# Introduction
The A&AI Model Loader Service is an application that facilitates the distribution and ingestion of
-new service and resource models from the SDC to the A&AI.
+new service and resource models and VNF catalogs from the SDC to the A&AI.
## Features
* 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`
The following file must be present in this directory on the host machine:
-_model-loader.properties_
+_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.
+ # Kafka consumer group.
ml.distribution.CONSUMER_GROUP=aai-ml-group
- # DMaaP consumer ID
+ # Kafka consumer ID
ml.distribution.CONSUMER_ID=aai-ml
# SDC Environment Name. This must match the environment name configured on the SDC
# 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
+ # How often (in seconds) to poll the Kafka topic for new model events
ml.distribution.POLLING_INTERVAL=<integer>
- # Timeout value (in seconds) when polling DMaaP for new model events
+ # Timeout value (in seconds) when polling the Kafka topic for new model events
ml.distribution.POLLING_TIMEOUT=<integer>
# Username to use when connecting to the SDC
# 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
{{your docker repo}}/model-loader
where
-
+
{{your docker repo}}
is the Docker repository you have published your image to.