diff --git a/README.md b/README.md
index 72f1506a..4f52ad3d 100644
--- a/README.md
+++ b/README.md
@@ -1,3 +1,94 @@
+### Author: Praneet Singh Solanki
+
+# DevOps For AI
+
+[DevOps for AI template](https://azuredevopsdemogenerator.azurewebsites.net/?name=azure%20machine%20learning) will help you to understand how to build the Continuous Integration and Continuous Delivery pipeline for a ML/AI project. We will be using the Azure DevOps Project for build and release pipelines along with Azure ML services for ML/AI model management and operationalization. 
+
+This template contains code and pipeline definition for a machine learning project demonstrating how to automate the end to end ML/AI project. The build pipelines include DevOps tasks for data sanity test, unit test, model training on different compute targets, model version management, model evaluation/model selection, model deployment as realtime web service, staged deployment to QA/prod, integration testing and functional testing.
+
+## Prerequisite
+- Active Azure subscription
+- Minimum contributor access to Azure subscription
+
+## Getting Started:
+
+### Import the DevOps for AI solution template from Azure DevOps Demo Generator: [Click here](https://azuredevopsdemogenerator.azurewebsites.net/?name=azure%20machine%20learning)
+
+Skip above step if already done.
+
+Once the template is imported for personal Azure DevOps account using DevOps demo generator, you need to follow below steps to get the pipeline running:
+
+### Update Pipeline Config:
+
+#### Build Pipeline
+1. Go to the **Pipelines -> Builds** on the newly created project and click **Edit** on top right
+![EditPipeline1](/docs/images/EditPipeline1.png)
+2. Click on **Create or Get Workspace** task, select the Azure subscription where you want to deploy and run the solution, and click **Authorize**
+![EditPipeline2](/docs/images/EditPipeline2.png)
+3. Click all other tasks below it and select the same subscription (no need to authorize again)
+4. Once the tasks are updated with subscription, click on **Save & queue** and select **Save**
+![EditPipeline3](/docs/images/EditPipeline3.png)
+
+#### Release Pipeline
+1. Go to the **Pipelines -> Releases** and click **Edit** on top  
+![EditPipeline4](/docs/images/EditPipeline4.png)
+2. Click on **1 job, 4 tasks** to open the tasks in **QA stage**
+![EditPipeline5](/docs/images/EditPipeline5.png)
+3. Update the subscription details in two tasks 
+![EditPipeline6](/docs/images/EditPipeline6.png)
+4. Click on **Tasks** on the top to switch to the Prod stage, update the subscription details for the two tasks in prod
+![EditPipeline7](/docs/images/EditPipeline7.png)
+5. Once you fix all the missing subscription, the **Save** is no longer grayed, click on save to save the changes in release pepeline
+![EditPipeline8](/docs/images/EditPipeline8.png)
+
+### Update Repo config:
+1. Go to the **Repos** on the newly created Azure DevOps project
+2. Open the config file [/aml_config/config.json](/aml_config/config.json) and edit it
+3. Put your Azure subscription ID in place of <>
+4. Change resource group and AML workspace name if you want
+5. Put the location where you want to deploy your Azure ML service workspace
+6. Save the changes and commit these changes to master branch 
+7. The commit will trigger the build pipeline to run deploying AML end to end solution
+8. Go to **Pipelines -> Builds** to see the pipeline run
+
+## Steps Performed in the Build Pipeline:
+
+1. Prepare the python environment
+2. Get or Create the workspace
+3. Submit Training job on the remote DSVM / Local Python Env
+4. Register model to workspace
+5. Create Docker Image for Scoring Webservice
+6. Copy and Publish the Artifacts to Release Pipeline
+
+## Steps Performed in the Release Pipeline
+In Release pipeline we deploy the image created from the build pipeline to Azure Container Instance and Azure Kubernetes Services
+
+### Deploy on ACI - QA Stage
+1. Prepare the python environment
+2. Create ACI and Deploy webservice image created in Build Pipeline
+3. Test the scoring image
+
+### Deploy on AKS - PreProd/Prod Stage
+1. Prepare the python environment
+2. Deploy on AKS
+    - Create AKS and create a new webservice on AKS with the scoring docker image
+
+        OR
+
+    - Get the existing AKS and update the webservice with new image created in Build Pipeline
+3. Test the scoring image
+
+### Repo Details
+
+You can find the details of the code ans scripts in the repository [here](/docs/code_description.md)
+
+### References
+
+- [Azure Machine Learning(Azure ML) Service Workspace](https://docs.microsoft.com/en-us/azure/machine-learning/service/overview-what-is-azure-ml)
+
+- [Azure ML Samples](https://docs.microsoft.com/en-us/azure/machine-learning/service/samples-notebooks)
+- [Azure ML Python SDK Quickstart](https://docs.microsoft.com/en-us/azure/machine-learning/service/quickstart-create-workspace-with-python)
+- [Azure DevOps](https://docs.microsoft.com/en-us/azure/devops/?view=vsts)
 
 # Contributing
 
diff --git a/aml_config/conda_dependencies.yml b/aml_config/conda_dependencies.yml
new file mode 100644
index 00000000..48505e28
--- /dev/null
+++ b/aml_config/conda_dependencies.yml
@@ -0,0 +1,50 @@
+# Conda environment specification. The dependencies defined in this file will
+
+# be automatically provisioned for managed runs. These include runs against
+
+# the localdocker, remotedocker, and cluster compute targets.
+
+
+# Note that this file is NOT used to automatically manage dependencies for the
+
+# local compute target. To provision these dependencies locally, run:
+
+# conda env update --file conda_dependencies.yml
+
+
+# Details about the Conda environment file format:
+
+# https://conda.io/docs/using/envs.html#create-environment-file-by-hand
+
+
+# For managing Spark packages and configuration, see spark_dependencies.yml.
+
+
+# Version of this configuration file's structure and semantics in AzureML.
+
+# This directive is stored in a comment to preserve the Conda file structure.
+
+# [AzureMlVersion] = 2
+
+
+name: project_environment
+dependencies:
+  # The python interpreter version.
+
+  # Currently Azure ML Workbench only supports 3.5.2 and later.
+
+- python=3.6.2
+  # Required by azureml-defaults, installed separately through Conda to
+
+  # get a prebuilt version and not require build tools for the install.
+
+- psutil=5.3
+
+- pip:
+    # Required packages for AzureML execution, history, and data preparation.
+  - azureml-sdk[notebooks]
+  - pynacl==1.2.1
+  - scipy==1.0.0
+  - scikit-learn==0.19.1
+  - pandas==0.23.1
+  - numpy==1.14.5
\ No newline at end of file
diff --git a/aml_config/config.json b/aml_config/config.json
new file mode 100644
index 00000000..0d14385b
--- /dev/null
+++ b/aml_config/config.json
@@ -0,0 +1,6 @@
+{
+    "subscription_id": "<>",
+    "resource_group": "DevOps_AzureML_Demo",
+    "workspace_name": "AzureML_Demo_ws",
+    "location": "southcentralus"
+}
\ No newline at end of file
diff --git a/aml_config/security_config.json b/aml_config/security_config.json
new file mode 100644
index 00000000..abb27988
--- /dev/null
+++ b/aml_config/security_config.json
@@ -0,0 +1,9 @@
+{
+    "sp_user" : "<>",
+    "sp_password" : "<>",
+    "sp_tenant_id" : "<>",
+    "remote_vm_name" : "<>",
+    "remote_vm_username" : "<>",
+    "remote_vm_password" : "<>",
+    "remote_vm_ip" : "<>"
+}
\ No newline at end of file
diff --git a/aml_service/00-WorkSpace.py b/aml_service/00-WorkSpace.py
new file mode 100644
index 00000000..89716a4e
--- /dev/null
+++ b/aml_service/00-WorkSpace.py
@@ -0,0 +1,59 @@
+"""
+Copyright (C) Microsoft Corporation. All rights reserved.​
+ ​
+Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual,
+royalty-free right to use, copy, and modify the software code provided by us
+("Software Code"). You may not sublicense the Software Code or any use of it
+(except to your affiliates and to vendors to perform work on your behalf)
+through distribution, network access, service agreement, lease, rental, or
+otherwise. This license does not purport to express any claim of ownership over
+data you may have shared with Microsoft in the creation of the Software Code.
+Unless applicable law gives you more rights, Microsoft reserves all other
+rights not expressly granted herein, whether by implication, estoppel or
+otherwise. ​
+ ​
+THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS
+OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
+MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR
+BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER
+IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE
+POSSIBILITY OF SUCH DAMAGE.
