diff --git a/docs/model_serving_framework/GPU_support.md b/docs/model_serving_framework/GPU_support.md
index accda7ed36..e6e41a4faa 100644
--- a/docs/model_serving_framework/GPU_support.md
+++ b/docs/model_serving_framework/GPU_support.md
@@ -11,6 +11,7 @@ Test on AWS EC2 `g5.xlarge`, 64-bit(x86)
 - Ubuntu AMI:  `Deep Learning AMI GPU PyTorch 1.12.1 (Ubuntu 20.04) 20221114`
 - Amazon Linux AMI: `Deep Learning AMI GPU PyTorch 1.12.1 (Amazon Linux 2) 20221114`
 - PyTorch: 1.12.1
+- CUDA: 11.6
 
 ## 1.1 mount nvidia-uvm device
 
@@ -60,6 +61,7 @@ Test on AWS EC2 `inf1.xlarge`,  64-bit(x86)
 - Ubuntu AMI:  `Deep Learning AMI GPU PyTorch 1.12.1 (Ubuntu 20.04) 20221114`
 - Amazon Linux AMI: `Deep Learning AMI GPU PyTorch 1.12.1 (Amazon Linux 2) 20221114`
 - PyTorch: 1.12.1
+- CUDA: 11.6
 
 ## 2.1 Fresh setup script
 
@@ -430,6 +432,32 @@ For the second one run this
 sudo sysctl -w vm.max_map_count=262144
 ```
 
+# 3. DOCKER
+
+Tested on AWS EC2 `g5.xlarge`, 64-bit(x86)
+
+- Amazon Linux AMI: `AWS Deep Learning Base AMI GPU CUDA 11 (Ubuntu 20.04) 20221104`
+- PyTorch: 1.12.1
+- Docker: 20.10.21
+- CUDA: 11.6
+- CUDA Driver: 510.47.03
+- Docker Image: nvidia/cuda:11.6.2-cudnn8-devel-ubuntu20.04
+
+Some example commands.
+
+Start nivida/cuda docker container:
+```
+sudo sysctl -w vm.max_map_count=262144
+docker run -it --runtime=nvidia --gpus all -p 9200:9200 nvidia/cuda:11.6.2-cudnn8-devel-ubuntu20.04 /bin/bash
+```
+Start OpenSearch in nivida/cuda docker container:
+```
+wget https://artifacts.opensearch.org/releases/bundle/opensearch/2.5.0/opensearch-2.5.0-linux-x64.tar.gz
+tar -xvf opensearch-2.5.0-linux-x64.tar.gz
+cd opensearch-2.5.0
+bash opensearch-tar-install.sh
+```
+