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9 DCAE MOD is composed of a mix of components developed in ONAP and other
10 components taken from the Apache Nifi project and modified for
11 appropriate use. The MOD architecture and design was intended to simplify the onboarding
12 and design experience in ONAP addressing below goals.
20 MOD aims to streamline the construction, management,
21 and evolution of DCAE flows from role to role, from environment to
22 environment, and from release to release. MOD is composed of three functional areas: onboarding, design, and
23 distribution and caters to different `user group <./Roles>`__
26 The below illustrations describe the architecture of DCAE-MOD and show the
27 usage flow in DCAE MOD
36 It is a component developed to onboard
37 models/components/microservices (spec files) into DCAE MOD.
42 It has been developed in Java. This project is a tool to
43 experiment with generating a Nifi Processor POJO from a DCAE component
49 It is a component taken from the Apache Nifi Project but modified for
50 use in the MOD project.
52 Apache NiFi is a dataflow system based on the concepts of flow-based
53 programming. It supports powerful and scalable directed graphs of data
54 routing, transformation, and system mediation logic. NiFi has a
55 web-based user interface for design, control, feedback, and monitoring
56 of dataflows. It is highly configurable along several dimensions of
57 quality of service, such as loss-tolerant versus guaranteed delivery,
58 low latency versus high throughput, and priority-based queuing. NiFi
59 provides fine-grained data provenance for all data received, forked,
60 joined cloned, modified, sent, and ultimately dropped upon reaching its
63 The NiFi UI provides mechanisms for creating automated dataflows, as
64 well as visualizing, editing, monitoring, and administering those
65 dataflows. The UI can be broken down into several segments, each
66 responsible for different functionality of the application. This section
67 provides screenshots of the application and highlights the different
68 segments of the UI. Each segment is discussed in further detail later in
71 The users of Apache Nifi will find that it is used very differently than
72 intended to serve our purpose in the DCAE-MOD project.
78 This component taken from the Apache Nifi project, is a REST API that
79 provides an interface to a registry with operations for saving,
80 versioning, reading NiFi flows and components.
85 It is a component developed using the Flask framework in Python.
86 It is a HTTP API to manage distribution targets for DCAE design.
87 Distribution targets are DCAE runtime environments that have been
88 registered and are enabled to accept flow design changes that are to be
89 orchestrated in that environment.
91 Flow Based Programming (FBP)
92 ----------------------------
94 NiFi’s fundamental design concepts closely relate to the main ideas of
96 Programming `[fbp] <https://nifi.apache.org/docs/nifi-docs/html/overview.html#fbp>`__.
98 For more information on how some of the main NiFi concepts map to FBP,
99 check out https://nifi.apache.org/docs/nifi-docs/html/overview.html
104 It is developed in Java’s Spring Boot framework. It
105 is a HTTP API to support runtime environment for DCAE-MOD. It has two
106 major functionalities:
108 1. It accepts changes on the flow-graph via fbp protocol
110 2. It generates and distributes helm charts OR blueprints based on the change made on
117 New Java module - Helmgenerator-core was introduced for Helm charts
118 generation. MOD/Runtime has been enhanced to include this new dependency
119 (inaddition to Bp-generator for supporting cloudify blueprints flows).
121 Below is snippet from -
122 https://github.com/onap/dcaegen2-platform/blob/master/mod/runtimeapi/runtime-core/pom.xml
127 <groupId>org.onap.dcaegen2.platform</groupId>
128 <artifactId>helmchartgenerator-core</artifactId>
129 <version>1.0.3</version>
136 MOD/Runtime Charts has been modified to include under resources, common
137 base templates, Charts.yaml, add-on templates and Values.yaml with
142 The Helmgenerator-core modules uses these template to pull the required
143 dependencies and generate new chart for MS onboarded. The parameters in
144 component-spec provided during onboarding is used for final Values.yaml
150 The MOD/RuntimeAPI introduces new configuration to identify distribution
151 mechanism. Supported artifactType are **BLUEPRINT** or **HELM. **
153 Blueprint – Distribution to Inventory/Dashboard
155 Helm – Distribution to ChartMuseum
157 For Jakarta release, the charts configuration has been set to support
158 HELM distribution by default and configured for ONAP-internal
159 chart-museum registry. RuntimeAPI Chart updates
160 https://github.com/onap/oom/blob/master/kubernetes/dcaemod/components/dcaemod-runtime-api/values.yaml
165 registryBaseurl: http://chart-museum:80
166 basehelmchartlocation: /helm-gen/
172 This tool allows the user to create a blueprint from a component spec json file.
173 This tool is used by the runtime api when artifactType is set to **BLUEPRINT** under
175 deployment <https://git.onap.org/oom/tree/kubernetes/dcaemod/components/dcaemod-runtime-api/values.yaml#n44>`__
180 This tool allows the user to create a DCAE Services helm chart from a component spec json file.
181 This tool is used by the runtime api when artifactType is set to **HELM** under
183 deployment <https://git.onap.org/oom/tree/kubernetes/dcaemod/components/dcaemod-runtime-api/values.yaml#n44>`__
191 Used only under BLUEPRINT mode
193 DCAE Inventory is a web
194 service that provides the following:
196 1. Real-time data on all DCAE services and their components
198 2. Comprehensive details on available DCAE service types
200 DCAE Inventory is a composite API that relies on other APIs to obtain
201 resources on underlying components and uses these resources to compose a
202 DCAE service resource. In addition, DCAE Inventory will store data that
203 is unique to the DCAE service level including:
205 1. DCAE service metadata
207 2. DCAE service type description and composition details
209 3. Relationships between DCAE service and DCAE service types and their
210 respective VNF and VNF types
212 DCAE Inventory has a REST interface to service client requests. It has a
213 well-defined query interface that would filter result sets based upon
216 Here, think of it as a back end API for the DCAE dashboard. The runtime
217 posts Cloudify Blueprints to this API so they show up in the DCAE
224 Used only under BLUEPRINT mode
226 The DCAE dashboard provides visibility into running DCAE services for
227 operational purposes. It queries the DCAE Inventory for aggregate
228 details on all the running DCAE services and for getting up-to-date
229 status information on DCAE services and their components.
234 A model/component/microservice can be onboarded by a ms Developer by
235 posting a spec file on the onboarding API. Alternatively, an Acumos
236 model can be onboarded using the Acumos Adapter. Once successfully
237 onboarded, the genprocessor converts converts them to jars and onboards
238 them into Nifi i.e DCAE MOD. These artifacts are now available to use
239 from the Modified Nifi Web UI i.e DCAE Designer.
241 The registry api offers version control and retrieval for flows. The
242 distributor api can be used to set distribution targets. Once a flow is
243 designed and distributed, it goes to the distributor api which is
244 supposed to post graph changes (in accordance with fbp) to the runtime
245 api. The runtime api generates and distributes deployment artifacts (either
246 blueprints or helm charts) based on the
247 change made on the flow-graph. The generated blueprints are received by the DCAE
248 inventory can then be viewed and deployed from the DCAE dashboard. On helm mode,
249 charts generated are pushed into configured Chartmuseum registry.
253 .. |image0| image:: ../images/DCAE-Mod-Architecture.png
255 .. |image1| image:: ../images/Onboarding-with-DCAE-MOD.png
257 .. |image2| image:: ../images/nifi-toolbar-components.png
259 .. |image3| image:: ../images/128713731_image2022.png