-------------------- To be finished --------------------
This guide is geared to provide information regarding how to do service design to automate instantiation and day0 configuration.
Installation
ONAP is meant to be deployed within a Kubernetes environment. Hence, the de-facto way to deploy CDS is through Kubernetes.
ONAP also package Kubernetes manifest as Chart, using Helm.
Prerequisite
https://docs.onap.org/en/latest/guides/onap-developer/settingup/index.html
Setup local Helm
Get the chart
Make sure to checkout the release to use, by replacing $release-tag
in bellow command
Install CDS
Result
Design time
Bellow are the requirements to enable automation for a service within ONAP.
For instantiation, the goal is to be able to automatically resolve all the HEAT/Helm variables, called cloud parameters.
For post-instantiation, the goal is to configure the VNF with initial configuration.
Prerequisite
Gather the cloud parameters:
Have the HEAT template along with the HEAT environment file.
or
Have the Helm chart along with the Values.yaml file
(CDS supports, but whether SO → Multicloud support for Helm/K8S is different story)
or
...
Have the configuration template to apply on the VNF.
- XML for NETCONF
- JSON / XML for RESTCONF
- not supported yet - CLI
- JSON for Ansible [not supported yet]
- Identify which template parameters are static and dynamic
Create and fill-in the a table for all the dynamic values
While doing so, identify the resources using the same process to be resolved; for instance, if two IPs has to be resolved through the same IPAM, the process the resolve the IP is the same.
Here are the information to capture for each dynamic cloud parameters
Data dictionary
For each unique identified dynamic resource, along with all their ingredients, we need to create a data dictionary.
Here are the modeling guideline: Modeling Concepts#resourceDefinition-modeling
Bellow are examples of data dictionary
Value will be pass as input.
{ "tags": "unit-number", "name": "unit-number", "property": { "description": "unit-number", "type": "string" }, "updated-by": "adetalhouet", "sources": { "input": { "type": "source-input" } } }
Value will be defaulted.
{ "tags": "prefix-id", "name": "prefix-id", "property" :{ "description": "prefix-id", "type": "integer" }, "updated-by": "adetalhouet", "sources": { "default": { "type": "source-default" } } }
Value will be resolved through REST.
Modeling reference: Modeling Concepts#rest
In this example, we're making a POST request to an IPAM system with no payload.
Some ingredients are required to perform the query, in this case, $prefixId
. Hence It is provided as an input-key-mapping
and defined as a key-dependencies.
Please refer to the modeling guideline for more in depth understanding.
As part of this request, the expected response will be as bellow. What is of interest is the address
field, as this is what we're trying to resolve.
To tell the resolution framework what is of interest in the response, the path
property can be used, which uses JSON_PATH, to get the value.
{ "tags" : "oam-local-ipv4-address", "name" : "create_netbox_ip", "property" : { "description" : "netbox ip", "type" : "string" }, "updated-by" : "adetalhouet", "sources" : { "primary-config-data" : { "type" : "source-rest", "properties" : { "type" : "JSON", "verb" : "POST", "endpoint-selector" : "ipam-1", "url-path" : "/api/ipam/prefixes/$prefixId/available-ips/", "path" : "/address", "input-key-mapping" : { "prefixId" : "prefix-id" }, "output-key-mapping" : { "address" : "address" }, "key-dependencies" : [ "prefix-id" ] } } } }
primary-aai-data via type source-rest
TBD
{ "name" : "primary-aai-data", "tags" : "primary-aai-data", "updated-by" : "Steve, Siani <steve.djissitchi@bell.ca>", "property" : { "description" : "primary-aai-data", "type" : "string" }, "sources" : { "default": { "type": "source-default", "properties": { } }, "input": { "type": "source-input", "properties": { } }, "primary-aai-data" : { "type" : "source-rest", "properties": { "type": "JSON", "url-path": "$aai-port/aai/v14/network/generic-vnfs/generic-vnf/$vnf-id", "path": "", "input-key-mapping": { "aai-port": "port", "vnf-id": "vnf-id" }, "output-key-mapping": { }, "key-dependencies": [ "port", "vnf-id" ] } } } }
Value will be resolved through a database.
