summaryrefslogtreecommitdiffstats
path: root/README.md
diff options
context:
space:
mode:
authorFiete Ostkamp <Fiete.Ostkamp@telekom.de>2024-02-22 13:19:35 +0100
committerFiete Ostkamp <Fiete.Ostkamp@telekom.de>2024-02-22 13:26:49 +0100
commitc7d3869e64534a06692191d0cdfecb2b30138c13 (patch)
tree3107fdf7dd2a00d2481ddbd91aaceb12f15f04ab /README.md
parent5ec525d780ef43770a896cda70ce633af1503095 (diff)
Update aai-common-alpine base image in model-loader
- update aai-common-alpine base image from 1.8.1 to 1.13.2 - rename README file Issue-ID: AAI-3785 Change-Id: I0343c5ffc4dc3b00fd95cdd1a18f4d9ca663f832 Signed-off-by: Fiete Ostkamp <Fiete.Ostkamp@telekom.de>
Diffstat (limited to 'README.md')
-rw-r--r--README.md140
1 files changed, 140 insertions, 0 deletions
diff --git a/README.md b/README.md
new file mode 100644
index 0000000..5aa1733
--- /dev/null
+++ b/README.md
@@ -0,0 +1,140 @@
+# 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
+
+ # Kafka consumer group.
+ ml.distribution.CONSUMER_GROUP=aai-ml-group
+
+ # Kafka 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 Kafka topic for new model events
+ ml.distribution.POLLING_INTERVAL=<integer>
+
+ # 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
+ 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
+
+ # 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.