
+      } catch (e) {
+        return response.customError(wrapError(e));
+      }
+    })
+  );
+}

x-pack/plugins/ml/server/routes/schemas/saved_objects.ts

@@ -19,6 +19,7 @@ export const itemTypeLiterals = schema.oneOf([
 ]);
 
 export const itemTypeSchema = schema.object({ jobType: itemTypeLiterals });
+export const jobTypeSchema = schema.object({ jobType: jobTypeLiterals });
 
 export const updateJobsSpaces = schema.object({
   jobType: jobTypeLiterals,

x-pack/plugins/ml/server/routes/trained_models.ts

@@ -19,10 +19,11 @@ import {
   pipelineSimulateBody,
   updateDeploymentParamsSchema,
 } from './schemas/inference_schema';
-import { modelsProvider } from '../models/data_frame_analytics';
+
 import { TrainedModelConfigResponse } from '../../common/types/trained_models';
 import { mlLog } from '../lib/log';
 import { forceQuerySchema } from './schemas/anomaly_detectors_schema';
+import { modelsProvider } from '../models/model_management';
 
 export function trainedModelsRoutes({ router, routeGuard }: RouteInitialization) {
   /**
@@ -68,7 +69,7 @@ export function trainedModelsRoutes({ router, routeGuard }: RouteInitialization)
               )
             );
 
-            const pipelinesResponse = await modelsProvider(client, mlClient).getModelsPipelines(
+            const pipelinesResponse = await modelsProvider(client).getModelsPipelines(
               modelIdsAndAliases
             );
             for (const model of result) {
@@ -178,9 +179,7 @@ export function trainedModelsRoutes({ router, routeGuard }: RouteInitialization)
     routeGuard.fullLicenseAPIGuard(async ({ client, request, mlClient, response }) => {
       try {
         const { modelId } = request.params;
-        const result = await modelsProvider(client, mlClient).getModelsPipelines(
-          modelId.split(',')
-        );
+        const result = await modelsProvider(client).getModelsPipelines(modelId.split(','));
         return response.ok({
           body: [...result].map(([id, pipelines]) => ({ model_id: id, pipelines })),
         });
@@ -260,38 +259,6 @@ export function trainedModelsRoutes({ router, routeGuard }: RouteInitialization)
     })
   );
 
-  /**
-   * @apiGroup TrainedModels
-   *
-   * @api {get} /api/ml/trained_models/nodes_overview Get node overview about the models allocation
-   * @apiName GetTrainedModelsNodesOverview
-   * @apiDescription Retrieves the list of ML nodes with memory breakdown and allocated models info
-   */
-  router.get(
-    {
-      path: '/api/ml/trained_models/nodes_overview',
-      validate: {},
-      options: {
-        tags: [
-          'access:ml:canViewMlNodes',
-          'access:ml:canGetDataFrameAnalytics',
-          'access:ml:canGetJobs',
-          'access:ml:canGetTrainedModels',
-        ],
-      },
-    },
-    routeGuard.fullLicenseAPIGuard(async ({ client, mlClient, request, response }) => {
-      try {
-        const result = await modelsProvider(client, mlClient).getNodesOverview();
-        return response.ok({
-          body: result,
-        });
-      } catch (e) {
-        return response.customError(wrapError(e));
-      }
-    })
-  );
-
   /**
    * @apiGroup TrainedModels
    *

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

@@ -21232,7 +21232,6 @@
     "xpack.ml.deepLink.filterListsSettings": "Listes de filtres",
     "xpack.ml.deepLink.indexDataVisualizer": "Index Data Visualizer (Visualiseur de données pour les index)",
     "xpack.ml.deepLink.modelManagement": "Gestion des modèles",
-    "xpack.ml.deepLink.nodesOverview": "Nœuds",
     "xpack.ml.deepLink.overview": "Aperçu",
     "xpack.ml.deepLink.settings": "Paramètres",
     "xpack.ml.deepLink.trainedModels": "Modèles entraînés",
@@ -21772,8 +21771,6 @@
     "xpack.ml.mlEntitySelector.dfaOptionsLabel": "Analyse du cadre de données",
     "xpack.ml.mlEntitySelector.fetchError": "Impossible de récupérer les entités de ML",
     "xpack.ml.mlEntitySelector.trainedModelsLabel": "Modèles entraînés",
-    "xpack.ml.modelManagement.nodesOverview.docTitle": "Nœuds",
-    "xpack.ml.modelManagement.nodesOverviewHeader": "Nœuds",
     "xpack.ml.modelManagement.trainedModels.docTitle": "Modèles entraînés",
     "xpack.ml.modelManagement.trainedModelsHeader": "Modèles entraînés",
     "xpack.ml.modelManagementLabel": "Gestion des modèles",
@@ -21884,7 +21881,6 @@
     "xpack.ml.navMenu.logCategorizationLinkText": "Analyse du modèle de log",
     "xpack.ml.navMenu.mlAppNameText": "Machine Learning",
     "xpack.ml.navMenu.modelManagementText": "Gestion des modèles",
-    "xpack.ml.navMenu.nodesOverviewText": "Nœuds",
     "xpack.ml.navMenu.notificationsTabLinkText": "Notifications",
     "xpack.ml.navMenu.overviewTabLinkText": "Aperçu",
     "xpack.ml.navMenu.settingsTabLinkText": "Paramètres",

