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Table of Contents
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Overview

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What is this release trying to address?

This release of OOF addresses a core ONAP requirement, which is Homing/Placement of VNFs and Services (VNF Homing Capability). Placement and allocation of resources is one of the fundamental requirements of provisioning a service over the cloud (or even non-cloud) infrastructure. OOF-HAS is a policy-driven placement optimizing service (or homing service) that allows ONAP to deploy services automatically across multiple sites and multiple clouds. It enables placement based on a wide variety of policy constraints including capacity, location, platform capabilities, and other service specific requirements. More details on HAS can be found here: Homing and Allocation Service (HAS). This release also provides the Optimization Design framework (runtime) that supports the Homing Optimizer. 

Use Cases

• Targeted goal in R2:
  • Use Case: Residential Broadband vCPE (Approved)
  • Hardware Platform Enablement In ONAP
• Stretch goal in R2:
  • Use Case: VoLTE(approved)
  • Use Case Proposal: Scale Out

While homing is critical to almost all use cases, we primarily focus on the Residential vCPE use case for the Beijing release. For these use cases, homing would be required during the Generic Service Instantiation Flow (Generic Service.png), where the SO would call HAS for homing right after the service decomposition block. More details on the homing requirements for the vCPE use case, including the API interactions can be found here: vCPE Homing Use Case.

We are currently working on defining similar requirements and workflows for the VOLTE use case as well. Some initial discussions on where and how homing would be integrated in the instantiation workflow for the VOLTE use case can be found in the comments section here: Use Case: VoLTE(approved).

Minimum Viable Product

• OOF-HAS - Homing Service (runtime) that can be provides optimized placement based on policy constraints, across multiple clouds and multiple sites. 
• OOF-OSDF - Optimization Design framework (runtime) that supports HAS, the Homing Optimizer. 

Functionalities

List the functionalities that this release is committing to deliver by providing a link to JIRA Epics and Stories. In the JIRA Priority field, specify the priority (either High, Medium, Low). The priority will be used in case de-scoping is required. Don't assign High priority to all functionalities.

Epics

Stories

ONAP Optimization Framework (OOF) provides the ability to create and run a policy-driven optimization application in a declarative, model-driven matter via the Optimization Service Design Framework (OSDF). The OSDF builds upon seed code from AT&T by bringing in new optimization technologies identified via collaborative efforts to provide a declarative, model-driven optimization framework. The OSDF also supports integration with custom coded optimization applications. Additionally, the OOF includes the Homing and Allocation Service (HAS) component, which again is builds upon seed code from AT&T, and addresses a core ONAP requirement, Homing/Placement of VNFs and Services (VNF Homing Capability).

The Beijing release is the first release of the OOF project and has the following key objectives:

1. Support minimum viable ONAP use cases for Homing/Placement of VNFs and Services via the Homing and Allocation Service
2. Demonstrate the declarative, model-driven functionality of OSDF via representative applications aligned with ONAP use cases

3. Provide a library of OSDF components/adapters for building new optimization applications

4. Ensure compliance with platform maturity requirements

Additionally, the following stretch goals and foundations for longer term are also being pursued:

1. Provide foundations of components required to support broader use cases that are targeted for R2+
2. Pursue exploratory efforts that are in the scope of near-term and longer-term OOF objectives

Detailed Description 

Additional details for the initial objectives are as follows:

1. Support minimum viable ONAP use cases for Homing/Placement of VNFs and Services via the Homing and Allocation Service
   Specific homing/placement use cases identified for this release are:
   1. Residential Broadband vCPE use case
   2. Hardware Platform Enablement (HPA) in ONAP
   3. VNF scale out use case
2. Demonstrate the declarative, model-driven functionality of OSDF via representative applications aligned with ONAP use cases
   This will be done through a simple example mimicking Change Management Scheduling Optimization use case (this effort is aligned with the requirements of the broader CMSO use case). Additional examples are also being pursued, but are slated as stretch goals. The example will also demonstrate the ability to inject new types of constraints at run-time via policy (thus, in many cases, be able to inject advanced functionality into the optimization application without changing the model or configuration).
3. Provide a library of OSDF components/adapters for building new optimization applications
   Beyond the adapters for Policy, AAI, MultiCloud, and SDC, additional focus will be on the incorporation of runtime metrics from MultiCloud for adaptive workload optimization
4. Ensure compliance with platform maturity requirements
   This will be done by meeting or exceeding minimum requirements for projects in Beijing release.
   

