Merge branch 'main' of https://github.com/Azure/azureml-examples

Author: kshitij-microsoft

.github/CODEOWNERS

@@ -84,7 +84,7 @@ jobs:
           bash "${{ github.workspace }}/infra/bootstrapping/sdk_helpers.sh" generate_workspace_config "../../.azureml/config.json";
           bash "${{ github.workspace }}/infra/bootstrapping/sdk_helpers.sh" replace_template_values "online-endpoints-deploy-mlflow-model-with-script.ipynb";
           [ -f "../../.azureml/config" ] && cat "../../.azureml/config";
-          papermill -k python online-endpoints-deploy-mlflow-model-with-script.ipynb online-endpoints-deploy-mlflow-model-with-script.output.ipynb
+          papermill -k python online-endpoints-deploy-mlflow-model-with-script.ipynb online-endpoints-deploy-mlflow-model-with-script.output.ipynb --log-output
       working-directory: sdk/python/endpoints/online/mlflow
     - name: upload notebook's working folder as an artifact
       if: ${{ always() }}

.github/workflows/sdk-endpoints-online-mlflow-online-endpoints-deploy-mlflow-model-with-script.yml

@@ -84,7 +84,7 @@ jobs:
           bash "${{ github.workspace }}/infra/bootstrapping/sdk_helpers.sh" generate_workspace_config "../../.azureml/config.json";
           bash "${{ github.workspace }}/infra/bootstrapping/sdk_helpers.sh" replace_template_values "online-endpoints-deploy-mlflow-model.ipynb";
           [ -f "../../.azureml/config" ] && cat "../../.azureml/config";
-          papermill -k python online-endpoints-deploy-mlflow-model.ipynb online-endpoints-deploy-mlflow-model.output.ipynb
+          papermill -k python online-endpoints-deploy-mlflow-model.ipynb online-endpoints-deploy-mlflow-model.output.ipynb --log-output
       working-directory: sdk/python/endpoints/online/mlflow
     - name: upload notebook's working folder as an artifact
       if: ${{ always() }}

.github/workflows/sdk-endpoints-online-mlflow-online-endpoints-deploy-mlflow-model.yml

@@ -84,7 +84,7 @@ jobs:
           bash "${{ github.workspace }}/infra/bootstrapping/sdk_helpers.sh" generate_workspace_config "../../.azureml/config.json";
           bash "${{ github.workspace }}/infra/bootstrapping/sdk_helpers.sh" replace_template_values "online-endpoints-triton.ipynb";
           [ -f "../../.azureml/config" ] && cat "../../.azureml/config";
-          papermill -k python online-endpoints-triton.ipynb online-endpoints-triton.output.ipynb
+          papermill -k python online-endpoints-triton.ipynb online-endpoints-triton.output.ipynb --log-output
       working-directory: sdk/python/endpoints/online/triton/single-model
     - name: upload notebook's working folder as an artifact
       if: ${{ always() }}

.github/workflows/sdk-endpoints-online-triton-single-model-online-endpoints-triton.yml

@@ -26,7 +26,7 @@ concurrency:
   cancel-in-progress: true
 jobs:
   build:
-    runs-on: ubuntu-20.04
+    runs-on: ubuntu-latest
     steps:
     - name: check out repo
       uses: actions/checkout@v2

.github/workflows/tutorials-get-started-notebooks-explore-data.yml

@@ -29,8 +29,8 @@ else
 fi
 
 # cleanup of existing models
-model_archive=$(az ml model archive -n $AML_SKLEARN_MODEL_NAME --version 1 || true)
-model_archive=$(az ml model archive -n $AML_LIGHTGBM_MODEL_NAME --version 1 || true)
+model_archive=$(az ml model archive -n $AML_SKLEARN_MODEL_NAME --version 2 || true)
+model_archive=$(az ml model archive -n $AML_LIGHTGBM_MODEL_NAME --version 3 || true)
 
 
 # <create_sklearn_deployment>
@@ -70,8 +70,8 @@ az ml online-endpoint invoke --name $ENDPOINT_NAME --deployment lightgbm-deploym
 # </test_lightgbm_deployment>
 
