[ML] Support force stop deployment

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

@@ -151,10 +151,13 @@ export function trainedModelsApiProvider(httpService: HttpService) {
       });
     },
 
-    stopModelAllocation(modelId: string) {
+    stopModelAllocation(modelId: string, options: { force: boolean } = { force: false }) {
+      const force = options?.force;
+
       return httpService.http<{ acknowledge: boolean }>({
         path: `${apiBasePath}/trained_models/${modelId}/deployment/_stop`,
         method: 'POST',
+        query: { force },
       });
     },
   };

x-pack/plugins/ml/public/application/trained_models/models_management/force_stop_dialog.tsx

@@ -0,0 +1,89 @@
+/*
+ * 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 { EuiConfirmModal } from '@elastic/eui';
+import { FormattedMessage } from '@kbn/i18n/react';
+import type { OverlayStart } from 'kibana/public';
+import type { ModelItem } from './models_list';
+import { toMountPoint } from '../../../../../../../src/plugins/kibana_react/public';
+
+interface ForceStopModelConfirmDialogProps {
+  model: ModelItem;
+  onCancel: () => void;
+  onConfirm: () => void;
+}
+
+export const ForceStopModelConfirmDialog: FC<ForceStopModelConfirmDialogProps> = ({
+  model,
+  onConfirm,
+  onCancel,
+}) => {
+  return (
+    <EuiConfirmModal
+      title={
+        <FormattedMessage
+          id="xpack.ml.trainedModels.modelsList.forceStopDialog.title"
+          defaultMessage="Force stop model {modelId}?"
+          values={{ modelId: model.model_id }}
+        />
+      }
+      onCancel={onCancel}
+      onConfirm={onConfirm}
+      cancelButtonText={
+        <FormattedMessage
+          id="xpack.ml.trainedModels.modelsList.forceStopDialog.cancelText"
+          defaultMessage="Cancel"
+        />
+      }
+      confirmButtonText={
+        <FormattedMessage
+          id="xpack.ml.trainedModels.modelsList.forceStopDialog.confirmText"
+          defaultMessage="Stop"
+        />
+      }
+      buttonColor="danger"
+    >
+      <FormattedMessage
+        id="xpack.ml.trainedModels.modelsList.forceStopDialog.pipelinesWarning"
+        defaultMessage="Selected model has associated pipelines: "
+      />
+      <ul>
+        {Object.keys(model.pipelines!)
+          .sort()
+          .map((pipelineName) => {
+            return <li key={pipelineName}>{pipelineName}</li>;
+          })}
+      </ul>
+    </EuiConfirmModal>
+  );
+};
+
+export const getUserConfirmationProvider =
+  (overlays: OverlayStart) => async (forceStopModel: ModelItem) => {
+    return new Promise(async (resolve, reject) => {
+      try {
+        const modalSession = overlays.openModal(
+          toMountPoint(
+            <ForceStopModelConfirmDialog
+              model={forceStopModel}
+              onCancel={() => {
+                modalSession.close();
+                resolve(false);
+              }}
+              onConfirm={() => {
+                modalSession.close();
+                resolve(true);
+              }}
+            />
+          )
+        );
+      } catch (e) {
+        resolve(false);
+      }
+    });
+  };

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

@@ -54,6 +54,7 @@ import { useFieldFormatter } from '../../contexts/kibana/use_field_formatter';
 import { FIELD_FORMAT_IDS } from '../../../../../../../src/plugins/field_formats/common';
 import { useRefresh } from '../../routing/use_refresh';
 import { DEPLOYMENT_STATE } from '../../../../common/constants/trained_models';
+import { getUserConfirmationProvider } from './force_stop_dialog';
 
 type Stats = Omit<TrainedModelStat, 'model_id'>;
 
@@ -81,6 +82,7 @@ export const ModelsList: FC = () => {
   const {
     services: {
       application: { navigateToUrl, capabilities },
+      overlays,
     },
   } = useMlKibana();
   const urlLocator = useMlLocator()!;
@@ -111,6 +113,8 @@ export const ModelsList: FC = () => {
     {}
   );
 
+  const getUserConfirmation = useMemo(() => getUserConfirmationProvider(overlays), []);
+
   const navigateToPath = useNavigateToPath();
 
   const isBuiltInModel = useCallback(
@@ -454,13 +458,21 @@ export const ModelsList: FC = () => {
       available: (item) => item.model_type === 'pytorch',
       enabled: (item) =>
         !isLoading &&
-        !isPopulatedObject(item.pipelines) &&
         isPopulatedObject(item.stats?.deployment_stats) &&
         item.stats?.deployment_stats?.state !== DEPLOYMENT_STATE.STOPPING,
       onClick: async (item) => {
+        const requireForceStop = isPopulatedObject(item.pipelines);
+
+        if (requireForceStop) {
+          const hasUserApproved = await getUserConfirmation(item);
+          if (!hasUserApproved) return;
+        }
+
         try {
           setIsLoading(true);
-          await trainedModelsApiService.stopModelAllocation(item.model_id);
+          await trainedModelsApiService.stopModelAllocation(item.model_id, {
+            force: requireForceStop,
+          });
           displaySuccessToast(
             i18n.translate('xpack.ml.trainedModels.modelsList.stopSuccess', {
               defaultMessage: 'Deployment for "{modelId}" has been stopped successfully.',

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

@@ -16,6 +16,7 @@ import { modelsProvider } from '../models/data_frame_analytics';
 import { TrainedModelConfigResponse } from '../../common/types/trained_models';
 import { memoryOverviewServiceProvider } from '../models/memory_overview';
 import { mlLog } from '../lib/log';
+import { forceQuerySchema } from './schemas/anomaly_detectors_schema';
 
 export function trainedModelsRoutes({ router, routeGuard }: RouteInitialization) {
   /**
@@ -262,6 +263,7 @@ export function trainedModelsRoutes({ router, routeGuard }: RouteInitialization)
       path: '/api/ml/trained_models/{modelId}/deployment/_stop',
       validate: {
         params: modelIdSchema,
+        query: forceQuerySchema,
       },
       options: {
         tags: ['access:ml:canGetDataFrameAnalytics'],
@@ -272,6 +274,7 @@ export function trainedModelsRoutes({ router, routeGuard }: RouteInitialization)
         const { modelId } = request.params;
         const { body } = await mlClient.stopTrainedModelDeployment({
           model_id: modelId,
+          force: request.query.force ?? false,
         });
         return response.ok({
           body,