+"""
+from azureml.core import Workspace
+import os, json
+import azureml.core
+
+print("SDK Version:", azureml.core.VERSION)
+# print('current dir is ' +os.curdir)
+with open("aml_config/config.json") as f:
+    config = json.load(f)
+
+workspace_name = config["workspace_name"]
+resource_group = config["resource_group"]
+subscription_id = config["subscription_id"]
+location = config["location"]
+# location = 'southcentralus'
+try:
+    ws = Workspace.get(
+        name=workspace_name,
+        subscription_id=subscription_id,
+        resource_group=resource_group,
+    )
+
+except:
+    # this call might take a minute or two.
+    print("Creating new workspace")
+    ws = Workspace.create(
+        name=workspace_name,
+        subscription_id=subscription_id,
+        resource_group=resource_group,
+        # create_resource_group=True,
+        location=location,
+    )
+
+# print Workspace details
+print(ws.name, ws.resource_group, ws.location, ws.subscription_id, sep="\n")
diff --git a/aml_service/01-Experiment.py b/aml_service/01-Experiment.py
new file mode 100644
index 00000000..f95398da
--- /dev/null
+++ b/aml_service/01-Experiment.py
@@ -0,0 +1,41 @@
+"""
+Copyright (C) Microsoft Corporation. All rights reserved.​
+ ​
+Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual,
+royalty-free right to use, copy, and modify the software code provided by us
+("Software Code"). You may not sublicense the Software Code or any use of it
+(except to your affiliates and to vendors to perform work on your behalf)
+through distribution, network access, service agreement, lease, rental, or
+otherwise. This license does not purport to express any claim of ownership over
+data you may have shared with Microsoft in the creation of the Software Code.
+Unless applicable law gives you more rights, Microsoft reserves all other
+rights not expressly granted herein, whether by implication, estoppel or
+otherwise. ​
+ ​
+THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS
+OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
+MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR
+BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER
+IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE
+POSSIBILITY OF SUCH DAMAGE.
+"""
+import os
+from azureml.core import Experiment
+from azureml.core import Workspace
+
+
+def getExperiment():
+    ws = Workspace.from_config()
+    script_folder = "."
+    experiment_name = "devops-ai-demo"
+    exp = Experiment(workspace=ws, name=experiment_name)
+    print(exp.name, exp.workspace.name, sep="\n")
+    return exp
+
+
+if __name__ == "__main__":
+    exp = getExperiment()
diff --git a/aml_service/02-AttachTrainingVM.py b/aml_service/02-AttachTrainingVM.py
new file mode 100644
index 00000000..17946a8e
--- /dev/null
+++ b/aml_service/02-AttachTrainingVM.py
@@ -0,0 +1,76 @@
+"""
+Copyright (C) Microsoft Corporation. All rights reserved.​
+ ​
+Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual,
+royalty-free right to use, copy, and modify the software code provided by us
+("Software Code"). You may not sublicense the Software Code or any use of it
+(except to your affiliates and to vendors to perform work on your behalf)
+through distribution, network access, service agreement, lease, rental, or
+otherwise. This license does not purport to express any claim of ownership over
+data you may have shared with Microsoft in the creation of the Software Code.
+Unless applicable law gives you more rights, Microsoft reserves all other
+rights not expressly granted herein, whether by implication, estoppel or
+otherwise. ​
+ ​
+THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS
+OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
+MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR
+BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER
+IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE
+POSSIBILITY OF SUCH DAMAGE.
+"""
+
+from azureml.core import Workspace
+from azureml.core import Run
+from azureml.core import Experiment
+from azureml.core.conda_dependencies import CondaDependencies
+from azureml.core.runconfig import RunConfiguration
+import os, json
+from azureml.core.compute import RemoteCompute
+from azureml.core.compute import DsvmCompute
+from azureml.core.compute_target import ComputeTargetException
+
+
+# Get workspace
+ws = Workspace.from_config()
+
+# Read the New VM Config
+with open("aml_config/security_config.json") as f:
+    config = json.load(f)
+
+remote_vm_name = config["remote_vm_name"]
+remote_vm_username = config["remote_vm_username"]
+remote_vm_password = config["remote_vm_password"]
+remote_vm_ip = config["remote_vm_ip"]
+
+try:
+    dsvm_compute = RemoteCompute.attach(
+        ws,
+        name=remote_vm_name,
+        username=remote_vm_username,
+        address=remote_vm_ip,
+        ssh_port=22,
+        password=remote_vm_password,
+    )
+    dsvm_compute.wait_for_completion(show_output=True)
+
+except Exception as e:
+    print("Caught = {}".format(e.message))
+    print("Compute config already attached.")
+
+
+## Create VM if not available
+# compute_target_name = remote_vm_name
+
+# try:
+#     dsvm_compute = DsvmCompute(workspace=ws, name=compute_target_name)
+#     print('found existing:', dsvm_compute.name)
+# except ComputeTargetException:
+#     print('creating new.')
+#     dsvm_config = DsvmCompute.provisioning_configuration(vm_size="Standard_D2_v2")
+#     dsvm_compute = DsvmCompute.create(ws, name=compute_target_name, provisioning_configuration=dsvm_config)
+#     dsvm_compute.wait_for_completion(show_output=True)
diff --git a/aml_service/10-TrainOnLocal.py b/aml_service/10-TrainOnLocal.py
new file mode 100644
index 00000000..807d1843
--- /dev/null
+++ b/aml_service/10-TrainOnLocal.py
@@ -0,0 +1,70 @@
+"""
+Copyright (C) Microsoft Corporation. All rights reserved.​
+ ​
+Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual,
+royalty-free right to use, copy, and modify the software code provided by us
+("Software Code"). You may not sublicense the Software Code or any use of it
+(except to your affiliates and to vendors to perform work on your behalf)
+through distribution, network access, service agreement, lease, rental, or
+otherwise. This license does not purport to express any claim of ownership over
+data you may have shared with Microsoft in the creation of the Software Code.
+Unless applicable law gives you more rights, Microsoft reserves all other
+rights not expressly granted herein, whether by implication, estoppel or
+otherwise. ​
+ ​
+THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS
+OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
+MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR
+BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER
+IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE
+POSSIBILITY OF SUCH DAMAGE.
+"""
+
+from azureml.core.runconfig import RunConfiguration
+from azureml.core import Workspace
+from azureml.core import Experiment
+from azureml.core import ScriptRunConfig
+import json
+
+# Get workspace
+ws = Workspace.from_config()
+
+# Attach Experiment
+experiment_name = "devops-ai-demo"
+exp = Experiment(workspace=ws, name=experiment_name)
+print(exp.name, exp.workspace.name, sep="\n")
+
+# Editing a run configuration property on-fly.
+run_config_user_managed = RunConfiguration()
+run_config_user_managed.environment.python.user_managed_dependencies = True
+
+print("Submitting an experiment.")
+src = ScriptRunConfig(
+    source_directory="./code",
+    script="training/train.py",
+    run_config=run_config_user_managed,
+)
+run = exp.submit(src)
+
+# Shows output of the run on stdout.
+run.wait_for_completion(show_output=True, wait_post_processing=True)
+
+# Raise exception if run fails
+if run.get_status() == "Failed":
+    raise Exception(
+        "Training on local failed with following run status: {} and logs: \n {}".format(
+            run.get_status(), run.get_details_with_logs()
+        )
+    )
+
+# Writing the run id to /aml_config/run_id.json
+
+run_id = {}
+run_id["run_id"] = run.id
+run_id["experiment_name"] = run.experiment.name
+with open("aml_config/run_id.json", "w") as outfile:
+    json.dump(run_id, outfile)
diff --git a/aml_service/11-TrainOnLocalEnv.py b/aml_service/11-TrainOnLocalEnv.py
new file mode 100644
index 00000000..9e2a9a3d
--- /dev/null
+++ b/aml_service/11-TrainOnLocalEnv.py
@@ -0,0 +1,78 @@
+"""
+Copyright (C) Microsoft Corporation. All rights reserved.​
+ ​
+Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual,
+royalty-free right to use, copy, and modify the software code provided by us
+("Software Code"). You may not sublicense the Software Code or any use of it
+(except to your affiliates and to vendors to perform work on your behalf)
+through distribution, network access, service agreement, lease, rental, or
+otherwise. This license does not purport to express any claim of ownership over
+data you may have shared with Microsoft in the creation of the Software Code.
