# Introduction

The A&AI Model Loader Service is an application that facilitates the distribution and ingestion of 
new service and resource models and VNF catalogs from the SDC to the A&AI.

## Features

The Model Loader:

* registers with the SDC to receive notification events 
* polls the UEB/DMaap cluster for notification events
* downloads artifacts from SDC upon receipt of a distribution event
* pushes distribution components to A&AI
		    
### VNF Catalog loading

The Model Loader supports two methods for supplying VNF Catalog data for loading into A&AI:

* Embedded TOSCA image and vendor data<br/>VNF Catalog data can be embedded within the TOSCA yaml files contained in the CSAR.


* VNF Catalog XML files<br/>VNF Catalog data in the form of XML files can be supplied in the CSAR under the path `Artifacts/Deployment/VNF_CATALOG`

**Note: Each CSAR should provide VNF Catalog information using only one of the above methods. If a CSAR contains both TOSCA and XML VNF Catalog information, a deploy failure will be logged and published to SDC, and no VNF Catalog data will be loaded into A&AI** 
		    
## Compiling Model Loader

Model Loader can be compiled by running `mvn clean install`
A Model Loader docker image can be created by running `docker build -t onap/model-loader target`

## Running Model Loader 

Push the Docker image to your Docker repository. Pull this down to the host machine.

**Create the following directories on the host machine:**

    ./logs
    ./opt/app/model-loader/appconfig
    ./opt/app/model-loader/appconfig/auth
    
You will be mounting these as data volumes when you start the Docker container.  For examples of the files required in these directories, see the aai/test/config repository (https://gerrit.onap.org/r/#/admin/projects/aai/test-config)

**Populate these directories as follows:**

#### Contents of /opt/app/model-loader/appconfig

The following file must be present in this directory on the host machine:
    
_model-loader.properties_  

    # Always false.  TLS Auth currently not supported 
    ml.distribution.ACTIVE_SERVER_TLS_AUTH=false
    
    # Address/port of the SDC
    ml.distribution.ASDC_ADDRESS=<SDC-Hostname>:8443
    
    # DMaaP consumer group.  
    ml.distribution.CONSUMER_GROUP=aai-ml-group
    
    # DMaaP consumer ID
    ml.distribution.CONSUMER_ID=aai-ml
    
    # SDC Environment Name.  This must match the environment name configured on the SDC
    ml.distribution.ENVIRONMENT_NAME=<Environment Name>
    
    # Currently not used
    ml.distribution.KEYSTORE_PASSWORD=
    
    # Currently not used
    ml.distribution.KEYSTORE_FILE=
    
    # Obfuscated password to connect to the SDC.  To obtain this value, use the following Jetty library to 
    # obfuscate the cleartext password:  http://www.eclipse.org/jetty/documentation/9.4.x/configuring-security-secure-passwords.html
    ml.distribution.PASSWORD=OBF:<password>
    
    # How often (in seconds) to poll the DMaaP cluster for new model events
    ml.distribution.POLLING_INTERVAL=<integer>
    
    # Timeout value (in seconds) when polling DMaaP for new model events
    ml.distribution.POLLING_TIMEOUT=<integer>
    
    # Username to use when connecting to the SDC
    ml.distribution.USER=<username>
    
    # Artifact type we want to download from the SDC (the values below will typically suffice)
    ml.distribution.ARTIFACT_TYPES=MODEL_QUERY_SPEC,TOSCA_CSAR
    
    # List of message bus addresses on which to listen for distribution events
    ml.distribution.MSG_BUS_ADDRESSES=<host1>,<host2>

    # URL of the A&AI
    ml.aai.BASE_URL=https://<AAI-Hostname>:8443
    
    # A&AI endpoint to post models
    ml.aai.MODEL_URL=/aai/v*/service-design-and-creation/models/model/
    
    # A&AI endpoint to post named queries
    ml.aai.NAMED_QUERY_URL=/aai/v*/service-design-and-creation/named-queries/named-query/
    
    # A&AI endpoint to post vnf images
    ml.aai.VNF_IMAGE_URL=/aai/v*/service-design-and-creation/vnf-images
    
    # Name of certificate to use in connecting to the A&AI
    ml.aai.KEYSTORE_FILE=aai-os-cert.p12
    
    # Obfuscated keystore password to connect to the A&AI.  This is only required if using 2-way SSL (not basic auth).
    # To obtain this value, use the following Jetty library to obfuscate the cleartext password:
    # http://www.eclipse.org/jetty/documentation/9.4.x/configuring-security-secure-passwords.html
    ml.aai.KEYSTORE_PASSWORD=OBF:<password>
    
    # Name of user to use when connecting to the A&AI.  This is only required if using basic auth (not 2-way SSL).
    ml.aai.AUTH_USER=<username>
    
    # Obfuscated password to connect to the A&AI.  This is only required if using basic auth (not 2-way SSL).
    # To obtain this value, use the following Jetty library to obfuscate the cleartext password:
    # http://www.eclipse.org/jetty/documentation/9.4.x/configuring-security-secure-passwords.html
    ml.aai.AUTH_PASSWORD=OBF:<password>
    


##### Contents of the /opt/app/model-loader/app-config/auth Directory

The following files must be present in this directory on the host machine:

_aai-os-cert.p12_

The certificate used to connected to the A&AI

**Start the service:**

You can now start the Docker container for the _Model Loader Service_, e.g:

	docker run -d \
		-e CONFIG_HOME=/opt/app/model-loader/config/ \
	    -v /logs:/logs \
	    -v /opt/app/model-loader/appconfig:/opt/app/model-loader/config \
	    --name model-loader \
	    {{your docker repo}}/model-loader
    
where

    {{your docker repo}}
is the Docker repository you have published your image to.