diff --git a/how-to-use-azureml/deploy-to-cloud/README.md b/how-to-use-azureml/deploy-to-cloud/README.md
index ece25d2c..8dba4c6e 100644
--- a/how-to-use-azureml/deploy-to-cloud/README.md
+++ b/how-to-use-azureml/deploy-to-cloud/README.md
@@ -1,5 +1,4 @@
 # Model Deployment with Azure ML service
-[![Build Status](https://aidemos.visualstudio.com/azmlcli/_apis/build/status/Azure.MachineLearningNotebooks?branchName=cli-ga)](https://aidemos.visualstudio.com/azmlcli/_build/latest?definitionId=87&branchName=cli-ga)
 
 You can use Azure Machine Learning to package, debug, validate and deploy inference containers to a variety of compute targets. This process is known as "MLOps" (ML operationalization).
 For more information please check out this article: https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-deploy-and-where
@@ -20,6 +19,7 @@ az ml model deploy -n acicicd -f model.json --ic inferenceConfig.yml --dc deploy
 ```
 
 Here is an [Azure DevOps Pipelines model deployment example](./azure-pipelines-model-deploy.yml)
+[![Build Status](https://aidemos.visualstudio.com/azmlcli/_apis/build/status/Azure.MachineLearningNotebooks?branchName=cli-ga)](https://aidemos.visualstudio.com/azmlcli/_build/latest?definitionId=87&branchName=cli-ga)
 
 ### Deploy from a notebook
 - Notebook example: [model-register-and-deploy](./model-register-and-deploy.ipynb).