The following items constitute “stretch goals” and “foundations towards real goals”

1. Provide foundational components required to support broader use cases targeted for R2+
   The objective is build “foundations" of components that will be developed and be ready for integration with applications supporting broader use cases such as:
   1. VoLTE use case
   2. 5G family of use cases
   3. Broader CMSO use case
2. Pursue exploratory efforts that are in the scope of near-term and longer-term OOF objectives
   We have identified some general features that we believe will be required in the near-term to longer term (timeframe or two or three releases in the future). However, the core OOF group will be focusing on the ONAP release deliverables and will not be able to spend substantial development effort on these items. Fortunately, these appear to align well with recent advances pursued by the broader optimization community. So, initially, we will pursue these via engaging the broader optimization community to contribute ideas and models. Specific features of interest currently are: 
   1. General algorithms for addressing uncertain data
   2. Robust scheduling under uncertainty
   3. Optimization of resource allocation when only approximate/averaged metrics are available

Use Cases

• Targeted goal in R2:
  • Use Case: Residential Broadband vCPE (approved)
  • Hardware Platform Enablement In ONAP
  • Use Case: VNF scale out (and potentially service scale out)
• Stretch goal in R2:
  • Use Case: VoLTE (approved)
  • 5G family of use cases
  • Broader CMSO use case

Minimum Viable Product

• OOF-HAS - Homing Service (runtime) that can be provides optimized placement based on policy constraints, across multiple clouds and multiple sites
• OOF-OSDF - Optimization Design framework (runtime) that supports HAS, the Homing Optimizer

• Application demonstrating a declarative, model-driven, and policy-driven basic CMSO functionality (this effort is aligned with broader CMSO use case)

• HPA functionality integration into OOF
• Integration with Multi Cloud (incorporation of runtime metrics)

Functionalities

List the functionalities that this release is committing to deliver by providing a link to JIRA Epics and Stories. In the JIRA Priority field, specify the priority (either High, Medium, Low). The priority will be used in case de-scoping is required. Don't assign High priority to all functionalities.

Epics

Stories

Longer term roadmap

As the ONAP platform matures and new capabilities are introduced over time, the need for platform optimization services will grow along with it. The ONAP Optimization Framework is envisioned to handle this need as effectively as possible, by enabling creation of new optimization services with minimal or little new code development. The goal of OOF is to provide

(i) a growing set of core platform optimization services such as VNF placement and resource allocation (OOF-HAS), change management scheduling (OOF-CMSO), etc. 

(ii) a framework  (OOF-OSDF) that allow users to construct new optimization services and to extend/enhance existing platform optimization services.

Vision for OSDF:

OOF-OSDF is envisioned to be a collection of design time optimization libraries along with reusable runtime tools and microservices to facilitate and simplify the creation of new specific runtime optimization functionalities. The goal of OSDF is to avoid siloed optimization tools and associated duplicated efforts and overheads. For instance, the Homing Service, HAS (which is targeted for Beijing release) will not only contribute its reusable components to the framework, but also leverages the framework in its own feature development. Other potential optimization services that can be built using this framework include energy optimization in networks, optimal route selection for various network services, and radio access network (RAN) performance optimization. 

Vision for HAS:

OOF-HAS, or the Homing Service is a distributed resource broker that enables automated policy-driven optimized placement of services on a global heterogeneous platform using ONAP. HAS is architected as an extensible homing service that can accommodate a growing set of homing objectives, policy constraints, data sources and placement algorithms.

Longer term roadmap

As the ONAP platform matures and new capabilities are introduced over time, the need for platform optimization services will grow along with it. The ONAP Optimization Framework is envisioned to handle this need as effectively as possible, by enabling creation of new optimization services with minimal or little new code development. The goal of OOF is to provide

(i) a growing set of core platform optimization services such as VNF placement and resource allocation (OOF-HAS), change management scheduling (OOF-CMSO), etc. 

(ii) a framework  (OOF-OSDF) that allow users to construct new optimization services and to extend/enhance existing platform optimization services.

