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# Backport This will backport the following commits from `main` to `8.12`: - [[ML] Enable Trained models functional tests (#173517)](https://github.com/elastic/kibana/pull/173517) <!--- Backport version: 8.9.7 --> ### Questions ? Please refer to the [Backport tool documentation](https://github.com/sqren/backport) <!--BACKPORT [{"author":{"name":"Dima Arnautov","email":"dmitrii.arnautov@elastic.co"},"sourceCommit":{"committedDate":"2023-12-22T11:23:50Z","message":"[ML] Enable Trained models functional tests (#173517)\n\n## Summary\r\n\r\nCloses https://github.com/elastic/kibana/issues/168899\r\nCloses https://github.com/elastic/kibana/issues/168492\r\nCloses https://github.com/elastic/kibana/issues/156243\r\n\r\nEnables Trained models functional tests \r\n\r\n### Checklist\r\n\r\n- [x] [Flaky Test\r\nRunner](https://ci-stats.kibana.dev/trigger_flaky_test_runner/1) was\r\nused on any tests changed\r\n(https://buildkite.com/elastic/kibana-flaky-test-suite-runner/builds/4664)","sha":"b5cd85c21fa60c121c30219666a89135c9a95124","branchLabelMapping":{"^v8.13.0$":"main","^v(\\d+).(\\d+).\\d+$":"$1.$2"}},"sourcePullRequest":{"labels":[":ml","test_ui_functional","release_note:skip","Team:ML","v8.12.0","v8.13.0"],"number":173517,"url":"https://github.com/elastic/kibana/pull/173517","mergeCommit":{"message":"[ML] Enable Trained models functional tests (#173517)\n\n## Summary\r\n\r\nCloses https://github.com/elastic/kibana/issues/168899\r\nCloses https://github.com/elastic/kibana/issues/168492\r\nCloses https://github.com/elastic/kibana/issues/156243\r\n\r\nEnables Trained models functional tests \r\n\r\n### Checklist\r\n\r\n- [x] [Flaky Test\r\nRunner](https://ci-stats.kibana.dev/trigger_flaky_test_runner/1) was\r\nused on any tests changed\r\n(https://buildkite.com/elastic/kibana-flaky-test-suite-runner/builds/4664)","sha":"b5cd85c21fa60c121c30219666a89135c9a95124"}},"sourceBranch":"main","suggestedTargetBranches":["8.12"],"targetPullRequestStates":[{"branch":"8.12","label":"v8.12.0","labelRegex":"^v(\\d+).(\\d+).\\d+$","isSourceBranch":false,"state":"NOT_CREATED"},{"branch":"main","label":"v8.13.0","labelRegex":"^v8.13.0$","isSourceBranch":true,"state":"MERGED","url":"https://github.com/elastic/kibana/pull/173517","number":173517,"mergeCommit":{"message":"[ML] Enable Trained models functional tests (#173517)\n\n## Summary\r\n\r\nCloses https://github.com/elastic/kibana/issues/168899\r\nCloses https://github.com/elastic/kibana/issues/168492\r\nCloses https://github.com/elastic/kibana/issues/156243\r\n\r\nEnables Trained models functional tests \r\n\r\n### Checklist\r\n\r\n- [x] [Flaky Test\r\nRunner](https://ci-stats.kibana.dev/trigger_flaky_test_runner/1) was\r\nused on any tests changed\r\n(https://buildkite.com/elastic/kibana-flaky-test-suite-runner/builds/4664)","sha":"b5cd85c21fa60c121c30219666a89135c9a95124"}}]}] BACKPORT--> Co-authored-by: Dima Arnautov <dmitrii.arnautov@elastic.co>
This commit is contained in:
Kibana Machine
GitHub
parent
a2630f0958
commit
193a858a6f
4 changed files with 189 additions and 133 deletions
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@ -92,6 +92,7 @@ export const DeploymentSetup: FC<DeploymentSetupProps> = ({
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id,
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label: id,
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value,
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'data-test-subj': `mlModelsStartDeploymentModalThreadsPerAllocation_${id}`,
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};
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}),
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[maxSingleMlNodeProcessors]
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@ -215,6 +216,7 @@ export const DeploymentSetup: FC<DeploymentSetupProps> = ({
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defaultMessage: 'low',
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}
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),
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'data-test-subj': 'mlModelsStartDeploymentModalLowPriority',
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},
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{
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id: 'normal',
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@ -225,6 +227,7 @@ export const DeploymentSetup: FC<DeploymentSetupProps> = ({
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defaultMessage: 'normal',
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}
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),
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'data-test-subj': 'mlModelsStartDeploymentModalNormalPriority',
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},
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]}
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data-test-subj={'mlModelsStartDeploymentModalPriority'}
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@ -17,8 +17,7 @@ export default function ({ getService }: FtrProviderContext) {
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id: model.name,
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}));
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// FLAKY: https://github.com/elastic/kibana/issues/165084
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describe.skip('trained models', function () {
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describe('trained models', function () {
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// 'Created at' will be different on each run,
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// so we will just assert that the value is in the expected timestamp format.
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const builtInModelData = {
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@ -112,12 +111,6 @@ export default function ({ getService }: FtrProviderContext) {
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await ml.api.cleanMlIndices();
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await ml.api.deleteIndices(modelWithPipelineAndDestIndexExpectedValues.index);
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await ml.api.deleteIngestPipeline(modelWithoutPipelineDataExpectedValues.name, false);
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await ml.api.deleteIngestPipeline(
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modelWithoutPipelineDataExpectedValues.duplicateName,
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false
