feature flag

Author: jan-elastic

distribution/tools/server-cli/src/main/java/org/elasticsearch/server/cli/MachineDependentHeap.java

@@ -11,6 +11,7 @@
 
 import org.elasticsearch.cluster.node.DiscoveryNodeRole;
 import org.elasticsearch.common.settings.Settings;
+import org.elasticsearch.common.util.FeatureFlag;
 import org.elasticsearch.node.NodeRoleSettings;
 
 import java.io.IOException;
@@ -37,6 +38,8 @@ public class MachineDependentHeap {
     protected static final long MAX_HEAP_SIZE = GB * 31; // 31GB
     protected static final long MIN_HEAP_SIZE = 1024 * 1024 * 128; // 128MB
 
+    private static final FeatureFlag NEW_ML_MEMORY_COMPUTATION_FEATURE_FLAG = new FeatureFlag("new_ml_memory_computation");
+
     public MachineDependentHeap() {}
 
     /**
@@ -102,8 +105,12 @@ protected int getHeapSizeMb(Settings nodeSettings, MachineNodeRole role, long av
              * could result in ML processes crashing with OOM errors or repeated autoscaling up and down.
              */
             case ML_ONLY -> {
-                double heapFractionBelow16GB = 0.4 / (1.0 + JvmErgonomics.DIRECT_MEMORY_TO_HEAP_FACTOR);
-                double heapFractionAbove16GB = 0.1 / (1.0 + JvmErgonomics.DIRECT_MEMORY_TO_HEAP_FACTOR);
+                double heapFractionBelow16GB = 0.4;
+                double heapFractionAbove16GB = 0.1;
+                if (NEW_ML_MEMORY_COMPUTATION_FEATURE_FLAG.isEnabled()) {
+                    heapFractionBelow16GB = 0.4 / (1.0 + JvmErgonomics.DIRECT_MEMORY_TO_HEAP_FACTOR);
+                    heapFractionAbove16GB = 0.1 / (1.0 + JvmErgonomics.DIRECT_MEMORY_TO_HEAP_FACTOR);
+                }
                 if (availableMemory <= GB * 16) {
                     yield mb((long) (availableMemory * heapFractionBelow16GB), 4);
                 } else {

distribution/tools/server-cli/src/test/java/org/elasticsearch/server/cli/MachineDependentHeapTests.java

@@ -56,6 +56,7 @@ public void testMasterOnlyOptions() throws Exception {
     }
 
     public void testMlOnlyOptions() throws Exception {
+        System.setProperty("es.kill_new_ml_memory_computation_feature_flag_enabled", "false");
         assertHeapOptions(1, containsInAnyOrder("-Xmx272m", "-Xms272m"), "ml");
         assertHeapOptions(4, containsInAnyOrder("-Xmx1092m", "-Xms1092m"), "ml");
         assertHeapOptions(32, containsInAnyOrder("-Xmx5460m", "-Xms5460m"), "ml");

server/src/main/java/org/elasticsearch/common/util/FeatureFlag.java

@@ -69,6 +69,7 @@ public static FeatureFlag legacyRegisteredFlag(String name) {
         assert name.contains("feature_flag") == false : "Feature flag names may not contain the string 'feature_flag'";
 
         final String propertyName = "es." + name + "_feature_flag_" + suffix;
+        System.out.println("Feature flag system property name: " + propertyName);
         if (build.isSnapshot()) {
             enabled = parseSystemProperty(getSystemProperty, propertyName, true);
             if (enabled == false) {

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

@@ -41,6 +41,7 @@
 import org.elasticsearch.common.settings.SettingsModule;
 import org.elasticsearch.common.unit.ByteSizeValue;
 import org.elasticsearch.common.unit.Processors;
+import org.elasticsearch.common.util.FeatureFlag;
 import org.elasticsearch.common.util.concurrent.EsExecutors;
 import org.elasticsearch.core.TimeValue;
 import org.elasticsearch.env.Environment;
@@ -557,6 +558,8 @@ public class MachineLearning extends Plugin
         License.OperationMode.PLATINUM
     );
 
+    private static final FeatureFlag NEW_ML_MEMORY_COMPUTATION_FEATURE_FLAG = new FeatureFlag("new_ml_memory_computation");
+
     @Override
     public Map<String, Processor.Factory> getProcessors(Processor.Parameters parameters) {
         if (this.enabled == false) {
@@ -846,7 +849,11 @@ public Settings additionalSettings() {
                 Long.toString(OsProbe.getInstance().osStats().getMem().getAdjustedTotal().getBytes())
             );
 
-            addMlNodeAttribute(additionalSettings, jvmSizeAttrName, Long.toString(JvmInfo.jvmInfo().getMem().getTotalMax().getBytes()));
+            long jvmSize = Runtime.getRuntime().maxMemory();
+            if (NEW_ML_MEMORY_COMPUTATION_FEATURE_FLAG.isEnabled()) {
+                jvmSize = JvmInfo.jvmInfo().getMem().getTotalMax().getBytes();
+            }
+            addMlNodeAttribute(additionalSettings, jvmSizeAttrName, Long.toString(jvmSize));
             addMlNodeAttribute(
                 additionalSettings,
                 deprecatedAllocatedProcessorsAttrName,