+Unless applicable law gives you more rights, Microsoft reserves all other
+rights not expressly granted herein, whether by implication, estoppel or
+otherwise. ​
+ ​
+THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS
+OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
+MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR
+BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER
+IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE
+POSSIBILITY OF SUCH DAMAGE.
+"""
+## Create a new Conda environment on local and train the model
+## System-managed environment
+
+from azureml.core.conda_dependencies import CondaDependencies
+from azureml.core.runconfig import RunConfiguration
+from azureml.core import Workspace
+from azureml.core import Experiment
+from azureml.core import ScriptRunConfig
+
+# Get workspace
+ws = Workspace.from_config()
+
+# Attach Experiment
+experiment_name = "devops-ai-demo"
+exp = Experiment(workspace=ws, name=experiment_name)
+print(exp.name, exp.workspace.name, sep="\n")
+
+# Editing a run configuration property on-fly.
+run_config_system_managed = RunConfiguration()
+# Use a new conda environment that is to be created from the conda_dependencies.yml file
+run_config_system_managed.environment.python.user_managed_dependencies = False
+# Automatically create the conda environment before the run
+run_config_system_managed.prepare_environment = True
+
+# # add scikit-learn to the conda_dependencies.yml file
+# Specify conda dependencies with scikit-learn
+# run_config_system_managed.environment.python.conda_dependencies = CondaDependencies.create(conda_packages=['scikit-learn'])
+
+print("Submitting an experiment to new conda virtual env")
+src = ScriptRunConfig(
+    source_directory="./code",
+    script="training/train.py",
+    run_config=run_config_user_managed,
+)
+run = exp.submit(src)
+
+# Shows output of the run on stdout.
+run.wait_for_completion(show_output=True, wait_post_processing=True)
+
+# Raise exception if run fails
+if run.get_status() == "Failed":
+    raise Exception(
+        "Training on local env failed with following run status: {} and logs: \n {}".format(
+            run.get_status(), run.get_details_with_logs()
+        )
+    )
+
+# Writing the run id to /aml_config/run_id.json
+run_id = {}
+run_id["run_id"] = run.id
+run_id["experiment_name"] = run.experiment.name
+with open("aml_config/run_id.json", "w") as outfile:
+    json.dump(run_id, outfile)
diff --git a/aml_service/12-TrainOnVM.py b/aml_service/12-TrainOnVM.py
new file mode 100644
index 00000000..019bf4e3
--- /dev/null
+++ b/aml_service/12-TrainOnVM.py
@@ -0,0 +1,78 @@
+"""
+Copyright (C) Microsoft Corporation. All rights reserved.​
+ ​
+Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual,
+royalty-free right to use, copy, and modify the software code provided by us
+("Software Code"). You may not sublicense the Software Code or any use of it
+(except to your affiliates and to vendors to perform work on your behalf)
+through distribution, network access, service agreement, lease, rental, or
+otherwise. This license does not purport to express any claim of ownership over
+data you may have shared with Microsoft in the creation of the Software Code.
+Unless applicable law gives you more rights, Microsoft reserves all other
+rights not expressly granted herein, whether by implication, estoppel or
+otherwise. ​
+ ​
+THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS
+OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
+MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR
+BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER
+IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE
+POSSIBILITY OF SUCH DAMAGE.
+"""
+import os, json
+from azureml.core import Workspace
+from azureml.core import Experiment
+from azureml.core.compute import RemoteCompute
+from azureml.core.runconfig import RunConfiguration
+from azureml.core import ScriptRunConfig
+import azureml.core
+
+
+# Get workspace
+ws = Workspace.from_config()
+
+# Read the New VM Config
+with open("aml_config/security_config.json") as f:
+    config = json.load(f)
+remote_vm_name = config["remote_vm_name"]
+
+
+# Attach Experiment
+experiment_name = "devops-ai-demo"
+exp = Experiment(workspace=ws, name=experiment_name)
+print(exp.name, exp.workspace.name, sep="\n")
+
+run_config = RunConfiguration()
+run_config.target = remote_vm_name
+
+# replace with your path to the python interpreter in the remote VM found earlier
+run_config.environment.python.interpreter_path = "/anaconda/envs/myenv/bin/python"
+run_config.environment.python.user_managed_dependencies = True
+
+
+src = ScriptRunConfig(
+    source_directory="./code", script="training/train.py", run_config=run_config
+)
+run = exp.submit(src)
+
+# Shows output of the run on stdout.
+run.wait_for_completion(show_output=True, wait_post_processing=True)
+
+# Raise exception if run fails
+if run.get_status() == "Failed":
+    raise Exception(
+        "Training on local env failed with following run status: {} and logs: \n {}".format(
+            run.get_status(), run.get_details_with_logs()
+        )
+    )
+
+# Writing the run id to /aml_config/run_id.json
+run_id = {}
+run_id["run_id"] = run.id
+run_id["experiment_name"] = run.experiment.name
+with open("aml_config/run_id.json", "w") as outfile:
+    json.dump(run_id, outfile)
diff --git a/aml_service/15-EvaluateModel.py b/aml_service/15-EvaluateModel.py
new file mode 100644
index 00000000..2dd9d99d
--- /dev/null
+++ b/aml_service/15-EvaluateModel.py
@@ -0,0 +1,91 @@
+"""
+Copyright (C) Microsoft Corporation. All rights reserved.​
+ ​
+Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual,
+royalty-free right to use, copy, and modify the software code provided by us
+("Software Code"). You may not sublicense the Software Code or any use of it
+(except to your affiliates and to vendors to perform work on your behalf)
+through distribution, network access, service agreement, lease, rental, or
+otherwise. This license does not purport to express any claim of ownership over
+data you may have shared with Microsoft in the creation of the Software Code.
+Unless applicable law gives you more rights, Microsoft reserves all other
+rights not expressly granted herein, whether by implication, estoppel or
+otherwise. ​
+ ​
+THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS
+OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
+MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR
+BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER
+IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE
+POSSIBILITY OF SUCH DAMAGE.
+"""
+import os, json
+from azureml.core import Workspace
+from azureml.core import Experiment
+from azureml.core.model import Model
+import azureml.core
+from azureml.core import Run
+
+
+# Get workspace
+ws = Workspace.from_config()
+
+# Paramaterize the matrics on which the models should be compared
+
+# Add golden data set on which all the model performance can be evaluated
+
+# Get the latest run_id
+with open("aml_config/run_id.json") as f:
+    config = json.load(f)
+
+new_model_run_id = config["run_id"]
+experiment_name = config["experiment_name"]
+exp = Experiment(workspace=ws, name=experiment_name)
+
+
+try:
+    # Get most recently registered model, we assume that is the model in production. Download this model and compare it with the recently trained model by running test with same data set.
+    model_list = Model.list(ws)
+    production_model = next(
+        filter(
+            lambda x: x.created_time == max(model.created_time for model in model_list),
+            model_list,
+        )
+    )
+    production_model_run_id = production_model.tags.get("run_id")
+    run_list = exp.get_runs()
+    # production_model_run = next(filter(lambda x: x.id == production_model_run_id, run_list))
+
+    # Get the run history for both production model and newly trained model and compare mse
+    production_model_run = Run(exp, run_id=production_model_run_id)
+    new_model_run = Run(exp, run_id=new_model_run_id)
+
+    production_model_mse = production_model_run.get_metrics().get("mse")
+    new_model_mse = new_model_run.get_metrics().get("mse")
+    print(
+        "Current Production model mse: {}, New trained model mse: {}".format(
+            production_model_mse, new_model_mse
+        )
+    )
+
+    promote_new_model = False
+    if new_model_mse < production_model_mse:
+        promote_new_model = True
+        print("New trained model performs better, thus it will be registered")
+except:
+    promote_new_model = True
+    print("This is the first model to be trained, thus nothing to evaluate for now")
+
+run_id = {}
+run_id["run_id"] = ""
+# Writing the run id to /aml_config/run_id.json
+if promote_new_model:
+    run_id["run_id"] = new_model_run_id
+
+run_id["experiment_name"] = experiment_name
+with open("aml_config/run_id.json", "w") as outfile:
+    json.dump(run_id, outfile)
diff --git a/aml_service/20-RegisterModel.py b/aml_service/20-RegisterModel.py
new file mode 100644
index 00000000..47870ae0
--- /dev/null
+++ b/aml_service/20-RegisterModel.py
@@ -0,0 +1,89 @@
+"""
+Copyright (C) Microsoft Corporation. All rights reserved.​
+ ​
+Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual,
+royalty-free right to use, copy, and modify the software code provided by us
+("Software Code"). You may not sublicense the Software Code or any use of it
+(except to your affiliates and to vendors to perform work on your behalf)
+through distribution, network access, service agreement, lease, rental, or
+otherwise. This license does not purport to express any claim of ownership over
+data you may have shared with Microsoft in the creation of the Software Code.
