[8.8] [Enterprise Search] Add Production Model Name to Allowed List f…

…or ELSER API Endpoints (#156020) (#156062)

# Backport

This will backport the following commits from `main` to `8.8`:
- [[Enterprise Search] Add Production Model Name to Allowed List for
ELSER API Endpoints
(#156020)](#156020)

<!--- Backport version: 8.9.7 -->

### Questions ?
Please refer to the [Backport tool
documentation](https://github.com/sqren/backport)

<!--BACKPORT [{"author":{"name":"Mark J.
Hoy","email":"[email protected]"},"sourceCommit":{"committedDate":"2023-04-27T17:22:30Z","message":"[Enterprise
Search] Add Production Model Name to Allowed List for ELSER API
Endpoints (#156020)\n\n## Summary\r\n\r\nSmall PR to add the production
model name to the `acceptableModelNames`\r\nlist that the Enteprise
Search 1-Click deploy API endpoints use to check\r\nto ensure we have a
known, valid model name.\r\n\r\n### Checklist\r\n- [ ] [Unit or
functional\r\ntests](https://www.elastic.co/guide/en/kibana/master/development-tests.html)\r\nwere
updated or added to match the most common
scenarios","sha":"fbe3aa36b31c0e6499d03b6afb14d4d628d05312","branchLabelMapping":{"^v8.9.0$":"main","^v(\\d+).(\\d+).\\d+$":"$1.$2"}},"sourcePullRequest":{"labels":["release_note:feature","Team:EnterpriseSearch","v8.8.0","v8.9.0"],"number":156020,"url":"https://github.com/elastic/kibana/pull/156020","mergeCommit":{"message":"[Enterprise
Search] Add Production Model Name to Allowed List for ELSER API
Endpoints (#156020)\n\n## Summary\r\n\r\nSmall PR to add the production
model name to the `acceptableModelNames`\r\nlist that the Enteprise
Search 1-Click deploy API endpoints use to check\r\nto ensure we have a
known, valid model name.\r\n\r\n### Checklist\r\n- [ ] [Unit or
functional\r\ntests](https://www.elastic.co/guide/en/kibana/master/development-tests.html)\r\nwere
updated or added to match the most common
scenarios","sha":"fbe3aa36b31c0e6499d03b6afb14d4d628d05312"}},"sourceBranch":"main","suggestedTargetBranches":["8.8"],"targetPullRequestStates":[{"branch":"8.8","label":"v8.8.0","labelRegex":"^v(\\d+).(\\d+).\\d+$","isSourceBranch":false,"state":"NOT_CREATED"},{"branch":"main","label":"v8.9.0","labelRegex":"^v8.9.0$","isSourceBranch":true,"state":"MERGED","url":"https://github.com/elastic/kibana/pull/156020","number":156020,"mergeCommit":{"message":"[Enterprise
Search] Add Production Model Name to Allowed List for ELSER API
Endpoints (#156020)\n\n## Summary\r\n\r\nSmall PR to add the production
model name to the `acceptableModelNames`\r\nlist that the Enteprise
Search 1-Click deploy API endpoints use to check\r\nto ensure we have a
known, valid model name.\r\n\r\n### Checklist\r\n- [ ] [Unit or
functional\r\ntests](https://www.elastic.co/guide/en/kibana/master/development-tests.html)\r\nwere
updated or added to match the most common
scenarios","sha":"fbe3aa36b31c0e6499d03b6afb14d4d628d05312"}}]}]
BACKPORT-->

Co-authored-by: Mark J. Hoy <[email protected]>

x-pack/plugins/enterprise_search/server/lib/ml/ml_model_deployment_common.ts

@@ -11,7 +11,7 @@ import {
   isResourceNotFoundException,
 } from '../../utils/identify_exceptions';
 
-export const acceptableModelNames = ['.elser_model_1_SNAPSHOT'];
+export const acceptableModelNames = ['.elser_model_1', '.elser_model_1_SNAPSHOT'];
 
 export function isNotFoundExceptionError(error: unknown): boolean {
   return (

x-pack/plugins/enterprise_search/server/lib/ml/start_ml_model_deployment.test.ts

@@ -15,7 +15,8 @@ import * as mockGetStatus from './get_ml_model_deployment_status';
 import { startMlModelDeployment } from './start_ml_model_deployment';
 
 describe('startMlModelDeployment', () => {
-  const knownModelName = '.elser_model_1_SNAPSHOT';
+  const productionModelName = '.elser_model_1';
+  const snapshotModelName = '.elser_model_1_SNAPSHOT';
   const mockTrainedModelsProvider = {
     getTrainedModels: jest.fn(),
     getTrainedModelsStats: jest.fn(),
@@ -27,7 +28,7 @@ describe('startMlModelDeployment', () => {
   });
 
   it('should error when there is no trained model provider', () => {
-    expect(() => startMlModelDeployment(knownModelName, undefined)).rejects.toThrowError(
+    expect(() => startMlModelDeployment(productionModelName, undefined)).rejects.toThrowError(
       'Machine Learning is not enabled'
     );
   });
@@ -49,15 +50,34 @@ describe('startMlModelDeployment', () => {
     jest.spyOn(mockGetStatus, 'getMlModelDeploymentStatus').mockReturnValueOnce(
       Promise.resolve({
         deploymentState: MlModelDeploymentState.Starting,
-        modelId: knownModelName,
+        modelId: productionModelName,
         nodeAllocationCount: 0,
         startTime: 123456,
         targetAllocationCount: 3,
       })
     );
 
     const response = await startMlModelDeployment(
-      knownModelName,
+      productionModelName,
+      mockTrainedModelsProvider as unknown as MlTrainedModels
+    );
+
+    expect(response.deploymentState).toEqual(MlModelDeploymentState.Starting);
+  });
+
+  it('should return the deployment state if not "downloaded" for snapshot model', async () => {
+    jest.spyOn(mockGetStatus, 'getMlModelDeploymentStatus').mockReturnValueOnce(
+      Promise.resolve({
+        deploymentState: MlModelDeploymentState.Starting,
+        modelId: snapshotModelName,
+        nodeAllocationCount: 0,
+        startTime: 123456,
+        targetAllocationCount: 3,
+      })
+    );
+
+    const response = await startMlModelDeployment(
+      snapshotModelName,
       mockTrainedModelsProvider as unknown as MlTrainedModels
     );
 
@@ -70,7 +90,7 @@ describe('startMlModelDeployment', () => {
       .mockReturnValueOnce(
         Promise.resolve({
           deploymentState: MlModelDeploymentState.Downloaded,
-          modelId: knownModelName,
+          modelId: productionModelName,
           nodeAllocationCount: 0,
           startTime: 123456,
           targetAllocationCount: 3,
@@ -79,7 +99,7 @@ describe('startMlModelDeployment', () => {
       .mockReturnValueOnce(
         Promise.resolve({
           deploymentState: MlModelDeploymentState.Starting,
-          modelId: knownModelName,
+          modelId: productionModelName,
           nodeAllocationCount: 0,
           startTime: 123456,
           targetAllocationCount: 3,
@@ -88,7 +108,7 @@ describe('startMlModelDeployment', () => {
     mockTrainedModelsProvider.startTrainedModelDeployment.mockImplementation(async () => {});
 
     const response = await startMlModelDeployment(
-      knownModelName,
+      productionModelName,
       mockTrainedModelsProvider as unknown as MlTrainedModels
     );
     expect(response.deploymentState).toEqual(MlModelDeploymentState.Starting);