Modeling reference: Modeling Concepts#sql
In this example, we're making a SQL to the primary database.
Some ingredients are required to perform the query, in this case, $vfmoudleid
. Hence It is provided as an input-key-mapping
and defined as a key-dependencies.
Please refer to the modeling guideline for more in depth understanding.
As part of this request, the expected response will be as put in value
. In the output-key-mapping
section, that value will be mapped to the expected resource name to resolve.
{ "name": "vf-module-type", "tags": "vf-module-type", "property": { "description": "vf-module-type", "type": "string" }, "updated-by": "adetalhouet", "sources": { "primary-db": { "type": "source-primary-db", "properties": { "type": "SQL", "query": "select sdnctl.demo.value as value from sdnctl.demo where sdnctl.demo.id=:vfmoduleid", "input-key-mapping": { "vfmoduleid": "vf-module-number" }, "output-key-mapping": { "vf-module-type": "value" }, "key-dependencies": [ "vf-module-number" ] } } } }
Value will be resolved through the execution of a script.
Modeling reference: Modeling Concepts#Capability
In this example, we're making use of a Python script.
Some ingredients are required to perform the query, in this case, $vf-module-type
. Hence It is provided as a key-dependencies.
Please refer to the modeling guideline for more in depth understanding.
As part of this request, the expected response will set within the script itself.
{ "tags": "interface-description", "name": "interface-description", "property": { "description": "interface-description", "type": "string" }, "updated-by": "adetalhouet", "sources": { "capability": { "type": "source-capability", "properties": { "script-type": "jython", "script-class-reference": "Scripts/python/DescriptionExample.py", "instance-dependencies": [], "key-dependencies": [ "vf-module-type" ] } } } }
The script itself is as bellow.
The key is to have the script class derived from the framework standards.
In the case of resource resolution, the class to derive from is AbstractRAProcessor
It will give the required methods to implement: process
and recover
, along with some utility functions,
such as set_resource_data_value
or addError
.
These functions either come from the AbstractRAProcessor
class, or from the class it derived from.
If the resolution fail, the recover method will get called with the exception as parameter.
Value will be resolved through REST., and output will be a complex type.
Modeling reference: Modeling Concepts#rest
In this example, we're making a POST request to an IPAM system with no payload.
Some ingredients are required to perform the query, in this case, $prefixId
. Hence It is provided as an input-key-mapping
and defined as a key-dependencies.
Please refer to the modeling guideline for more in depth understanding.
As part of this request, the expected response will be as bellow.
What is of interest is the address
and id
fields. For the process to return these two values, we need to create a custom data-type, as bellow
The type of the data dictionary will be dt-netbox-ip
.
To tell the resolution framework what is of interest in the response, the output-key-mapping section is used. The process will map the output-key-mapping to the defined data-type.
{ "tags" : "oam-local-ipv4-address", "name" : "create_netbox_ip", "property" : { "description" : "netbox ip", "type" : "dt-netbox-ip" }, "updated-by" : "adetalhouet", "sources" : { "primary-config-data" : { "type" : "source-rest", "properties" : { "type" : "JSON", "verb" : "POST", "endpoint-selector" : "ipam-1", "url-path" : "/api/ipam/prefixes/$prefixId/available-ips/", "path" : "", "input-key-mapping" : { "prefixId" : "prefix-id" }, "output-key-mapping" : { "address" : "address", "id" : "id" }, "key-dependencies" : [ "prefix-id" ] } } } }
Workflows
The following workflows are contracts established between SO, SDNC and CDS to cover the instantiation and the post-instantiation use cases.
Please refer to the modeling guide to understand workflow concept: Modeling Concepts#workflow
resource-assignment
This action is meant to assign resources needed to instantiate the service, e.g. to resolve all the cloud parameters.
Also, this action has the ability to perform a dry-run, meaning that result from the resolution will be made visible to the user.
If user is fine with the result, he can proceed, else, (TDB) he will have opportunity to re-trigger the resolution.
Context
This action is triggered by Generic-Resource-API (GR-API) within SDNC as part of the AssignBB orchestrated by SO.
It will be triggered for the service, and each VNF(s) and VF-Module(s) (referred as entity bellow).
See SO Building blocks Assignment.
