diff --git a/frontend/server/src/main/java/org/pytorch/serve/ensemble/DagExecutor.java b/frontend/server/src/main/java/org/pytorch/serve/ensemble/DagExecutor.java
index 5dcb72c52e..cc7da3ba55 100644
--- a/frontend/server/src/main/java/org/pytorch/serve/ensemble/DagExecutor.java
+++ b/frontend/server/src/main/java/org/pytorch/serve/ensemble/DagExecutor.java
@@ -1,5 +1,6 @@
 package org.pytorch.serve.ensemble;
 
+import com.google.common.util.concurrent.ThreadFactoryBuilder;
 import java.util.ArrayList;
 import java.util.HashSet;
 import java.util.List;
@@ -14,6 +15,7 @@
 import java.util.concurrent.ExecutorService;
 import java.util.concurrent.Executors;
 import java.util.concurrent.Future;
+import java.util.concurrent.ThreadFactory;
 import java.util.concurrent.TimeUnit;
 import java.util.concurrent.TimeoutException;
 import org.pytorch.serve.archive.model.ModelNotFoundException;
@@ -41,8 +43,11 @@ public DagExecutor(Dag dag) {
     public ArrayList<NodeOutput> execute(RequestInput input, ArrayList<String> topoSortedList) {
 
         CompletionService<NodeOutput> executorCompletionService = null;
+        ExecutorService executorService = null;
         if (topoSortedList == null) {
-            ExecutorService executorService = Executors.newFixedThreadPool(4);
+            ThreadFactory namedThreadFactory =
+                    new ThreadFactoryBuilder().setNameFormat("wf-execute-thread-%d").build();
+            executorService = Executors.newFixedThreadPool(4, namedThreadFactory);
             executorCompletionService = new ExecutorCompletionService<>(executorService);
         }
 
@@ -140,6 +145,9 @@ public ArrayList<NodeOutput> execute(RequestInput input, ArrayList<String> topoS
                 }
             }
         }
+        if (executorService != null) {
+            executorService.shutdown();
+        }
 
         return leafOutputs;
     }
@@ -150,7 +158,7 @@ private NodeOutput invokeModel(
                     InterruptedException {
         try {
 
-            logger.error(String.format("Invoking -  %s for attempt %d", nodeName, retryAttempt));
+            logger.info(String.format("Invoking -  %s for attempt %d", nodeName, retryAttempt));
             CompletableFuture<byte[]> respFuture = new CompletableFuture<>();
             RestJob job = ApiUtils.addRESTInferenceJob(null, workflowModel.getName(), null, input);
             job.setResponsePromise(respFuture);
diff --git a/frontend/server/src/main/java/org/pytorch/serve/workflow/WorkflowManager.java b/frontend/server/src/main/java/org/pytorch/serve/workflow/WorkflowManager.java
index a391d54b33..116656537e 100644
--- a/frontend/server/src/main/java/org/pytorch/serve/workflow/WorkflowManager.java
+++ b/frontend/server/src/main/java/org/pytorch/serve/workflow/WorkflowManager.java
@@ -1,5 +1,6 @@
 package org.pytorch.serve.workflow;
 
+import com.google.common.util.concurrent.ThreadFactoryBuilder;
 import com.google.gson.JsonObject;
 import com.google.gson.JsonParser;
 import io.netty.channel.ChannelHandlerContext;
@@ -23,6 +24,7 @@
 import java.util.concurrent.ExecutorService;
 import java.util.concurrent.Executors;
 import java.util.concurrent.Future;
+import java.util.concurrent.ThreadFactory;
 import org.pytorch.serve.archive.DownloadArchiveException;
 import org.pytorch.serve.archive.model.ModelNotFoundException;
 import org.pytorch.serve.archive.model.ModelVersionNotFoundException;
@@ -51,8 +53,11 @@
 public final class WorkflowManager {
     private static final Logger logger = LoggerFactory.getLogger(WorkflowManager.class);
 
+    private final ThreadFactory namedThreadFactory =
+            new ThreadFactoryBuilder().setNameFormat("wf-manager-thread-%d").build();
     private final ExecutorService inferenceExecutorService =
-            Executors.newFixedThreadPool(Runtime.getRuntime().availableProcessors());
+            Executors.newFixedThreadPool(
+                    Runtime.getRuntime().availableProcessors(), namedThreadFactory);
 
     private static WorkflowManager workflowManager;
     private final ConfigManager configManager;