+Unless applicable law gives you more rights, Microsoft reserves all other
+rights not expressly granted herein, whether by implication, estoppel or
+otherwise. ​
+ ​
+THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS
+OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
+MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR
+BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER
+IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE
+POSSIBILITY OF SUCH DAMAGE.
+"""
+import os, json, sys
+from azureml.core import Workspace
+from azureml.core import Run
+from azureml.core import Experiment
+from azureml.core.model import Model
+
+from azureml.core.runconfig import RunConfiguration
+
+# Get workspace
+ws = Workspace.from_config()
+
+# Get the latest evaluation result
+try:
+    with open("aml_config/run_id.json") as f:
+        config = json.load(f)
+    if not config["run_id"]:
+        raise Exception("No new model to register as production model perform better")
+except:
+    print("No new model to register as production model perform better")
+    # raise Exception('No new model to register as production model perform better')
+    sys.exit(0)
+
+run_id = config["run_id"]
+experiment_name = config["experiment_name"]
+exp = Experiment(workspace=ws, name=experiment_name)
+
+run = Run(experiment=exp, run_id=run_id)
+names = run.get_file_names
+names()
+print("Run ID for last run: {}".format(run_id))
+model_local_dir = "model"
+os.makedirs(model_local_dir, exist_ok=True)
+
+# Download Model to Project root directory
+model_name = "sklearn_regression_model.pkl"
+run.download_file(
+    name="./outputs/" + model_name, output_file_path="./model/" + model_name
+)
+print("Downloaded model {} to Project root directory".format(model_name))
+os.chdir("./model")
+model = Model.register(
+    model_path=model_name,  # this points to a local file
+    model_name=model_name,  # this is the name the model is registered as
+    tags={"area": "diabetes", "type": "regression", "run_id": run_id},
+    description="Regression model for diabetes dataset",
+    workspace=ws,
+)
+os.chdir("..")
+print(
+    "Model registered: {} \nModel Description: {} \nModel Version: {}".format(
+        model.name, model.description, model.version
+    )
+)
+
+# Remove the evaluate.json as we no longer need it
+# os.remove("aml_config/evaluate.json")
+
+# Writing the registered model details to /aml_config/model.json
+model_json = {}
+model_json["model_name"] = model.name
+model_json["model_version"] = model.version
+model_json["run_id"] = run_id
+with open("aml_config/model.json", "w") as outfile:
+    json.dump(model_json, outfile)
diff --git a/aml_service/30-CreateScoringImage.py b/aml_service/30-CreateScoringImage.py
new file mode 100644
index 00000000..c52b3de1
--- /dev/null
+++ b/aml_service/30-CreateScoringImage.py
@@ -0,0 +1,96 @@
+"""
+Copyright (C) Microsoft Corporation. All rights reserved.​
+ ​
+Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual,
+royalty-free right to use, copy, and modify the software code provided by us
+("Software Code"). You may not sublicense the Software Code or any use of it
+(except to your affiliates and to vendors to perform work on your behalf)
+through distribution, network access, service agreement, lease, rental, or
+otherwise. This license does not purport to express any claim of ownership over
+data you may have shared with Microsoft in the creation of the Software Code.
+Unless applicable law gives you more rights, Microsoft reserves all other
+rights not expressly granted herein, whether by implication, estoppel or
+otherwise. ​
+ ​
+THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS
+OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
+MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR
+BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER
+IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE
+POSSIBILITY OF SUCH DAMAGE.
+"""
+import os, json, sys
+from azureml.core import Workspace
+from azureml.core.image import ContainerImage, Image
+from azureml.core.model import Model
+
+# Get workspace
+ws = Workspace.from_config()
+
+# Get the latest model details
+
+try:
+    with open("aml_config/model.json") as f:
+        config = json.load(f)
+except:
+    print("No new model to register thus no need to create new scoring image")
+    # raise Exception('No new model to register as production model perform better')
+    sys.exit(0)
+
+model_name = config["model_name"]
+model_version = config["model_version"]
+
+
+model_list = Model.list(workspace=ws)
+model, = (m for m in model_list if m.version == model_version and m.name == model_name)
+print(
+    "Model picked: {} \nModel Description: {} \nModel Version: {}".format(
+        model.name, model.description, model.version
+    )
+)
+
+os.chdir("./code/scoring")
+image_name = "diabetes-model-score"
+
+image_config = ContainerImage.image_configuration(
+    execution_script="score.py",
+    runtime="python-slim",
+    conda_file="conda_dependencies.yml",
+    description="Image with ridge regression model",
+    tags={"area": "diabetes", "type": "regression"},
+)
+
+image = Image.create(
+    name=image_name, models=[model], image_config=image_config, workspace=ws
+)
+
+image.wait_for_creation(show_output=True)
+os.chdir("../..")
+
+if image.creation_state != "Succeeded":
+    raise Exception("Image creation status: {image.creation_state}")
+
+print(
+    "{}(v.{} [{}]) stored at {} with build log {}".format(
+        image.name,
+        image.version,
+        image.creation_state,
+        image.image_location,
+        image.image_build_log_uri,
+    )
+)
+
+# Writing the image details to /aml_config/image.json
+image_json = {}
+image_json["image_name"] = image.name
+image_json["image_version"] = image.version
+image_json["image_location"] = image.image_location
+with open("aml_config/image.json", "w") as outfile:
+    json.dump(image_json, outfile)
+
+
+# How to fix the schema for a model, like if we have multiple models expecting different schema,
diff --git a/aml_service/50-deployOnAci.py b/aml_service/50-deployOnAci.py
new file mode 100644
index 00000000..34c5b83f
--- /dev/null
+++ b/aml_service/50-deployOnAci.py
@@ -0,0 +1,89 @@
+"""
+Copyright (C) Microsoft Corporation. All rights reserved.​
+ ​
+Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual,
+royalty-free right to use, copy, and modify the software code provided by us
+("Software Code"). You may not sublicense the Software Code or any use of it
+(except to your affiliates and to vendors to perform work on your behalf)
+through distribution, network access, service agreement, lease, rental, or
+otherwise. This license does not purport to express any claim of ownership over
+data you may have shared with Microsoft in the creation of the Software Code.
+Unless applicable law gives you more rights, Microsoft reserves all other
+rights not expressly granted herein, whether by implication, estoppel or
+otherwise. ​
+ ​
+THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS
+OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
+MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR
+BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER
+IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE
+POSSIBILITY OF SUCH DAMAGE.
+"""
+import os, json, datetime, sys
+from operator import attrgetter
+from azureml.core import Workspace
+from azureml.core.model import Model
+from azureml.core.image import Image
+from azureml.core.webservice import Webservice
+from azureml.core.webservice import AciWebservice
+
+# Get workspace
+ws = Workspace.from_config()
+
+
+# Get the Image to deploy details
+try:
+    with open("aml_config/image.json") as f:
+        config = json.load(f)
+except:
+    print("No new model, thus no deployment on ACI")
+    # raise Exception('No new model to register as production model perform better')
+    sys.exit(0)
+
+
+image_name = config["image_name"]
+image_version = config["image_version"]
+
+images = Image.list(workspace=ws)
+image, = (m for m in images if m.version == image_version and m.name == image_name)
+print(
+    "From image.json, Image used to deploy webservice on ACI: {}\nImage Version: {}\nImage Location = {}".format(
+        image.name, image.version, image.image_location
+    )
+)
+
+# image = max(images, key=attrgetter('version'))
+# print('From Max Version, Image used to deploy webservice on ACI: {}\nImage Version: {}\nImage Location = {}'.format(image.name, image.version, image.image_location))
+
+
+aciconfig = AciWebservice.deploy_configuration(
+    cpu_cores=1,
+    memory_gb=1,
+    tags={"area": "diabetes", "type": "regression"},
+    description="A sample description",
+)
+
+aci_service_name = "aciwebservice" + datetime.datetime.now().strftime("%m%d%H")
+
+service = Webservice.deploy_from_image(
+    deployment_config=aciconfig, image=image, name=aci_service_name, workspace=ws
+)
+
+service.wait_for_deployment()
+print(
+    "Deployed ACI Webservice: {} \nWebservice Uri: {}".format(
+        service.name, service.scoring_uri
+    )
+)
+
+# service=Webservice(name ='aciws0622', workspace =ws)
+# Writing the ACI details to /aml_config/aci_webservice.json
+aci_webservice = {}
+aci_webservice["aci_name"] = service.name
+aci_webservice["aci_url"] = service.scoring_uri
+with open("aml_config/aci_webservice.json", "w") as outfile:
+    json.dump(aci_webservice, outfile)
diff --git a/aml_service/51-deployOnAks.py b/aml_service/51-deployOnAks.py
new file mode 100644
index 00000000..66ec8848
--- /dev/null
+++ b/aml_service/51-deployOnAks.py
@@ -0,0 +1,122 @@
+"""
+Copyright (C) Microsoft Corporation. All rights reserved.​
+ ​
+Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual,
+royalty-free right to use, copy, and modify the software code provided by us
+("Software Code"). You may not sublicense the Software Code or any use of it
+(except to your affiliates and to vendors to perform work on your behalf)
+through distribution, network access, service agreement, lease, rental, or
+otherwise. This license does not purport to express any claim of ownership over
+data you may have shared with Microsoft in the creation of the Software Code.