 # cleanup of models
-model_archive=$(az ml model archive -n $AML_SKLEARN_MODEL_NAME --version 1 || true)
-model_archive=$(az ml model archive -n $AML_LIGHTGBM_MODEL_NAME --version 1 || true)
+model_archive=$(az ml model archive -n $AML_SKLEARN_MODEL_NAME --version 2 || true)
+model_archive=$(az ml model archive -n $AML_LIGHTGBM_MODEL_NAME --version 3 || true)
 
 # <delete_endpoint>
 az ml online-endpoint delete --name $ENDPOINT_NAME --yes 

cli/deploy-managed-online-endpoint-ncd.sh

@@ -3,7 +3,7 @@ name: lightgbm-deployment
 endpoint_name: my-endpoint
 model:
   name: mir-sample-lightgbm-ncd-model
-  version: 2
+  version: 3
   path: lightgbm-iris/model
   type: mlflow_model
 instance_type: Standard_DS3_v2

cli/endpoints/online/ncd/lightgbm-deployment.yaml

@@ -8,6 +8,7 @@ dependencies:
   - lightgbm==3.3.5
   - pandas==2.0.0
   - psutil==5.9.4
-  - typing-extensions==4.5.0
+  - typing-extensions==4.1.1
   - numpy==1.26.4
+  - azureml-inference-server-http
 name: mlflow-env

cli/endpoints/online/ncd/lightgbm-iris/model/conda.yaml

@@ -75,6 +75,9 @@ Test Status is for branch - **_main_**
 |endpoints|online|[online-endpoints-deploy-mlflow-model-with-script](endpoints/online/mlflow/online-endpoints-deploy-mlflow-model-with-script.ipynb)|Deploy an mlflow model to an online endpoint. This will be a no-code-deployment. It doesn't require scoring script and environment.|[![online-endpoints-deploy-mlflow-model-with-script](https://github.com/Azure/azureml-examples/actions/workflows/sdk-endpoints-online-mlflow-online-endpoints-deploy-mlflow-model-with-script.yml/badge.svg?branch=main)](https://github.com/Azure/azureml-examples/actions/workflows/sdk-endpoints-online-mlflow-online-endpoints-deploy-mlflow-model-with-script.yml)|
 |endpoints|online|[online-endpoints-deploy-mlflow-model](endpoints/online/mlflow/online-endpoints-deploy-mlflow-model.ipynb)|Deploy an mlflow model to an online endpoint. This will be a no-code-deployment. It doesn't require scoring script and environment.|[![online-endpoints-deploy-mlflow-model](https://github.com/Azure/azureml-examples/actions/workflows/sdk-endpoints-online-mlflow-online-endpoints-deploy-mlflow-model.yml/badge.svg?branch=main)](https://github.com/Azure/azureml-examples/actions/workflows/sdk-endpoints-online-mlflow-online-endpoints-deploy-mlflow-model.yml)|
 |endpoints|online|[online-endpoints-triton](endpoints/online/triton/single-model/online-endpoints-triton.ipynb)|Deploy a custom container as an online endpoint. Use web servers other than the default Python Flask server used by Azure ML without losing the benefits of Azure ML's built-in monitoring, scaling, alerting, and authentication.|[![online-endpoints-triton](https://github.com/Azure/azureml-examples/actions/workflows/sdk-endpoints-online-triton-single-model-online-endpoints-triton.yml/badge.svg?branch=main)](https://github.com/Azure/azureml-examples/actions/workflows/sdk-endpoints-online-triton-single-model-online-endpoints-triton.yml)|
+|environments|environment|[environment](assets/environment/environment.ipynb)|Environments in AML SDK v2 ensure reproducibility and consistency by encapsulating dependencies, packages, and runtime settings for training and inference workflows.| NA |
+|environments|environment with private package - conda file|[environment-with-private-package-conda-spec](assets/environment/environment-with-private-packages/environment-with-private-package-conda-spec.ipynb)|Environments in AML SDK v2 ensure reproducibility and consistency by encapsulating dependencies, packages, and runtime settings for training and inference workflows. This example shows how to use private python packages with environments using conda file.| NA |
+|environments|environment with private packages - docker image|[environment-with-private-package-docker-image](assets/environment/environment-with-private-packages/environment-with-private-package-docker-image.ipynb)|Environments in AML SDK v2 ensure reproducibility and consistency by encapsulating dependencies, packages, and runtime settings for training and inference workflows.This example shows how to use private python packages with environments using docker image.| NA |
 |featurestore_sample|automation-test|[test_featurestore_cli_samples](featurestore_sample/automation-test/test_featurestore_cli_samples.ipynb)|*no description*|[![test_featurestore_cli_samples](https://github.com/Azure/azureml-examples/actions/workflows/sdk-featurestore_sample-automation-test-test_featurestore_cli_samples.yml/badge.svg?branch=main)](https://github.com/Azure/azureml-examples/actions/workflows/sdk-featurestore_sample-automation-test-test_featurestore_cli_samples.yml)|
 |featurestore_sample|automation-test|[test_featurestore_sdk_samples](featurestore_sample/automation-test/test_featurestore_sdk_samples.ipynb)|*no description*|[![test_featurestore_sdk_samples](https://github.com/Azure/azureml-examples/actions/workflows/sdk-featurestore_sample-automation-test-test_featurestore_sdk_samples.yml/badge.svg?branch=main)](https://github.com/Azure/azureml-examples/actions/workflows/sdk-featurestore_sample-automation-test-test_featurestore_sdk_samples.yml)|
 |featurestore_sample|automation-test|[test_featurestore_vnet_samples](featurestore_sample/automation-test/test_featurestore_vnet_samples.ipynb)|*no description*|[![test_featurestore_vnet_samples](https://github.com/Azure/azureml-examples/actions/workflows/sdk-featurestore_sample-automation-test-test_featurestore_vnet_samples.yml/badge.svg?branch=main)](https://github.com/Azure/azureml-examples/actions/workflows/sdk-featurestore_sample-automation-test-test_featurestore_vnet_samples.yml)|

