[ML] Fix ML usage action when ML sub-features are disabled (elastic#97820)

To support differentiation of serverless product types it's now
possible to disable subsets of ML functionality.

The ML usage action was not updated to reflect this, so still
attempted to call actions to find out about usage of disabled
sub-features. Because that action is designed to never fail,
it actually returned reasonable output in these cases. However,
it generated a lot of log spam with warnings about calling
non-existent actions.

This PR adjusts the logic of the ML usage action to take into
account which sub-features might be disabled, and avoid calling
actions which won't exist in this case.

Author: David Roberts

x-pack/plugin/ml/src/main/java/org/elasticsearch/xpack/ml/MachineLearning.java

@@ -885,8 +885,9 @@ public Collection<Object> createComponents(
         IndicesService indicesService
     ) {
         if (enabled == false) {
-            // special holder for @link(MachineLearningFeatureSetUsage) which needs access to job manager, empty if ML is disabled
-            return List.of(new JobManagerHolder());
+            // Holders for @link(MachineLearningFeatureSetUsage) which needs access to job manager and ML extension,
+            // both empty if ML is disabled
+            return List.of(new JobManagerHolder(), new MachineLearningExtensionHolder());
         }
 
         machineLearningExtension.get().configure(environment.settings());
@@ -1247,7 +1248,8 @@ public Collection<Object> createComponents(
             trainedModelAssignmentService,
             trainedModelAllocationClusterServiceSetOnce.get(),
             deploymentManager.get(),
-            nodeAvailabilityZoneMapper
+            nodeAvailabilityZoneMapper,
+            new MachineLearningExtensionHolder(machineLearningExtension.get())
         );
     }
 

x-pack/plugin/ml/src/main/java/org/elasticsearch/xpack/ml/MachineLearningExtensionHolder.java

@@ -0,0 +1,41 @@
+/*
+ * 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.
+ */
+
+package org.elasticsearch.xpack.ml;
+
+import org.elasticsearch.node.Node;
+
+import java.util.Objects;
+
+/**
+ * Wrapper for the {@link MachineLearningExtension} interface that allows it to be used
+ * given the way {@link Node} does Guice bindings for plugin components.
+ * TODO: remove this class entirely once Guice is removed entirely.
+ */
+public class MachineLearningExtensionHolder {
+
+    private final MachineLearningExtension machineLearningExtension;
+
+    /**
+     * Used by Guice, and in cases where ML is disabled.
+     */
+    public MachineLearningExtensionHolder() {
+        this.machineLearningExtension = null;
+    }
+
+    public MachineLearningExtensionHolder(MachineLearningExtension machineLearningExtension) {
+        this.machineLearningExtension = Objects.requireNonNull(machineLearningExtension);
+    }
+
+    public boolean isEmpty() {
+        return machineLearningExtension == null;
+    }
+
+    public MachineLearningExtension getMachineLearningExtension() {
+        return machineLearningExtension;
+    }
+}

x-pack/plugin/ml/src/main/java/org/elasticsearch/xpack/ml/MachineLearningUsageTransportAction.java

@@ -73,6 +73,7 @@ public class MachineLearningUsageTransportAction extends XPackUsageFeatureTransp
     private final Client client;
     private final XPackLicenseState licenseState;
     private final JobManagerHolder jobManagerHolder;
+    private final MachineLearningExtension machineLearningExtension;
     private final boolean enabled;
 
     @Inject
@@ -85,7 +86,8 @@ public MachineLearningUsageTransportAction(
         Environment environment,
         Client client,
         XPackLicenseState licenseState,
-        JobManagerHolder jobManagerHolder
+        JobManagerHolder jobManagerHolder,
+        MachineLearningExtensionHolder machineLearningExtensionHolder
     ) {
         super(
             XPackUsageFeatureAction.MACHINE_LEARNING.name(),
@@ -98,6 +100,11 @@ public MachineLearningUsageTransportAction(
         this.client = new OriginSettingClient(client, ML_ORIGIN);
         this.licenseState = licenseState;
         this.jobManagerHolder = jobManagerHolder;
+        if (machineLearningExtensionHolder.isEmpty()) {
+            this.machineLearningExtension = new DefaultMachineLearningExtension();
+        } else {
+            this.machineLearningExtension = machineLearningExtensionHolder.getMachineLearningExtension();
+        }
         this.enabled = XPackSettings.MACHINE_LEARNING_ENABLED.get(environment.settings());
     }
 
@@ -187,10 +194,18 @@ protected void masterOperation(
         dataframeAnalyticsStatsRequest.setPageParams(new PageParams(0, 10_000));
         ActionListener<GetDatafeedsStatsAction.Response> datafeedStatsListener = ActionListener.wrap(response -> {
             addDatafeedsUsage(response, datafeedsUsage);
-            client.execute(GetDataFrameAnalyticsStatsAction.INSTANCE, dataframeAnalyticsStatsRequest, dataframeAnalyticsStatsListener);
+            if (machineLearningExtension.isDataFrameAnalyticsEnabled()) {
+                client.execute(GetDataFrameAnalyticsStatsAction.INSTANCE, dataframeAnalyticsStatsRequest, dataframeAnalyticsStatsListener);
+            } else {
+                addInferenceUsage(inferenceUsageListener);
+            }
         }, e -> {
             logger.warn("Failed to get datafeed stats to include in ML usage", e);
-            client.execute(GetDataFrameAnalyticsStatsAction.INSTANCE, dataframeAnalyticsStatsRequest, dataframeAnalyticsStatsListener);
+            if (machineLearningExtension.isDataFrameAnalyticsEnabled()) {
+                client.execute(GetDataFrameAnalyticsStatsAction.INSTANCE, dataframeAnalyticsStatsRequest, dataframeAnalyticsStatsListener);
+            } else {
+                addInferenceUsage(inferenceUsageListener);
+            }
         });
 