+Unless applicable law gives you more rights, Microsoft reserves all other
+rights not expressly granted herein, whether by implication, estoppel or
+otherwise. ​
+ ​
+THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS
+OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
+MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR
+BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER
+IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE
+POSSIBILITY OF SUCH DAMAGE.
+"""
+import os, json, datetime, sys
+from operator import attrgetter
+from azureml.core import Workspace
+from azureml.core.model import Model
+from azureml.core.image import Image
+from azureml.core.compute import AksCompute, ComputeTarget
+from azureml.core.webservice import Webservice, AksWebservice
+
+# Get workspace
+ws = Workspace.from_config()
+
+# Get the Image to deploy details
+try:
+    with open("aml_config/image.json") as f:
+        config = json.load(f)
+except:
+    print("No new model, thus no deployment on ACI")
+    # raise Exception('No new model to register as production model perform better')
+    sys.exit(0)
+
+image_name = config["image_name"]
+image_version = config["image_version"]
+
+images = Image.list(workspace=ws)
+image, = (m for m in images if m.version == image_version and m.name == image_name)
+print(
+    "From image.json, Image used to deploy webservice on ACI: {}\nImage Version: {}\nImage Location = {}".format(
+        image.name, image.version, image.image_location
+    )
+)
+
+# image = max(images, key=attrgetter('version'))
+# print('From Max Version, Image used to deploy webservice on ACI: {}\nImage Version: {}\nImage Location = {}'.format(image.name, image.version, image.image_location))
+
+# Check if AKS already Available
+try:
+    with open("aml_config/aks_webservice.json") as f:
+        config = json.load(f)
+    aks_name = config["aks_name"]
+    aks_service_name = config["aks_service_name"]
+    compute_list = ws.compute_targets()
+    aks_target, = (c for c in compute_list if c.name == aks_name)
+    service = Webservice(name=aks_service_name, workspace=ws)
+    print(
+        "Updating AKS service {} with image: {}".format(
+            aks_service_name, image.image_location
+        )
+    )
+    service.update(image=image)
+except:
+    aks_name = "aks" + datetime.datetime.now().strftime("%m%d%H")
+    aks_service_name = "akswebservice" + datetime.datetime.now().strftime("%m%d%H")
+    prov_config = AksCompute.provisioning_configuration(
+        agent_count=6, vm_size="Standard_F2", location="eastus"
+    )
+    print(
+        "No AKS found in aks_webservice.json. Creating new Aks: {} and AKS Webservice: {}".format(
+            aks_name, aks_service_name
+        )
+    )
+    # Create the cluster
+    aks_target = ComputeTarget.create(
+        workspace=ws, name=aks_name, provisioning_configuration=prov_config
+    )
+
+    aks_target.wait_for_completion(show_output=True)
+    print(aks_target.provisioning_state)
+    print(aks_target.provisioning_errors)
+
+    # Use the default configuration (can also provide parameters to customize)
+    aks_config = AksWebservice.deploy_configuration(enable_app_insights=True)
+
+    service = Webservice.deploy_from_image(
+        workspace=ws,
+        name=aks_service_name,
+        image=image,
+        deployment_config=aks_config,
+        deployment_target=aks_target,
+    )
+
+    service.wait_for_deployment(show_output=True)
+    print(service.state)
+    print(
+        "Deployed AKS Webservice: {} \nWebservice Uri: {}".format(
+            service.name, service.scoring_uri
+        )
+    )
+
+
+# Writing the AKS details to /aml_config/aks_webservice.json
+aks_webservice = {}
+aks_webservice["aks_name"] = aks_name
+aks_webservice["aks_service_name"] = service.name
+aks_webservice["aks_url"] = service.scoring_uri
+aks_webservice["aks_keys"] = service.get_keys()
+with open("aml_config/aks_webservice.json", "w") as outfile:
+    json.dump(aks_webservice, outfile)
diff --git a/aml_service/60-AciWebserviceTest.py b/aml_service/60-AciWebserviceTest.py
new file mode 100644
index 00000000..e2087c98
--- /dev/null
+++ b/aml_service/60-AciWebserviceTest.py
@@ -0,0 +1,62 @@
+"""
+Copyright (C) Microsoft Corporation. All rights reserved.​
+ ​
+Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual,
+royalty-free right to use, copy, and modify the software code provided by us
+("Software Code"). You may not sublicense the Software Code or any use of it
+(except to your affiliates and to vendors to perform work on your behalf)
+through distribution, network access, service agreement, lease, rental, or
+otherwise. This license does not purport to express any claim of ownership over
+data you may have shared with Microsoft in the creation of the Software Code.
+Unless applicable law gives you more rights, Microsoft reserves all other
+rights not expressly granted herein, whether by implication, estoppel or
+otherwise. ​
+ ​
+THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS
+OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
+MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR
+BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER
+IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE
+POSSIBILITY OF SUCH DAMAGE.
+"""
+import numpy
+import os, json, datetime, sys
+from operator import attrgetter
+from azureml.core import Workspace
+from azureml.core.model import Model
+from azureml.core.image import Image
+from azureml.core.webservice import Webservice
+from azureml.core.webservice import AciWebservice
+
+# Get workspace
+ws = Workspace.from_config()
+
+# Get the ACI Details
+try:
+    with open("aml_config/aci_webservice.json") as f:
+        config = json.load(f)
+except:
+    print("No new model, thus no deployment on ACI")
+    # raise Exception('No new model to register as production model perform better')
+    sys.exit(0)
+
+service_name = config["aci_name"]
+# Get the hosted web service
+service = Webservice(name=service_name, workspace=ws)
+
+# Input for Model with all features
+input_j = [[1, 2, 3, 4, 5, 6, 7, 8, 9, 10], [10, 9, 8, 7, 6, 5, 4, 3, 2, 1]]
+print(input_j)
+test_sample = json.dumps({"data": input_j})
+test_sample = bytes(test_sample, encoding="utf8")
+try:
+    prediction = service.run(input_data=test_sample)
+    print(prediction)
+except Exception as e:
+    result = str(e)
+    print(result)
+    raise Exception("ACI service is not working as expected")
diff --git a/aml_service/61-AksWebserviceTest.py b/aml_service/61-AksWebserviceTest.py
new file mode 100644
index 00000000..d55b6baa
--- /dev/null
+++ b/aml_service/61-AksWebserviceTest.py
@@ -0,0 +1,65 @@
+"""
+Copyright (C) Microsoft Corporation. All rights reserved.​
+ ​
+Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual,
+royalty-free right to use, copy, and modify the software code provided by us
+("Software Code"). You may not sublicense the Software Code or any use of it
+(except to your affiliates and to vendors to perform work on your behalf)
+through distribution, network access, service agreement, lease, rental, or
+otherwise. This license does not purport to express any claim of ownership over
+data you may have shared with Microsoft in the creation of the Software Code.
+Unless applicable law gives you more rights, Microsoft reserves all other
+rights not expressly granted herein, whether by implication, estoppel or
+otherwise. ​
+ ​
+THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS
+OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
+MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR
+BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER
+IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE
+POSSIBILITY OF SUCH DAMAGE.