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);
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// Need to delete index before ingest pipeline, else it will give error
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await ml.api.deleteIngestPipeline(modelWithPipelineAndDestIndex.modelId);
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await ml.testResources.deleteDataViewByTitle(
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@ -188,122 +181,141 @@ export default function ({ getService }: FtrProviderContext) {
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await ml.trainedModelsTable.assertPipelinesTabContent(false);
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});
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it('deploys the trained model with default values', async () => {
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await ml.testExecution.logTestStep('should display the trained model in the table');
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await ml.trainedModelsTable.filterWithSearchString(modelWithoutPipelineData.modelId, 1);
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await ml.testExecution.logTestStep(
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'should show collapsed actions menu for the model in the table'
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);
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await ml.trainedModelsTable.assertModelCollapsedActionsButtonExists(
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modelWithoutPipelineData.modelId,
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true
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);
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await ml.testExecution.logTestStep('should show deploy action for the model in the table');
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await ml.trainedModelsTable.assertModelDeployActionButtonEnabled(
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modelWithoutPipelineData.modelId,
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true
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);
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await ml.testExecution.logTestStep('should open the deploy model flyout');
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await ml.trainedModelsTable.clickDeployAction(modelWithoutPipelineData.modelId);
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await ml.testExecution.logTestStep('should complete the deploy model Details step');
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await ml.deployDFAModelFlyout.completeTrainedModelsInferenceFlyoutDetails({
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name: modelWithoutPipelineDataExpectedValues.name,
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description: modelWithoutPipelineDataExpectedValues.description,
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// If no metadata is provided, the target field will default to empty string
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targetField: '',
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// FLAKY: https://github.com/elastic/kibana/issues/165084
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describe.skip('DFA model deployment', () => {
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after(async () => {
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await ml.api.deleteIngestPipeline(modelWithoutPipelineDataExpectedValues.name, false);
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await ml.api.deleteIngestPipeline(
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modelWithoutPipelineDataExpectedValues.duplicateName,
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false
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);
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});
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await ml.testExecution.logTestStep('should complete the deploy model Pipeline Config step');
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await ml.deployDFAModelFlyout.completeTrainedModelsInferenceFlyoutPipelineConfig({
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inferenceConfig: modelWithoutPipelineDataExpectedValues.inferenceConfig,
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fieldMap: modelWithoutPipelineDataExpectedValues.fieldMap,
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});
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await ml.testExecution.logTestStep(
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'should complete the deploy model pipeline On Failure step'
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);
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await ml.deployDFAModelFlyout.completeTrainedModelsInferenceFlyoutOnFailure(
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getDefaultOnFailureConfiguration()
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);
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await ml.testExecution.logTestStep(
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'should complete the deploy model pipeline Create pipeline step'
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);
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await ml.deployDFAModelFlyout.completeTrainedModelsInferenceFlyoutCreateStep({
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description: modelWithoutPipelineDataExpectedValues.description,
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processors: [
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{
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inference: {
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model_id: modelWithoutPipelineData.modelId,
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ignore_failure: false,
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inference_config: modelWithoutPipelineDataExpectedValues.inferenceConfig,
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on_failure: getDefaultOnFailureConfiguration(),
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},
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},
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],
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});
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});
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it('deploys the trained model with custom values', async () => {
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await ml.testExecution.logTestStep('should display the trained model in the table');
