diff --git a/docs/readthedocs/source/doc/PPML/QuickStart/tpc-h_with_sparksql_on_k8s.md b/docs/readthedocs/source/doc/PPML/QuickStart/tpc-h_with_sparksql_on_k8s.md
index 86fbe2ebf0e..51bc3e0d1f4 100644
--- a/docs/readthedocs/source/doc/PPML/QuickStart/tpc-h_with_sparksql_on_k8s.md
+++ b/docs/readthedocs/source/doc/PPML/QuickStart/tpc-h_with_sparksql_on_k8s.md
@@ -28,7 +28,7 @@ Generate input data with size ~100GB (user can adjust data size to need):
 ### Deploy PPML TPC-H on Kubernetes ###
 1.  Pull docker image
 ```
-sudo docker pull intelanalytics/bigdl-ppml-trusted-big-data-ml-python-graphene:0.14.0-SNAPSHOT
+sudo docker pull intelanalytics/bigdl-ppml-trusted-big-data-ml-python-graphene:2.1.0-SNAPSHOT
 ```
 2. Prepare SGX keys, make sure keys and tpch-spark can be accessed on each K8S node
 3. Start a bigdl-ppml enabled Spark K8S client container with configured local IP, key, tpch and kuberconfig path
@@ -38,7 +38,7 @@ export DATA_PATH=/root/zoo-tutorials/tpch-spark
 export KEYS_PATH=/root/keys
 export KUBERCONFIG_PATH=/root/kuberconfig
 export LOCAL_IP=$local_ip
-export DOCKER_IMAGE=intelanalytics/bigdl-ppml-trusted-big-data-ml-python-graphene:0.14.0-SNAPSHOT
+export DOCKER_IMAGE=intelanalytics/bigdl-ppml-trusted-big-data-ml-python-graphene:2.1.0-SNAPSHOT
 sudo docker run -itd \
         --privileged \
         --net=host \