+"""
+import numpy
+import os, json, datetime, sys
+from operator import attrgetter
+from azureml.core import Workspace
+from azureml.core.model import Model
+from azureml.core.image import Image
+from azureml.core.webservice import Webservice
+
+
+# Get workspace
+ws = Workspace.from_config()
+
+# Get the AKS Details
+try:
+    with open("aml_config/aks_webservice.json") as f:
+        config = json.load(f)
+except:
+    print("No new model, thus no deployment on ACI")
+    # raise Exception('No new model to register as production model perform better')
+    sys.exit(0)
+
+service_name = config["aks_service_name"]
+# Get the hosted web service
+service = Webservice(workspace=ws, name=service_name)
+
+# Input for Model with all features
+input_j = [[1, 2, 3, 4, 5, 6, 7, 8, 9, 10], [10, 9, 8, 7, 6, 5, 4, 3, 2, 1]]
+print(input_j)
+test_sample = json.dumps({"data": input_j})
+test_sample = bytes(test_sample, encoding="utf8")
+try:
+    prediction = service.run(input_data=test_sample)
+    print(prediction)
+except Exception as e:
+    result = str(e)
+    print(result)
+    raise Exception("AKS service is not working as expected")
+
+# Delete aci after test
+service.delete()
diff --git a/aml_service/helper/azcli.py b/aml_service/helper/azcli.py
new file mode 100644
index 00000000..4affc1b3
--- /dev/null
+++ b/aml_service/helper/azcli.py
@@ -0,0 +1,73 @@
+"""
+Copyright (C) Microsoft Corporation. All rights reserved.​
+ ​
+Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual,
+royalty-free right to use, copy, and modify the software code provided by us
+("Software Code"). You may not sublicense the Software Code or any use of it
+(except to your affiliates and to vendors to perform work on your behalf)
+through distribution, network access, service agreement, lease, rental, or
+otherwise. This license does not purport to express any claim of ownership over
+data you may have shared with Microsoft in the creation of the Software Code.
+Unless applicable law gives you more rights, Microsoft reserves all other
+rights not expressly granted herein, whether by implication, estoppel or
+otherwise. ​
+ ​
+THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS
+OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
+MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR
+BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER
+IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE
+POSSIBILITY OF SUCH DAMAGE.
+"""
+import subprocess
+
+
+def az_login(sp_user: str, sp_password: str, sp_tenant_id: str):
+    """
+    Uses the provided service principal credentials to log into the azure cli.
+    This should always be the first step in executing az cli commands.
+    """
+    cmd = "az login --service-principal --username {} --password {} --tenant {}"
+    out, err = run_cmd(cmd.format(sp_user, sp_password, sp_tenant_id))
+    return out, err
+
+
+def run_cmd(cmd: str):
+    """
+    Runs an arbitrary command line command.  Works for Linux or Windows.
+    Returns a tuple of output and error.
+    """
+    proc = subprocess.Popen(
+        cmd, shell=True, stdout=subprocess.PIPE, universal_newlines=True
+    )
+    output, error = proc.communicate()
+    if proc.returncode != 0:
+        print("Following command execution failed: {}".format(cmd))
+        raise Exception("Operation Failed. Look at console logs for error info")
+    return output, error
+
+
+def az_account_set(subscription_id: str):
+    """
+    Sets the correct azure subscription.
+    This should always be run after the az_login.
+    """
+    cmd = "az account set  -s {}"
+    out, err = run_cmd(cmd.format(subscription_id))
+    return out, err
+
+
+def az_acr_create(resource_group: str, acr_name: str):
+    cmd = "az acr create --resource-group {} --name {} --sku Basic"
+    out, err = run_cmd(cmd.format(resource_group, acr_name))
+    return out, err
+
+
+def az_acr_login(acr_name: str):
+    cmd = "az acr login --name {}"
+    out, err = run_cmd(cmd.format(acr_name))
+    return out, err
diff --git a/code/scoring/conda_dependencies.yml b/code/scoring/conda_dependencies.yml
new file mode 100644
index 00000000..9bca0710
--- /dev/null
+++ b/code/scoring/conda_dependencies.yml
@@ -0,0 +1,49 @@
+# Conda environment specification. The dependencies defined in this file will
+
+# be automatically provisioned for managed runs. These include runs against
+
+# the localdocker, remotedocker, and cluster compute targets.
+
+
+# Note that this file is NOT used to automatically manage dependencies for the
+
+# local compute target. To provision these dependencies locally, run:
+
+# conda env update --file conda_dependencies.yml
+
+
+# Details about the Conda environment file format:
+
+# https://conda.io/docs/using/envs.html#create-environment-file-by-hand
+
+
+# For managing Spark packages and configuration, see spark_dependencies.yml.
+
+
+# Version of this configuration file's structure and semantics in AzureML.
+
+# This directive is stored in a comment to preserve the Conda file structure.
+
+# [AzureMlVersion] = 2
+
+
+name: project_environment
+dependencies:
+  # The python interpreter version.
+
+  # Currently Azure ML Workbench only supports 3.5.2 and later.
+
+- python=3.6.2
+  # Required by azureml-defaults, installed separately through Conda to
+
+  # get a prebuilt version and not require build tools for the install.
+
+- psutil=5.3
+
+- pip:
+    # Required packages for AzureML execution, history, and data preparation.
+  - azureml-sdk[notebooks]    # add the version to lock it ==0.1.74
+  - scipy==1.0.0
+  - scikit-learn==0.19.1
+  - pandas==0.23.1
+  - numpy==1.14.5
\ No newline at end of file
diff --git a/code/scoring/score.py b/code/scoring/score.py
new file mode 100644
index 00000000..994ca24a
--- /dev/null
+++ b/code/scoring/score.py
@@ -0,0 +1,58 @@
+"""
+Copyright (C) Microsoft Corporation. All rights reserved.​
+ ​
+Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual,
+royalty-free right to use, copy, and modify the software code provided by us
+("Software Code"). You may not sublicense the Software Code or any use of it
+(except to your affiliates and to vendors to perform work on your behalf)
+through distribution, network access, service agreement, lease, rental, or
+otherwise. This license does not purport to express any claim of ownership over
+data you may have shared with Microsoft in the creation of the Software Code.
+Unless applicable law gives you more rights, Microsoft reserves all other
+rights not expressly granted herein, whether by implication, estoppel or
+otherwise. ​
+ ​
+THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS
+OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
+MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR
+BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER
+IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE
+POSSIBILITY OF SUCH DAMAGE.
+"""
+import pickle
+import json
+import numpy
+from sklearn.ensemble import RandomForestClassifier
+from azureml.core.model import Model
+
+
+def init():
+    global model
+    from sklearn.externals import joblib
+
+    # load the model from file into a global object
+    model_path = Model.get_model_path(model_name="sklearn_regression_model.pkl")
+    model = joblib.load(model_path)
+
+
+def run(raw_data):
+    try:
+        data = json.loads(raw_data)["data"]
+        data = numpy.array(data)
+        result = model.predict(data)
+        return json.dumps({"result": result.tolist()})
+    except Exception as e:
+        result = str(e)
+        return json.dumps({"error": result})
+
+
+if __name__ == "__main__":
+    # Test scoring
+    init()
+    test_row = '{"data":[[1,2,3,4,5,6,7,8,9,10],[10,9,8,7,6,5,4,3,2,1]]}'
+    prediction = run(test_row)
+    print("Test result: ", prediction)
diff --git a/code/testing/data_test.py b/code/testing/data_test.py
new file mode 100644
index 00000000..206cc8a5
--- /dev/null
+++ b/code/testing/data_test.py
@@ -0,0 +1,124 @@
+# test integrity of the input data
+"""
+Copyright (C) Microsoft Corporation. All rights reserved.​
+ ​
+Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual,
+royalty-free right to use, copy, and modify the software code provided by us
+("Software Code"). You may not sublicense the Software Code or any use of it
+(except to your affiliates and to vendors to perform work on your behalf)
+through distribution, network access, service agreement, lease, rental, or
+otherwise. This license does not purport to express any claim of ownership over
+data you may have shared with Microsoft in the creation of the Software Code.
+Unless applicable law gives you more rights, Microsoft reserves all other
+rights not expressly granted herein, whether by implication, estoppel or
+otherwise. ​
+ ​
+THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS
+OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
+MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR
+BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER
+IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE
+POSSIBILITY OF SUCH DAMAGE.