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

@@ -21212,7 +21212,6 @@
     "xpack.ml.deepLink.filterListsSettings": "フィルターリスト",
     "xpack.ml.deepLink.indexDataVisualizer": "インデックスデータビジュアライザー",
     "xpack.ml.deepLink.modelManagement": "モデル管理",
-    "xpack.ml.deepLink.nodesOverview": "ノード",
     "xpack.ml.deepLink.overview": "概要",
     "xpack.ml.deepLink.settings": "設定",
     "xpack.ml.deepLink.trainedModels": "学習済みモデル",
@@ -21752,8 +21751,6 @@
     "xpack.ml.mlEntitySelector.dfaOptionsLabel": "データフレーム分析",
     "xpack.ml.mlEntitySelector.fetchError": "MLエンティティを取得できませんでした",
     "xpack.ml.mlEntitySelector.trainedModelsLabel": "学習済みモデル",
-    "xpack.ml.modelManagement.nodesOverview.docTitle": "ノード",
-    "xpack.ml.modelManagement.nodesOverviewHeader": "ノード",
     "xpack.ml.modelManagement.trainedModels.docTitle": "学習済みモデル",
     "xpack.ml.modelManagement.trainedModelsHeader": "学習済みモデル",
     "xpack.ml.modelManagementLabel": "モデル管理",
@@ -21864,7 +21861,6 @@
     "xpack.ml.navMenu.logCategorizationLinkText": "ログパターン分析",
     "xpack.ml.navMenu.mlAppNameText": "機械学習",
     "xpack.ml.navMenu.modelManagementText": "モデル管理",
-    "xpack.ml.navMenu.nodesOverviewText": "ノード",
     "xpack.ml.navMenu.notificationsTabLinkText": "通知",
     "xpack.ml.navMenu.overviewTabLinkText": "概要",
     "xpack.ml.navMenu.settingsTabLinkText": "設定",

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

@@ -21242,7 +21242,6 @@
     "xpack.ml.deepLink.filterListsSettings": "筛选列表",
     "xpack.ml.deepLink.indexDataVisualizer": "索引数据可视化工具",
     "xpack.ml.deepLink.modelManagement": "模型管理",
-    "xpack.ml.deepLink.nodesOverview": "节点",
     "xpack.ml.deepLink.overview": "概览",
     "xpack.ml.deepLink.settings": "设置",
     "xpack.ml.deepLink.trainedModels": "已训练模型",
@@ -21782,8 +21781,6 @@
     "xpack.ml.mlEntitySelector.dfaOptionsLabel": "数据帧分析",
     "xpack.ml.mlEntitySelector.fetchError": "无法提取 ML 实体",
     "xpack.ml.mlEntitySelector.trainedModelsLabel": "已训练模型",
-    "xpack.ml.modelManagement.nodesOverview.docTitle": "节点",
-    "xpack.ml.modelManagement.nodesOverviewHeader": "节点",
     "xpack.ml.modelManagement.trainedModels.docTitle": "已训练模型",
     "xpack.ml.modelManagement.trainedModelsHeader": "已训练模型",
     "xpack.ml.modelManagementLabel": "模型管理",
@@ -21894,7 +21891,6 @@
     "xpack.ml.navMenu.logCategorizationLinkText": "日志模式分析",
     "xpack.ml.navMenu.mlAppNameText": "Machine Learning",
     "xpack.ml.navMenu.modelManagementText": "模型管理",
-    "xpack.ml.navMenu.nodesOverviewText": "节点",
     "xpack.ml.navMenu.notificationsTabLinkText": "通知",
     "xpack.ml.navMenu.overviewTabLinkText": "概览",
     "xpack.ml.navMenu.settingsTabLinkText": "设置",