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await ml.trainedModelsTable.filterWithSearchString(modelWithoutPipelineData.modelId, 1);
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await ml.testExecution.logTestStep(
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'should not show collapsed actions menu for the model in the table'
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);
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await ml.trainedModelsTable.assertModelCollapsedActionsButtonExists(
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modelWithoutPipelineData.modelId,
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true
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);
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await ml.testExecution.logTestStep('should show deploy action for the model in the table');
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await ml.trainedModelsTable.assertModelDeployActionButtonExists(
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modelWithoutPipelineData.modelId,
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false
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);
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await ml.testExecution.logTestStep('should open the deploy model flyout');
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await ml.trainedModelsTable.clickDeployAction(modelWithoutPipelineData.modelId);
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await ml.testExecution.logTestStep('should complete the deploy model Details step');
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await ml.deployDFAModelFlyout.completeTrainedModelsInferenceFlyoutDetails(
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{
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name: modelWithoutPipelineDataExpectedValues.duplicateName,
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description: modelWithoutPipelineDataExpectedValues.duplicateDescription,
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targetField: 'myTargetField',
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},
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true
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);
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await ml.testExecution.logTestStep('should complete the deploy model Pipeline Config step');
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await ml.deployDFAModelFlyout.completeTrainedModelsInferenceFlyoutPipelineConfig(
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{
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it.skip('deploys the trained model with default values', async () => {
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await ml.testExecution.logTestStep('should display the trained model in the table');
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await ml.trainedModelsTable.filterWithSearchString(modelWithoutPipelineData.modelId, 1);
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await ml.testExecution.logTestStep(
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'should show collapsed actions menu for the model in the table'
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);
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await ml.trainedModelsTable.assertModelCollapsedActionsButtonExists(
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modelWithoutPipelineData.modelId,
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true
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);
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await ml.testExecution.logTestStep(
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'should show deploy action for the model in the table'
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);
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await ml.trainedModelsTable.assertModelDeployActionButtonEnabled(
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modelWithoutPipelineData.modelId,
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true
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);
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await ml.testExecution.logTestStep('should open the deploy model flyout');
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await ml.trainedModelsTable.clickDeployAction(modelWithoutPipelineData.modelId);
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await ml.testExecution.logTestStep('should complete the deploy model Details step');
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await ml.deployDFAModelFlyout.completeTrainedModelsInferenceFlyoutDetails({
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name: modelWithoutPipelineDataExpectedValues.name,
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description: modelWithoutPipelineDataExpectedValues.description,
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// If no metadata is provided, the target field will default to empty string
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targetField: '',
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});
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await ml.testExecution.logTestStep(
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'should complete the deploy model Pipeline Config step'
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);
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await ml.deployDFAModelFlyout.completeTrainedModelsInferenceFlyoutPipelineConfig({
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inferenceConfig: modelWithoutPipelineDataExpectedValues.inferenceConfig,
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editedInferenceConfig: modelWithoutPipelineDataExpectedValues.editedInferenceConfig,
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fieldMap: modelWithoutPipelineDataExpectedValues.fieldMap,
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editedFieldMap: modelWithoutPipelineDataExpectedValues.editedFieldMap,
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},
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true
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);
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await ml.testExecution.logTestStep(
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'should complete the deploy model pipeline On Failure step'
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);
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await ml.deployDFAModelFlyout.completeTrainedModelsInferenceFlyoutOnFailure(