+"""
+
+import sys
+import os
+import numpy as np
+import pandas as pd
+
+# number of features
+n_columns = 10
+
+# distribution of features in the training set
+historical_mean = np.array(
+    [
+        -3.63962254e-16,
+        1.26972339e-16,
+        -8.01646331e-16,
+        1.28856202e-16,
+        -8.99230414e-17,
+        1.29609747e-16,
+        -4.56397112e-16,
+        3.87573332e-16,
+        -3.84559152e-16,
+        -3.39848813e-16,
+        1.52133484e02,
+    ]
+)
+historical_std = np.array(
+    [
+        4.75651494e-02,
+        4.75651494e-02,
+        4.75651494e-02,
+        4.75651494e-02,
+        4.75651494e-02,
+        4.75651494e-02,
+        4.75651494e-02,
+        4.75651494e-02,
+        4.75651494e-02,
+        4.75651494e-02,
+        7.70057459e01,
+    ]
+)
+
+# maximal relative change in feature mean or standrd deviation that we can tolerate
+shift_tolerance = 3
+
+
+def check_schema(X):
+    n_actual_columns = X.shape[1]
+    if n_actual_columns != n_columns:
+        print(
+            "Error: found {} feature columns. The data should have {} feature columns.".format(
+                n_actual_columns, n_columns
+            )
+        )
+        return False
+
+    return True
+
+
+def check_missing_values(dataset):
+    n_nan = np.sum(np.isnan(dataset.values))
+    if n_nan > 0:
+        print("Warning: the data has {} missing values".format(n_nan))
+        return False
+    return True
+
+
+def check_distribution(dataset):
+    mean = np.mean(dataset.values, axis=0)
+    std = np.mean(dataset.values, axis=0)
+    if (
+        np.sum(abs(mean - historical_mean) > shift_tolerance * abs(historical_mean)) > 0
+        or np.sum(abs(std - historical_std) > shift_tolerance * abs(historical_std)) > 0
+    ):
+        print("Warning: new data has different distribution than the training data")
+        return False
+    return True
+
+
+def main():
+    filename = sys.argv[1]
+    if not os.path.exists(filename):
+        print("Error: The file {} does not exist".format(filename))
+        return
+
+    dataset = pd.read_csv(filename)
+    if check_schema(dataset[dataset.columns[:-1]]):
+        print("Data schema test succeeded")
+        if check_missing_values(dataset) and check_distribution(dataset):
+            print("Missing values test passed")
+            print("Data distribution test passed")
+        else:
+            print(
+                "There might be some issues with the data. Please check warning messages."
+            )
+
+
+if __name__ == "__main__":
+    main()
diff --git a/code/training/train.py b/code/training/train.py
new file mode 100644
index 00000000..6aeb2c96
--- /dev/null
+++ b/code/training/train.py
@@ -0,0 +1,87 @@
+"""
+Copyright (C) Microsoft Corporation. All rights reserved.​
+ ​
+Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual,
+royalty-free right to use, copy, and modify the software code provided by us
+("Software Code"). You may not sublicense the Software Code or any use of it
+(except to your affiliates and to vendors to perform work on your behalf)
+through distribution, network access, service agreement, lease, rental, or
+otherwise. This license does not purport to express any claim of ownership over
+data you may have shared with Microsoft in the creation of the Software Code.
+Unless applicable law gives you more rights, Microsoft reserves all other
+rights not expressly granted herein, whether by implication, estoppel or
+otherwise. ​
+ ​
+THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS
+OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
+MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR
+BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER
+IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE
+POSSIBILITY OF SUCH DAMAGE.
+"""
+import pickle
+from azureml.core import Workspace
+from azureml.core.run import Run
+import os
+from sklearn.datasets import load_diabetes
+from sklearn.linear_model import Ridge
+from sklearn.metrics import mean_squared_error
+from sklearn.model_selection import train_test_split
+from sklearn.externals import joblib
+import numpy as np
+import json
+import subprocess
+from typing import Tuple, List
+
+# run_history_name = 'devops-ai'
+# os.makedirs('./outputs', exist_ok=True)
+# #ws.get_details()
+# Start recording results to AML
+# run = Run.start_logging(workspace = ws, history_name = run_history_name)
+run = Run.get_submitted_run()
+
+
+X, y = load_diabetes(return_X_y=True)
+columns = ["age", "gender", "bmi", "bp", "s1", "s2", "s3", "s4", "s5", "s6"]
+X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=0)
+data = {"train": {"X": X_train, "y": y_train}, "test": {"X": X_test, "y": y_test}}
+
+print("Running train.py")
+
+# Randomly pic alpha
+alphas = np.arange(0.0, 1.0, 0.05)
+alpha = alphas[np.random.choice(alphas.shape[0], 1, replace=False)][0]
+print(alpha)
+run.log("alpha", alpha)
+reg = Ridge(alpha=alpha)
+reg.fit(data["train"]["X"], data["train"]["y"])
+preds = reg.predict(data["test"]["X"])
+run.log("mse", mean_squared_error(preds, data["test"]["y"]))
+
+
+# Save model as part of the run history
+model_name = "sklearn_regression_model.pkl"
+# model_name = "."
+
+with open(model_name, "wb") as file:
+    joblib.dump(value=reg, filename=model_name)
+
+# upload the model file explicitly into artifacts
+run.upload_file(name="./outputs/" + model_name, path_or_stream=model_name)
+print("Uploaded the model {} to experiment {}".format(model_name, run.experiment.name))
+dirpath = os.getcwd()
+print(dirpath)
+
+
+# register the model
+# run.log_model(file_name = model_name)
+# print('Registered the model {} to run history {}'.format(model_name, run.history.name))
+
+
+print("Following files are uploaded ")
+print(run.get_file_names())
+run.complete()
diff --git a/data/diabetes.csv b/data/diabetes.csv
new file mode 100644
index 00000000..162002a7
--- /dev/null
+++ b/data/diabetes.csv
@@ -0,0 +1,443 @@
+AGE,SEX,BMI,BP,S1,S2,S3,S4,S5,S6,Y
+0.0380759064334241,0.0506801187398187,0.0616962065186885,0.0218723549949558,-0.0442234984244464,-0.0348207628376986,-0.0434008456520269,-0.00259226199818282,0.0199084208763183,-0.0176461251598052,151.0
+-0.001882016527791,-0.044641636506989,-0.0514740612388061,-0.0263278347173518,-0.00844872411121698,-0.019163339748222,0.0744115640787594,-0.0394933828740919,-0.0683297436244215,-0.09220404962683,75.0
+0.0852989062966783,0.0506801187398187,0.0444512133365941,-0.00567061055493425,-0.0455994512826475,-0.0341944659141195,-0.0323559322397657,-0.00259226199818282,0.00286377051894013,-0.0259303389894746,141.0
+-0.0890629393522603,-0.044641636506989,-0.0115950145052127,-0.0366564467985606,0.0121905687618,0.0249905933641021,-0.0360375700438527,0.0343088588777263,0.0226920225667445,-0.0093619113301358,206.0
+0.00538306037424807,-0.044641636506989,-0.0363846922044735,0.0218723549949558,0.00393485161259318,0.0155961395104161,0.0081420836051921,-0.00259226199818282,-0.0319914449413559,-0.0466408735636482,135.0
+-0.0926954778032799,-0.044641636506989,-0.0406959404999971,-0.0194420933298793,-0.0689906498720667,-0.0792878444118122,0.0412768238419757,-0.076394503750001,-0.0411803851880079,-0.0963461565416647,97.0
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+0.063503675590561,0.0506801187398187,-0.00189470584028465,0.0666296740135272,0.0906198816792644,0.108914381123697,0.0228686348215404,0.0177033544835672,-0.0358167281015492,0.00306440941436832,63.0
+0.0417084448844436,0.0506801187398187,0.0616962065186885,-0.0400993174922969,-0.0139525355440215,0.00620168565673016,-0.0286742944356786,-0.00259226199818282,-0.0149564750249113,0.0113486232440377,110.0
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+0.00538306037424807,0.0506801187398187,-0.00189470584028465,0.0081008722200108,-0.00432086553661359,-0.0157187066685371,-0.0029028298070691,-0.00259226199818282,0.0383932482116977,-0.0135040182449705,185.0
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diff --git a/data/diabetes_bad_dist.csv b/data/diabetes_bad_dist.csv
new file mode 100644
index 00000000..2d7cf434
--- /dev/null
+++ b/data/diabetes_bad_dist.csv
@@ -0,0 +1,3 @@
+AGE,SEX,BMI,BP,S1,S2,S3,S4,S5,S6,Y
+100,0.0506801187398187,0.0616962065186885,0.0218723549949558,-0.0442234984244464,-0.0348207628376986,-0.0434008456520269,-0.00259226199818282,0.0199084208763183,-0.0176461251598052,151.0
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diff --git a/data/diabetes_bad_schema.csv b/data/diabetes_bad_schema.csv
new file mode 100644
index 00000000..b21fca1d
--- /dev/null
+++ b/data/diabetes_bad_schema.csv
@@ -0,0 +1,3 @@
+SEX,BMI,BP,S1,S2,S3,S4,S5,S6,Y
+0.0506801187398187,0.0616962065186885,0.0218723549949558,-0.0442234984244464,-0.0348207628376986,-0.0434008456520269,-0.00259226199818282,0.0199084208763183,-0.0176461251598052,151.0
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diff --git a/data/diabetes_missing_values.csv b/data/diabetes_missing_values.csv
new file mode 100644
index 00000000..44d8a056
--- /dev/null
+++ b/data/diabetes_missing_values.csv
@@ -0,0 +1,3 @@
+AGE,SEX,BMI,BP,S1,S2,S3,S4,S5,S6,Y
+,,,0.0218723549949558,-0.0442234984244464,-0.0348207628376986,-0.0434008456520269,-0.00259226199818282,0.0199084208763183,-0.0176461251598052,151.0
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diff --git a/docs/code_description.md b/docs/code_description.md
new file mode 100644
index 00000000..45fb7bb7
--- /dev/null
+++ b/docs/code_description.md
@@ -0,0 +1,60 @@
+## Repo Details
+
+### Environment Setup
+
+- requirements.txt : It consist of list of python packages which are needed by the train.py to run successfully on host agent (locally).
