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[ML] track inference model feature usage per node (#79752)
This adds feature usage tracking for deployed inference models. The models are tracked under the existing, inference feature and contain context related to the model ID. I decided to track the feature via the allocation task to keep the logic similar between allocation tasks and licensed persistent tasks. closes: #76452
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68 changes: 68 additions & 0 deletions
68
...java/org/elasticsearch/xpack/ml/inference/deployment/TrainedModelDeploymentTaskTests.java
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| /* | ||
| * 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. | ||
| */ | ||
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| package org.elasticsearch.xpack.ml.inference.deployment; | ||
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| import org.elasticsearch.license.LicensedFeature; | ||
| import org.elasticsearch.license.XPackLicenseState; | ||
| import org.elasticsearch.tasks.TaskId; | ||
| import org.elasticsearch.test.ESTestCase; | ||
| import org.elasticsearch.xpack.core.ml.action.StartTrainedModelDeploymentAction; | ||
| import org.elasticsearch.xpack.core.ml.inference.trainedmodel.PassThroughConfig; | ||
| import org.elasticsearch.xpack.ml.inference.allocation.TrainedModelAllocationNodeService; | ||
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| import java.util.Map; | ||
| import java.util.function.Consumer; | ||
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| import static org.elasticsearch.xpack.core.ml.MlTasks.TRAINED_MODEL_ALLOCATION_TASK_NAME_PREFIX; | ||
| import static org.elasticsearch.xpack.core.ml.MlTasks.TRAINED_MODEL_ALLOCATION_TASK_TYPE; | ||
| import static org.mockito.Mockito.mock; | ||
| import static org.mockito.Mockito.times; | ||
| import static org.mockito.Mockito.verify; | ||
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| public class TrainedModelDeploymentTaskTests extends ESTestCase { | ||
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| void assertTrackingComplete(Consumer<TrainedModelDeploymentTask> method, String modelId) { | ||
| XPackLicenseState licenseState = mock(XPackLicenseState.class); | ||
| LicensedFeature.Persistent feature = mock(LicensedFeature.Persistent.class); | ||
| TrainedModelDeploymentTask task = new TrainedModelDeploymentTask( | ||
| 0, | ||
| TRAINED_MODEL_ALLOCATION_TASK_TYPE, | ||
| TRAINED_MODEL_ALLOCATION_TASK_NAME_PREFIX + modelId, | ||
| TaskId.EMPTY_TASK_ID, | ||
| Map.of(), | ||
| new StartTrainedModelDeploymentAction.TaskParams( | ||
| modelId, | ||
| randomLongBetween(1, Long.MAX_VALUE), | ||
| randomInt(5), | ||
| randomInt(5), | ||
| randomInt(5) | ||
| ), | ||
| mock(TrainedModelAllocationNodeService.class), | ||
| licenseState, | ||
| feature | ||
| ); | ||
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| task.init(new PassThroughConfig(null, null, null)); | ||
| verify(feature, times(1)).startTracking(licenseState, "model-" + modelId); | ||
| method.accept(task); | ||
| verify(feature, times(1)).stopTracking(licenseState, "model-" + modelId); | ||
| } | ||
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| public void testOnStopWithoutNotification() { | ||
| assertTrackingComplete(t -> t.stopWithoutNotification("foo"), randomAlphaOfLength(10)); | ||
| } | ||
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| public void testOnStop() { | ||
| assertTrackingComplete(t -> t.stop("foo"), randomAlphaOfLength(10)); | ||
| } | ||
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| public void testCancelled() { | ||
| assertTrackingComplete(TrainedModelDeploymentTask::onCancelled, randomAlphaOfLength(10)); | ||
| } | ||
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| } |