sdk/python/README.md

@@ -37,7 +37,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "msdoc": "how-to-manage-environments-v2.md",
     "name": "libraries"
    },
    "outputs": [],
@@ -61,7 +60,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "msdoc": "how-to-manage-environments-v2.md",
     "name": "workspace_details"
    },
    "outputs": [],
@@ -76,7 +74,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "msdoc": "how-to-manage-environments-v2.md",
     "name": "get_workspace"
    },
    "outputs": [],
@@ -141,10 +138,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "msdoc": "how-to-manage-environments-v2.md",
-    "name": "create_from_docker_image"
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "env = Environment(\n",
@@ -154,14 +148,9 @@
     "        \"dependencies\": [\n",
     "            \"python=3.8\",  # Specify the Python version\n",
     "            \"pip\",\n",
-    "            {\n",
-    "                \"pip\": [\n",
-    "                    private_wheel_1,\n",
-    "                    private_wheel_2\n",
-    "                ]\n",
-    "            }\n",
+    "            {\"pip\": [private_wheel_1, private_wheel_2]},\n",
     "        ]\n",
-    "    }\n",
+    "    },\n",
     ")\n",
     "\n",
     "# Register the environment\n",
@@ -172,7 +161,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# 3. Define a job within the custom ebvironment"
+    "# 3. Define a job within the custom environment"
    ]
   },
   {
@@ -189,7 +178,7 @@
     "    code=\"./my-script-folder\",  # Directory containing the script\n",
     "    environment=env,  # The environment with private wheels\n",
     "    compute=\"my-compute\",  # Compute target to use\n",
-    "    environment_variables={\"ENV_VAR\": \"value\"}  # Optional: environment variables\n",
+    "    environment_variables={\"ENV_VAR\": \"value\"},  # Optional: environment variables\n",
     ")\n",
     "\n",
     "# Submit the job\n",