+
+- install_requirements.sh : This script prepare the python environment i.e. install the Azure ML SDK and the packages specified in requirements.txt
+
+### Config Files
+All the scripts inside the ./aml_config are config files. These are the files where you need to provide details about the subscription, resource group, workspace, conda dependencies, remote vm, AKS etc.
+
+- config.json : This is a mandatory config file. Provide the subscription id, resource group name, workspace name and location where you want to create Azure ML services workspace. If you have already created the workspace, provide the existing workspace details in here.
+
+- conda_dependencies.yml : This is a mandatory file. This files contains the list of dependencies which are needed by the training/scoring script to run. This file is used to prepare environment for the local run(user managed/system managed) and docker run(local/remote).
+
+- security_config.json : This file contains the credentials to the remove vm where we want to train the model. This config is used by the script 02-AttachTrainingVM.py to attach remote vm as a compute to the workspace. Attaching remote vm to workspace is one time operation. It is recommended not to publish this file with credentials populated in it. You can put the credentials, run the 02-AttachTrainingVM.py manually and clear the credentials before pushing it to git.
+
+- aks_webservice.json : This is an optional config. If you already have an AKS attached to your workspace, then provide the details in this file. If not, you do not have to check in this file to git.
+
+### Build Pipeline Scripts
+
+The script under ./aml_service are used in build pipeline. All the scripts starting with 0 are the one time run scripts. These are the scripts which need to be run only once. There is no harm of running these scripts every time in build pipeline.
+
+- 00-WorkSpace.py : This is a onetime run script. It reads the workspace details from ./aml_config/config.json file and create (if workspace not available) or get (existing workspace). 
+
+- 01-Experiment.py : This is a onetime run script. It registers the root directory as project. It is not included as a step in build pipeline.
+
+- 02-AttachTrainingVM.py : This is a onetime run script. It attaches a remote VM to the workspace. It reads the config from ./aml_config/security_config.json. It is not included as a step in build pipeline.
+
+- 10-TrainOnLocal.py : This scripts triggers the run of ./training/train.py script on the local compute(Host agent in case of build pipeline). If you are training on remote vm, you do not need this script in build pipeline. All the training scripts (1x) generates an output file aml_config/run_id.json which records the run_id and run history name of the training run. run_id.json is used by 20-RegisterModel.py to get the trained model.
+
+- 11-TrainOnLocalEnv.py : Its functionality is same as 10-TrainOnLocal.py, the only difference is that it creates a virtual environment on local compute and run training script on virtual env.
+
+- 12-TrainOnVM.py : As we want to train the model on remote VM, this script is included as a task in build pipeline. It submits the training job on remote vm. 
+
+- 15.EvaluateModel.py : It gets the metrics of latest model trained and compares it with the model in production. If the production model still performs better, all below scripts are skipped. 
+
+- 20-RegisterModel.py : It gets the run id from training steps output json and registers the model associated with that run along with tags. This scripts outputs a model.json file which contains model name and version. This script included as build task.
+
+- 30-CreateScoringImage.py : This takes the model details from last step, creates a scoring webservice docker image and publish the image to ACR. This script included as build task. It writes the image name and version to image.json file.
+
+### Deployment/Release Scripts
+File under the directory ./aml_service starting with 5x and 6x are used in release pipeline. They are basically to deploy the docker image on AKS and ACI and publish webservice on them.
+
+- 50-deployOnAci.py : This script reads the image.json which is published as an artifact from build pipeline, create aci cluster and deploy the scoring web service on it. It writes the scoring service details to aci_webservice.json
+
+- 51-deployOnAks.py : This script reads the image.json which is published as an artifact from build pipeline, create aks cluster and deploy the scoring web service on it. If the aks_webservice.json file was checked in with existing aks details, it will update the existing webservice with new Image. It writes the scoring service details to aks_webservice.json
+
+- 60-AciWebServiceTest.py : Reads the ACI info from aci_webservice.json and test it with sample data.
+
+- 61-AksWebServiceTest.py : Reads the AKS info from aks_webservice.json and test it with sample data.
+
+### Training/Scoring Scripts
+
+- /code/training/train.py : This is the model training code. It uploads the model file to AML Service run id once the training is successful. This script is submitted as run job by all the 1x scripts.
+
+- /code/scoring/score.py : This is the score file used to create the webservice docker image. There is a conda_dependencies.yml in this directory which is exactly same as the one in aml_config. These two files are needed by the 30-CreateScoringImage.py scripts to be in same root directory while creating the image.
+
+**Note: In CICD Pipeline, please make sure that the working directory is the root directory of the repo.**  
+
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diff --git a/docs/images/EditPipeline7.png b/docs/images/EditPipeline7.png
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diff --git a/docs/images/EditPipeline8.png b/docs/images/EditPipeline8.png
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diff --git a/environment_setup/install_requirements.sh b/environment_setup/install_requirements.sh
new file mode 100644
index 00000000..164a1a7b
--- /dev/null
+++ b/environment_setup/install_requirements.sh
@@ -0,0 +1,31 @@
+#!/bin/bash
+
+# Copyright (C) Microsoft Corporation. All rights reserved.​
+#  ​
+# Microsoft Corporation (“Microsoft”) grants you a nonexclusive, perpetual,
+# royalty-free right to use, copy, and modify the software code provided by us
+# ('Software Code'). You may not sublicense the Software Code or any use of it
+# (except to your affiliates and to vendors to perform work on your behalf)
+# through distribution, network access, service agreement, lease, rental, or
+# otherwise. This license does not purport to express any claim of ownership over
+# data you may have shared with Microsoft in the creation of the Software Code.
+# Unless applicable law gives you more rights, Microsoft reserves all other
+# rights not expressly granted herein, whether by implication, estoppel or
+# otherwise. ​
+#  ​
+# THE SOFTWARE CODE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS
+# OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
+# MICROSOFT OR ITS LICENSORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
+# SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR
+# BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER
+# IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+# ARISING IN ANY WAY OUT OF THE USE OF THE SOFTWARE CODE, EVEN IF ADVISED OF THE
+# POSSIBILITY OF SUCH DAMAGE.
+
+
+python --version
+pip install azure-cli==2.0.46
+pip install --upgrade azureml-sdk[notebooks,automl]
+pip install -r requirements.txt
\ No newline at end of file
diff --git a/environment_setup/requirements.txt b/environment_setup/requirements.txt
new file mode 100644
index 00000000..c69c9074
--- /dev/null
+++ b/environment_setup/requirements.txt
@@ -0,0 +1,4 @@
+scipy==1.0.0
+scikit-learn==0.19.1
+numpy==1.14.5
+pandas==0.23.1
\ No newline at end of file
diff --git a/model/placeholder b/model/placeholder
new file mode 100644
index 00000000..e69de29b