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getDefaultOnFailureConfiguration(),
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true
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);
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await ml.testExecution.logTestStep(
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'should complete the deploy model pipeline Create pipeline step'
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);
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await ml.deployDFAModelFlyout.completeTrainedModelsInferenceFlyoutCreateStep({
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description: modelWithoutPipelineDataExpectedValues.duplicateDescription,
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processors: [
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{
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inference: {
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field_map: {
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incoming_field: 'old_field',
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});
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await ml.testExecution.logTestStep(
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'should complete the deploy model pipeline On Failure step'
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);
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await ml.deployDFAModelFlyout.completeTrainedModelsInferenceFlyoutOnFailure(
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getDefaultOnFailureConfiguration()
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);
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await ml.testExecution.logTestStep(
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'should complete the deploy model pipeline Create pipeline step'
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);
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await ml.deployDFAModelFlyout.completeTrainedModelsInferenceFlyoutCreateStep({
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description: modelWithoutPipelineDataExpectedValues.description,
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processors: [
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{
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inference: {
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model_id: modelWithoutPipelineData.modelId,
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ignore_failure: false,
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inference_config: modelWithoutPipelineDataExpectedValues.inferenceConfig,
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on_failure: getDefaultOnFailureConfiguration(),
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},
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ignore_failure: true,
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if: "ctx?.network?.name == 'Guest'",
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model_id: modelWithoutPipelineData.modelId,
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inference_config: modelWithoutPipelineDataExpectedValues.inferenceConfigDuplicate,
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tag: 'tag',
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target_field: 'myTargetField',
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},
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],
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});
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});
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it.skip('deploys the trained model with custom values', async () => {
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await ml.testExecution.logTestStep('should display the trained model in the table');
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await ml.trainedModelsTable.filterWithSearchString(modelWithoutPipelineData.modelId, 1);
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await ml.testExecution.logTestStep(
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'should not show collapsed actions menu for the model in the table'
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);
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await ml.trainedModelsTable.assertModelCollapsedActionsButtonExists(
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modelWithoutPipelineData.modelId,
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true
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);
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await ml.testExecution.logTestStep(
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'should show deploy action for the model in the table'
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);
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await ml.trainedModelsTable.assertModelDeployActionButtonExists(
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modelWithoutPipelineData.modelId,
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false
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);
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await ml.testExecution.logTestStep('should open the deploy model flyout');
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await ml.trainedModelsTable.clickDeployAction(modelWithoutPipelineData.modelId);
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await ml.testExecution.logTestStep('should complete the deploy model Details step');
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await ml.deployDFAModelFlyout.completeTrainedModelsInferenceFlyoutDetails(
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{
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name: modelWithoutPipelineDataExpectedValues.duplicateName,
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description: modelWithoutPipelineDataExpectedValues.duplicateDescription,
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targetField: 'myTargetField',
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},
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],
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true
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);
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await ml.testExecution.logTestStep(
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'should complete the deploy model Pipeline Config step'
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);
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await ml.deployDFAModelFlyout.completeTrainedModelsInferenceFlyoutPipelineConfig(
