diff --git a/frontend/server/src/main/java/org/pytorch/serve/wlm/WorkerThread.java b/frontend/server/src/main/java/org/pytorch/serve/wlm/WorkerThread.java
index fd16698d16..793a2c1d1b 100644
--- a/frontend/server/src/main/java/org/pytorch/serve/wlm/WorkerThread.java
+++ b/frontend/server/src/main/java/org/pytorch/serve/wlm/WorkerThread.java
@@ -80,7 +80,6 @@ public class WorkerThread implements Runnable {
     private WorkerLifeCycle lifeCycle;
     private int responseTimeout;
     private long recoveryStartTS; // 0: default value. no recovery needed, in healthy mode
-    private String telemetryPath = System.getenv("SM_TELEMETRY_LOG_REV_2022_12");
 
     public WorkerThread(
             ConfigManager configManager,
@@ -179,9 +178,7 @@ public void run() {
         currentThread.set(thread);
         BaseModelRequest req = null;
         int status = HttpURLConnection.HTTP_INTERNAL_ERROR;
-        if (telemetryPath != null) {
-            loggerTelemetryMetrics.info("Telemetry enabled.");
-        }
+
         try {
             connect();
 
@@ -286,7 +283,7 @@ public void run() {
         } catch (OutOfMemoryError oom) {
             logger.error("Out of memory error when creating workers", oom);
             status = HttpURLConnection.HTTP_ENTITY_TOO_LARGE;
-            if (telemetryPath != null) {
+            if (java.lang.System.getenv("SM_TELEMETRY_LOG") != null) {
                 loggerTelemetryMetrics.info(
                         "ModelServerError.Count:1|#TorchServe:{},{}:-1",
                         ConfigManager.getInstance().getVersion(),
@@ -294,7 +291,7 @@ public void run() {
             }
         } catch (Throwable t) {
             logger.warn("Backend worker thread exception.", t);
-            if (telemetryPath != null) {
+            if (java.lang.System.getenv("SM_TELEMETRY_LOG") != null) {
                 loggerTelemetryMetrics.info(
                         "ModelServerError.Count:1|#TorchServe:{},{}:-1",
                         ConfigManager.getInstance().getVersion(),