Vision for OSDF:

OOF-OSDF is envisioned to be a collection of design time optimization libraries along with reusable runtime tools and microservices to facilitate and simplify the creation of new specific runtime optimization functionalities. The goal of OSDF is to avoid siloed optimization tools and associated duplicated efforts and overheads. For instance, the Homing Service, HAS (which is targeted for Beijing release) will not only contribute its reusable components to the framework, but also leverages the framework in its own feature development. Other potential optimization services that can be built using this framework include energy optimization in networks, optimal route selection for various network services, and radio access network (RAN) performance optimization. 

Vision for HAS:

OOF-HAS, or the Homing Service is a distributed resource broker that enables automated policy-driven optimized placement of services on a global heterogeneous platform using ONAP. HAS is architected as an extensible homing service that can accommodate a growing set of homing objectives, policy constraints, data sources and placement algorithms. It is service-agnostic by design and can easily onboard new services with minimal effort. HAS is designed to be used as a building block for both initial deployment, as well as runtime redeployment due to failures or runtime-capacity increase (scale-out). While the immediate deliverable of HAS in Beijing Release is to provide optimized homing/placement of services during the service instantiation workflows in ONAP,  HAS naturally extends to a general policy-driven optimizing placement platform for all platform placement functions, including placements of VMs, containers (e.g., for DCAE micro-services), ONAP Control Loops or VNF specific resources. HAS will also eventually allow placements of additional resource types such as licenses, VNF resources, etc.

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Sub-Components

• OOF-HAS - Homing Service that can be provides optimized placement based on policy constraints, across multiple clouds and multiple sites. 
• OOF-OSDF - Optimization Design framework that helps create new types of policy- and model-driven applications. It also supports optimization modules that use custom code for solving the optimization problem. The OOF-OSDF also supports HAS, the Homing Optimizer

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Third Party Products Dependencies

Third Party Products mean products that are mandatory to provide services for your components. Development of new functionality in third party product may or not be expected.
List the Third Party Products (OpenStack, ODL, RabbitMQ, ElasticSearch,Crystal Reports, ...).

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(OpenStack, ODL, RabbitMQ, ElasticSearch,Crystal Reports, ...).

In case there are specific dependencies  (Centos 7 vs Ubuntu 16. Etc.) list them as well.

Testing and Integration Plans

The following testing will be ensured for OOF in this release:

• Unit Tests and Code Coverage: We will use Python testing frameworks (combination of unittest, nose and coverage.py modules). We will work with our collaborators from MultiCloud who have used a similar ecosystem for their project.
• Continuous System Integration Testing (CSIT): We will develop Robot Framework scripts for in Robot Framework.
• Functional Test cases: OOF will be tested according to a small but representative test cases covering specific “concrete” optimization scenarios. These test cases will be documented in detail

In case there are specific dependencies  (Centos 7 vs Ubuntu 16. Etc.) list them as well.

Testing and Integration Plans

The following type of tests will be ensured for OOF in this release:

• Unit tests: Unit tests will be added incrementally as part of code delivery ensuring static code analysis as recommended by common SW delivery practices. OOF is written in Python, so coverage target percentage will be evaluated along project. Unit Tests will be automated, so that execution will happen before every OOF delivery. This includes writing test cases for the new components and those for the existing ones not yet covered under unit testing. A python based Unit Testing framework will be integrated into the project, binding all developers to start with Unit Tests when developing each module.
• CSIT Test cases: OOF will be integrated following Continuous System Integration Testing test cases practice. This will ensure both Sanity test cases execution and Functional Test execution (details are provided in further chapters here below). CSIT test cases will be executed integrating OOF with Robot Framework and Jenkins.
• Functional Test cases: OOF will be tested according to specific “concrete” optimization scenarios committed as “functional” part of OOF delivery. In particular vCPE optimization has been identified as concrete scenario, so a dedicated test suite will be set up to verify expectations are met. This will imply a proper set of simulators will be available to fulfill the whole vCPE optimization flow: Policy simulator, AAI simulator, SDNC Simulator, Music Simulator. for vCPE management. Functional test cases (or a meaningful subset) will be part of CSIT Test cases. 
• End to End Test cases:  OOF We will be integrated within the whole ONAP components architecture and dedicated set of E2E test cases will be setup. Purpose, scope and details on E2E testing will be planned/defined subsequently by working with the Integration team, and for the test cases in the scope of this releaseadapt the Robot Framework scripts in consulation with the integration team.  

Gaps

This section is used to document a limitation on a functionality or platform support. We are currently aware of this limitation and it will be delivered in a future Release.
List identified release gaps (if any), and its impact.

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