added custom docker environment setting

configuration/environments/environment_inference_dockerfile/BaseDockerfile

@@ -0,0 +1,6 @@
+
+FROM mcr.microsoft.com/azureml/openmpi3.1.2-ubuntu18.04
+RUN apt-get update
+RUN apt-get install ffmpeg libsm6 libxext6  -y
+RUN apt-get update && apt-get install -y python3-opencv
+RUN pip install opencv-python

configuration/environments/environment_inference_dockerfile/azureml_environment.json

@@ -0,0 +1,44 @@
+{
+    "name": "environment_inference_dockerfile",
+    "version": "oct21",
+    "environmentVariables": {
+        "EXAMPLE_ENV_VAR": "EXAMPLE_VALUE"
+    },
+    "python": {
+        "userManagedDependencies": false,
+        "interpreterPath": "python",
+        "condaDependenciesFile": null,
+        "baseCondaEnvironment": null
+    },
+    "docker": {
+        "enabled": false,
+        "baseImage": null,
+        "sharedVolumes": true,
+        "shmSize": null,
+        "arguments": [],
+        "baseImageRegistry": {
+            "address": null,
+            "username": null,
+            "password": null,
+            "registryIdentity": null
+        },
+        "platform": {
+            "os": "Linux",
+            "architecture": "amd64"
+        }
+    },
+    "spark": {
+        "repositories": [],
+        "packages": [],
+        "precachePackages": true
+    },
+    "databricks": {
+        "mavenLibraries": [],
+        "pypiLibraries": [],
+        "rcranLibraries": [],
+        "jarLibraries": [],
+        "eggLibraries": []
+    },
+    "r": null,
+    "inferencingStackVersion": null
+}

configuration/environments/environment_inference_dockerfile/conda_dependencies.yml

@@ -0,0 +1,11 @@
+channels:
+- conda-forge
+dependencies:
+- python=3.8
+- pip:
+  - azureml-core==1.35.0
+  - azureml-defaults==1.35.0
+  - pandas
+  - joblib
+
+name: basic_env

configuration/environments/environment_training_dockerfile/BaseDockerfile

@@ -0,0 +1,6 @@
+
+FROM mcr.microsoft.com/azureml/openmpi3.1.2-ubuntu18.04
+RUN apt-get update
+RUN apt-get install ffmpeg libsm6 libxext6  -y
+RUN apt-get update && apt-get install -y python3-opencv
+RUN pip install opencv-python

configuration/environments/environment_training_dockerfile/azureml_environment.json

@@ -0,0 +1,44 @@
+{
+    "name": "environment_training_dockerfile",
+    "version": "oct21",
+    "environmentVariables": {
+        "EXAMPLE_ENV_VAR": "EXAMPLE_VALUE"
+    },
+    "python": {
+        "userManagedDependencies": false,
+        "interpreterPath": "python",
+        "condaDependenciesFile": null,
+        "baseCondaEnvironment": null
+    },
+    "docker": {
+        "enabled": false,
+        "baseImage": null,
+        "sharedVolumes": true,
+        "shmSize": null,
+        "arguments": [],
+        "baseImageRegistry": {
+            "address": null,
+            "username": null,
+            "password": null,
+            "registryIdentity": null
+        },
+        "platform": {
+            "os": "Linux",
+            "architecture": "amd64"
+        }
+    },
+    "spark": {
+        "repositories": [],
+        "packages": [],
+        "precachePackages": true
+    },
+    "databricks": {
+        "mavenLibraries": [],
+        "pypiLibraries": [],
+        "rcranLibraries": [],
+        "jarLibraries": [],
+        "eggLibraries": []
+    },
+    "r": null,
+    "inferencingStackVersion": null
+}

configuration/environments/environment_training_dockerfile/conda_dependencies.yml

@@ -0,0 +1,11 @@
+channels:
+- conda-forge
+dependencies:
+- python=3.8
+- pip:
+  - azureml-core==1.35.0
+  - azureml-defaults==1.35.0
+  - pandas
+  - joblib
+
+name: basic_env

docs/how-to/AdjustingDockerfile.md

@@ -0,0 +1,17 @@
+# Customizing the base docker image (mcr.microsoft.com/azureml/openmpi3.1.2-ubuntu18.04:20210922.v1) 
+You have the option to specify your custom docker images for training and inference separately.
+
+## First Step: Define your dockerfile
+In case you need to upgrade/change packages in Linux (using for example apt-get install / apt-get update) or define additional commands you have the option to configure the Dockerfile on your own.
+
+**[Environments](../../configuration/environments/)** contains two docker-related folders "environment_inference_dockerfile" and "environment_training_dockerfile" with the corresponding Dockerfile (BaseDockerfile). 
+
+## Second Step: Change the environment path
+After having set up your Dockerfile, you need to change the paths here: **[Configurations](../../configuration/configuration-aml.variables.yaml)**
+
+Replace "AML_TRAINING_ENV_PATH" with "configuration/environments/environment_training_dockerfile" if you need the adjusted dockerfile for training.
+Replace "AML_BATCHINFERENCE_ENV_PATH" with "configuration/environments/environment_inference_dockerfile" if you need the adjusted dockerfile for training.
+
+In case you want to deploy your own webservice, you can customize your docker images differently. Issue [#29](https://github.com/microsoft/dstoolkit-mlops-base/issues/29) describes this enhancement.
+
+For more detail, please refer to *[GettingStarted](GettingStarted.md)*

docs/how-to/FAQ.md

@@ -4,4 +4,9 @@
 
 If you see the error below. You have to ensure that the service connection is created at the Azure Machine Learning Workspace level and not Subscription level
 
-![faq-error-invoke](../media/FAQ-invoke.error.png)
+![faq-error-invoke](../media/FAQ-invoke.error.png)
+
+## I would like to adjust the Docker Image. How can I change the Dockerfile?
+
+Documentation can be found here: 
+**[Custom Dockerfile](../../docs/how-to/AdjustingDockerfile)**