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{
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inferenceConfig: modelWithoutPipelineDataExpectedValues.inferenceConfig,
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editedInferenceConfig: modelWithoutPipelineDataExpectedValues.editedInferenceConfig,
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fieldMap: modelWithoutPipelineDataExpectedValues.fieldMap,
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editedFieldMap: modelWithoutPipelineDataExpectedValues.editedFieldMap,
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},
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true
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);
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await ml.testExecution.logTestStep(
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'should complete the deploy model pipeline On Failure step'
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);
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await ml.deployDFAModelFlyout.completeTrainedModelsInferenceFlyoutOnFailure(
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getDefaultOnFailureConfiguration(),
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true
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);
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await ml.testExecution.logTestStep(
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'should complete the deploy model pipeline Create pipeline step'
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);
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await ml.deployDFAModelFlyout.completeTrainedModelsInferenceFlyoutCreateStep({
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description: modelWithoutPipelineDataExpectedValues.duplicateDescription,
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processors: [
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{
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inference: {
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field_map: {
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incoming_field: 'old_field',
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},
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ignore_failure: true,
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if: "ctx?.network?.name == 'Guest'",
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model_id: modelWithoutPipelineData.modelId,
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inference_config: modelWithoutPipelineDataExpectedValues.inferenceConfigDuplicate,
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tag: 'tag',
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target_field: 'myTargetField',
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},
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},
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],
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});
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});
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});
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@ -418,7 +430,7 @@ export default function ({ getService }: FtrProviderContext) {
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);
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});
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it('navigates to data drift', async () => {
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it.skip('navigates to data drift', async () => {
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await ml.testExecution.logTestStep('should show the model map in the expanded row');
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await ml.trainedModelsTable.ensureRowIsExpanded(modelWithPipelineAndDestIndex.modelId);
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await ml.trainedModelsTable.assertModelsMapTabContent();
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@ -450,8 +462,7 @@ export default function ({ getService }: FtrProviderContext) {
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await ml.navigation.navigateToTrainedModels();
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});
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// FLAKY: https://github.com/elastic/kibana/issues/168899
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describe.skip('with imported models', function () {
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describe('with imported models', function () {
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before(async () => {
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await ml.navigation.navigateToTrainedModels();
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});
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@ -475,8 +486,10 @@ export default function ({ getService }: FtrProviderContext) {
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});
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it(`stops deployment of the imported model ${model.id}`, async () => {
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// Wait for the model to be deployed before stopping it.
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await ml.testExecution.logTestStep('should have a Deployed state');
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await ml.trainedModelsTable.assertModelState(model.id, 'Deployed');
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await ml.trainedModelsTable.stopDeployment(model.id);
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await ml.trainedModelsTable.assertModelDeleteActionButtonEnabled(model.id, true);
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});
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it(`deletes the imported model ${model.id}`, async () => {
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@ -363,15 +363,21 @@ export function MachineLearningCommonUIProvider({
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});
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},
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async selectButtonGroupValue(inputTestSubj: string, value: string) {
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async selectButtonGroupValue(inputTestSubj: string, value: string, valueTestSubj?: string) {
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await retry.tryForTime(5000, async () => {
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// The input element can not be clicked directly.