         // Step 1. Extract usage from jobs stats and then request stats for all datafeeds
@@ -210,8 +225,14 @@ protected void masterOperation(
         );
 
         // Step 0. Kick off the chain of callbacks by requesting jobs stats
-        GetJobsStatsAction.Request jobStatsRequest = new GetJobsStatsAction.Request(Metadata.ALL);
-        client.execute(GetJobsStatsAction.INSTANCE, jobStatsRequest, jobStatsListener);
+        if (machineLearningExtension.isAnomalyDetectionEnabled()) {
+            GetJobsStatsAction.Request jobStatsRequest = new GetJobsStatsAction.Request(Metadata.ALL);
+            client.execute(GetJobsStatsAction.INSTANCE, jobStatsRequest, jobStatsListener);
+        } else if (machineLearningExtension.isDataFrameAnalyticsEnabled()) {
+            client.execute(GetDataFrameAnalyticsStatsAction.INSTANCE, dataframeAnalyticsStatsRequest, dataframeAnalyticsStatsListener);
+        } else {
+            addInferenceUsage(inferenceUsageListener);
+        }
     }
 
     private void addJobsUsage(GetJobsStatsAction.Response response, List<Job> jobs, Map<String, Object> jobsUsage) {
@@ -361,23 +382,27 @@ private void addDataFrameAnalyticsUsage(GetDataFrameAnalyticsAction.Response res
     }
 
     private void addInferenceUsage(ActionListener<Map<String, Object>> listener) {
-        GetTrainedModelsAction.Request getModelsRequest = new GetTrainedModelsAction.Request(
-            "*",
-            Collections.emptyList(),
-            Collections.emptySet()
-        );
-        getModelsRequest.setPageParams(new PageParams(0, 10_000));
-        client.execute(GetTrainedModelsAction.INSTANCE, getModelsRequest, ActionListener.wrap(getModelsResponse -> {
-            GetTrainedModelsStatsAction.Request getStatsRequest = new GetTrainedModelsStatsAction.Request("*");
-            getStatsRequest.setPageParams(new PageParams(0, 10_000));
-            client.execute(GetTrainedModelsStatsAction.INSTANCE, getStatsRequest, ActionListener.wrap(getStatsResponse -> {
-                Map<String, Object> inferenceUsage = new LinkedHashMap<>();
-                addInferenceIngestUsage(getStatsResponse, inferenceUsage);
-                addTrainedModelStats(getModelsResponse, getStatsResponse, inferenceUsage);
-                addDeploymentStats(getStatsResponse, inferenceUsage);
-                listener.onResponse(inferenceUsage);
+        if (machineLearningExtension.isDataFrameAnalyticsEnabled() || machineLearningExtension.isNlpEnabled()) {
+            GetTrainedModelsAction.Request getModelsRequest = new GetTrainedModelsAction.Request(
+                "*",
+                Collections.emptyList(),
+                Collections.emptySet()
+            );
+            getModelsRequest.setPageParams(new PageParams(0, 10_000));
+            client.execute(GetTrainedModelsAction.INSTANCE, getModelsRequest, ActionListener.wrap(getModelsResponse -> {
+                GetTrainedModelsStatsAction.Request getStatsRequest = new GetTrainedModelsStatsAction.Request("*");
+                getStatsRequest.setPageParams(new PageParams(0, 10_000));
+                client.execute(GetTrainedModelsStatsAction.INSTANCE, getStatsRequest, ActionListener.wrap(getStatsResponse -> {
+                    Map<String, Object> inferenceUsage = new LinkedHashMap<>();
+                    addInferenceIngestUsage(getStatsResponse, inferenceUsage);
+                    addTrainedModelStats(getModelsResponse, getStatsResponse, inferenceUsage);
+                    addDeploymentStats(getStatsResponse, inferenceUsage);
+                    listener.onResponse(inferenceUsage);
+                }, listener::onFailure));
             }, listener::onFailure));
-        }, listener::onFailure));
+        } else {
+            listener.onResponse(Map.of());
+        }
     }
 
     private void addDeploymentStats(GetTrainedModelsStatsAction.Response statsResponse, Map<String, Object> inferenceUsage) {

x-pack/plugin/ml/src/main/java/org/elasticsearch/xpack/ml/process/MlControllerHolder.java

@@ -17,7 +17,7 @@
  */
 public class MlControllerHolder {
 
-    private MlController mlController;
+    private final MlController mlController;
 
     public MlControllerHolder(MlController mlController) {
         this.mlController = Objects.requireNonNull(mlController);