Steps
This is a single action type of workflow, hence the target will refer to a node_template of type component-resource-resolution
Inputs
Property | Description |
---|---|
artifact-name | This action will require resource accumulator templates for each VNF and VF-Module; this will be covered during the User Guide component explanation. These templates are identified using artifact prefix. See Modeling Concepts#template So in order to know for which entity the action is triggered, this is required as input is required. |
resolution-key | The dry-run functionality requires the ability to retrieve the resolution that has been made later point in time in the process. The combination of the artifact-name and the resolution-key will be used to uniquely identify the result. |
Output
In order to perform dry-run, it is necessary to provide the meshed resolved template as output. To do so, the use of Modeling Concepts#getAttribute expression is required.
Also, as mentioned here Modeling Concepts#resourceResolution, the resource resolution component node will populate an attribute named assignment-params with the result.
Example
Here is an example of the resource-assignment workflow:
{ "workflows": { "resource-assignment": { "steps": { "resource-assignment-process": { "description": "Resource Assign Workflow", "target": "resource-assignment-process" } }, "inputs": { "artifact-name": { "required": true, "type": "string" }, "resolution-key": { "required": true, "type": "string" }, "resource-assignment-properties": { "description": "Dynamic PropertyDefinition for workflow(resource-assignment).", "required": true, "type": "dt-resource-assignment-properties" } }, "outputs": { "dry-run": { "type": "json", "value": { "get_attribute": [ "SELF", "assignment-params" ] } } } } } }
config-assign
This action is meant to assign all the resources and mesh the templates needed for the configuration to apply during post-instantiation (day0 config).
If user is fine with the result, he can proceed, else, (TDB) he will have opportunity to re-trigger the resolution.
Context
This action is triggered by SO after the AssignBB has been executed for Service, VNF and VF-Module. It corresponds to the ConfigAssignBB.
See SO Building blocks Assignment.
Steps
This is a single action type of workflow, hence the target will refer to a node_template of type component-resource-resolution
Inputs
Property | Description |
---|---|
resolution-key | The dry-run functionality requires the ability to retrieve the resolution that has been made later point in time in the process. The combination of the artifact-name and the resolution-key will be used to uniquely identify the result. |
Output
In order to perform dry-run, it is necessary to provide the meshed resolved template as output. To do so, the use of Modeling Concepts#getAttribute expression is required.
Also, as mentioned here Modeling Concepts#resourceResolution, the resource resolution component node will populate an attribute named assignment-params with the result.
Example
Here is an example of the config-assign workflow:
{ "workflows": { "config-assign": { "steps": { "config-assign-process": { "description": "Config Assign Workflow", "target": "config-assign-process" } }, "inputs": { "resolution-key": { "required": true, "type": "string" }, "config-assign-properties": { "description": "Dynamic PropertyDefinition for workflow(config-assign).", "required": true, "type": "dt-config-assign-properties" } }, "outputs": { "dry-run": { "type": "json", "value": { "get_attribute": [ "SELF", "assignment-params" ] } } } } } }
config-deploy
This action is meant to push the configuration templates defined during the config-assign step for the post-instantiation.
This action is triggered by SO during after the CreateBB has been executed for all the VF-Modules.
Context
This action is triggered by SO after the CreateVnfBB has been executed. It corresponds to the ConfigDeployBB.
See SO Building blocks Assignment.
Steps
This is a single action type of workflow, hence the target will refer to a node_template of type component-netconf-executor or component-jython-executor or component-restconf-executor.
Inputs
Property | Description |
---|---|
resolution-key | Needed to retrieve the resolution that has been made earlier point in time in the process. The combination of the artifact-name and the resolution-key will be used to uniquely identify the result. |
Output
SUCCESS or FAILURE
Example
Here is an example of the config-deploy workflow:
{ "workflow": { "config-deploy": { "steps": { "config-deploy": { "description": "Config Deploy using Python (Netconf) script", "target": "config-deploy-process" } }, "inputs": { "resolution-key": { "required": true, "type": "string" }, "config-deploy-properties": { "description": "Dynamic PropertyDefinition for workflow(config-deploy).", "required": true, "type": "dt-config-deploy-properties" } } } } }