diff --git a/.github/workflows/build_on_schedule.yml b/.github/workflows/build_on_schedule.yml
index ea1f4879c..32b518ac5 100644
--- a/.github/workflows/build_on_schedule.yml
+++ b/.github/workflows/build_on_schedule.yml
@@ -16,30 +16,65 @@ jobs:
       options: --gpus all --rm -v /data/scratch/cifar-10:/data/scratch/cifar-10
     timeout-minutes: 40
     steps:
+      - name: Check GPU Availability # ensure all GPUs have enough memory
+        id: check-avai
+        run: |
+          avai=true
+          for i in $(seq 0 7);
+          do
+            gpu_used=$(nvidia-smi -i $i --query-gpu=memory.used --format=csv,noheader,nounits)
+            [ "$gpu_used" -le "10000" ] && avai=false
+          done
+
+          echo "GPU is available: $avai"
+          echo "avai=$avai" >> $GITHUB_OUTPUT
+
       - uses: actions/checkout@v2
+        if: steps.check-avai.outputs.avai == 'true'
         with:
           repository: hpcaitech/TensorNVMe
           ssh-key: ${{ secrets.SSH_KEY_FOR_CI }}
           path: TensorNVMe
+
       - name: Install tensornvme
+        if: steps.check-avai.outputs.avai == 'true'
         run: |
           cd TensorNVMe
           conda install cmake
           pip install -r requirements.txt
           pip install -v .
+
       - uses: actions/checkout@v2
+        if: steps.check-avai.outputs.avai == 'true'
         with:
           ssh-key: ${{ secrets.SSH_KEY_FOR_CI }}
+
       - name: Install Colossal-AI
+        if: steps.check-avai.outputs.avai == 'true'
         run: |
           [ ! -z "$(ls -A /github/home/cuda_ext_cache/)" ] && cp -r /github/home/cuda_ext_cache/* /__w/ColossalAI/ColossalAI/
           CUDA_EXT=1 pip install -v -e .
           cp -r /__w/ColossalAI/ColossalAI/build /github/home/cuda_ext_cache/
           pip install -r requirements/requirements-test.txt
+
       - name: Unit Testing
+        if: steps.check-avai.outputs.avai == 'true'
         run: |
-          gpu_used=$(nvidia-smi -i 0 --query-gpu=memory.used --format=csv,noheader,nounits)
-          [ "$gpu_used" -le "10000" ] && PYTHONPATH=$PWD pytest tests
+          PYTHONPATH=$PWD pytest tests
         env:
           DATA: /data/scratch/cifar-10
           LD_LIBRARY_PATH: /github/home/.tensornvme/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64
+
+      - name: Notify Lark
+        id: message-preparation
+        if: ${{ failure() }}
+        run: |
+          url=$SERVER_URL/$REPO/actions/runs/$RUN_ID
+          msg="Scheduled Build and Test failed on 8 GPUs, please visit $url for details"
+          echo $msg
+          python .github/workflows/scripts/send_message_to_lark.py -m "$msg" -u $WEBHOOK_URL
+        env:
+          SERVER_URL: ${{github.server_url }}
+          REPO: ${{ github.repository }}
+          RUN_ID: ${{ github.run_id }}
+          WEBHOOK_URL: ${{ secrets.LARK_NOTIFICATION_WEBHOOK_URL }}
diff --git a/.github/workflows/scripts/send_message_to_lark.py b/.github/workflows/scripts/send_message_to_lark.py
new file mode 100644
index 000000000..a113327a7
--- /dev/null
+++ b/.github/workflows/scripts/send_message_to_lark.py
@@ -0,0 +1,20 @@
+import argparse
+
+import requests
+
+
+def parse_args():
+    parser = argparse.ArgumentParser()
+    parser.add_argument('-m', '--message', type=str)
+    parser.add_argument('-u', '--url', type=str)
+    return parser.parse_args()
+
+
+def send_message_to_lark(message, webhook_url):
+    data = {"msg_type": "text", "content": {"text": message}}
+    requests.post(webhook_url, json=data)
+
+
+if __name__ == '__main__':
+    args = parse_args()
+    send_message_to_lark(args.message, args.url)
diff --git a/test.sh b/test.sh
new file mode 100644
index 000000000..8dcecc6dd
--- /dev/null
+++ b/test.sh
@@ -0,0 +1,6 @@
+avai=true
+for i in $(seq 0 7);
+do
+  gpu_used=$(nvidia-smi -i $i --query-gpu=memory.used --format=csv,noheader,nounits)
+  [ "$gpu_used" -le "10000" ] && avai=false
+done