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// Instead, we need to click the corresponding label
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const fieldSetElement = await testSubjects.find(inputTestSubj);
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let labelElement: WebElementWrapper;
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const labelElement = await fieldSetElement.findByCssSelector(`label[title="${value}"]`);
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await labelElement.click();
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if (valueTestSubj) {
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await testSubjects.click(valueTestSubj);
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labelElement = await testSubjects.find(valueTestSubj);
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} else {
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const fieldSetElement = await testSubjects.find(inputTestSubj);
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labelElement = await fieldSetElement.findByCssSelector(`label[title="${value}"]`);
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await labelElement.click();
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}
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const labelClasses = await labelElement.getAttribute('class');
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expect(labelClasses).to.contain(
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|
|
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|
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@ -52,6 +52,7 @@ export function TrainedModelsTableProvider(
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description: string;
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modelTypes: string[];
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createdAt: string;
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state: string;
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} = {
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id: $tr
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.findTestSubject('mlModelsTableColumnId')
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|
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@ -64,6 +65,11 @@ export function TrainedModelsTableProvider(
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.text()
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.trim(),
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modelTypes,
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state: $tr
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.findTestSubject('mlModelsTableColumnDeploymentState')
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.find('.euiTableCellContent')
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.text()
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.trim(),
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createdAt: $tr
|
||||
.findTestSubject('mlModelsTableColumnCreatedAt')
|
||||
.find('.euiTableCellContent')
|
||||
|
|
@ -193,12 +199,17 @@ export function TrainedModelsTableProvider(
|
|||
|
||||
public async toggleActionsContextMenu(modelId: string, expectOpen = true) {
|
||||
await testSubjects.click(this.rowSelector(modelId, 'euiCollapsedItemActionsButton'));
|
||||
const panelElement = await find.byCssSelector('.euiContextMenuPanel');
|
||||
const isDisplayed = await panelElement.isDisplayed();
|
||||
expect(isDisplayed).to.eql(
|
||||
expectOpen,
|
||||
`Expected the action context menu for '${modelId}' to be ${expectOpen ? 'open' : 'closed'}`
|
||||
);
|
||||
|
||||
await retry.tryForTime(5 * 1000, async () => {
|
||||
const panelElement = await find.byCssSelector('.euiContextMenuPanel');
|
||||
const isDisplayed = await panelElement.isDisplayed();
|
||||
expect(isDisplayed).to.eql(
|
||||
expectOpen,
|
||||
`Expected the action context menu for '${modelId}' to be ${
|
||||
expectOpen ? 'open' : 'closed'
|
||||
}`
|
||||
);
|
||||
});
|
||||
}
|
||||
|
||||
public async assertModelDeleteActionButtonExists(modelId: string, expectedValue: boolean) {
|
||||
|
|
@ -510,14 +521,18 @@ export function TrainedModelsTableProvider(
|
|||
public async setPriority(value: 'low' | 'normal') {
|
||||
await mlCommonUI.selectButtonGroupValue(
|
||||
'mlModelsStartDeploymentModalPriority',
|
||||
value.toString()
|
||||
value.toString(),
|
||||
value === 'normal'
|
||||
? 'mlModelsStartDeploymentModalNormalPriority'
|
||||
: 'mlModelsStartDeploymentModalLowPriority'
|
||||
);
|
||||
}
|
||||
|
||||
public async setThreadsPerAllocation(value: number) {
|
||||
await mlCommonUI.selectButtonGroupValue(
|
||||
'mlModelsStartDeploymentModalThreadsPerAllocation',
|
||||
value.toString()
|
||||
value.toString(),
|
||||
`mlModelsStartDeploymentModalThreadsPerAllocation_${value}`
|
||||
);
|
||||
}
|
||||
|
||||
|
|
@ -540,6 +555,25 @@ export function TrainedModelsTableProvider(
|
|||
`Deployment for "${modelId}" has been started successfully.`
|
||||
);
|
||||
await this.waitForModelsToLoad();
|
||||
|
||||
await retry.tryForTime(
|
||||
5 * 1000,
|
||||
async () => {
|
||||
await this.assertModelState(modelId, 'Deployed');
|
||||
},
|
||||
async () => {
|
||||
await this.refreshModelsTable();
|
||||
}
|
||||
);
|
||||
}
|
||||
|
||||
public async assertModelState(modelId: string, expectedValue = 'Deployed') {
|
||||
const rows = await this.parseModelsTable();
|
||||
const modelRow = rows.find((row) => row.id === modelId);
|
||||
expect(modelRow?.state).to.eql(
|
||||
expectedValue,
|
||||
`Expected trained model row state to be '${expectedValue}' (got '${modelRow?.state!}')`
|
||||
);
|
||||
}
|
||||
|
||||
public async stopDeployment(modelId: string) {
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue