PTL: Martin Skorupski

H release highlights/accomplishments (<date>):(2023-06-15):

• update of OAM-Controller to ODL version Sulfur
• support of SMO team and the aligmened of requiremnets acorss several open-source projects. 
• Updates according to O-RAN Operations and Maintenance Interface Specification 8.0 (O-RAN.WG10.O1-Interface.0-v08.00)    October 2022
  • Please see H-Release for further details
• Hardening the solution by introducing a "SMO-gateway"
  • all components exposing http northbound are reachable by FQDN (https port 443)
  • the OAM-Controller components interfacing with the network can be reached also by FQDN (VES-http: 443, SSH-Callhome: 4334, TSL-Callhome 4335)
• Add a FlowManagement Component
  • which includes examples for ONAP-VES, StndDefined-VES with 3GPP-Body and StndDefined-VES with WG4-OFHM-body

H release source code, container images and deployment instructions (and status)

Jira: Count of Epics ( 15 issues ), User Stories, Tasks, and Issues:  166 issues

Source Code:

• OAM master
• OAM Controller features master
• ONAP VES Collector master

Integration:

• helm charts
• docker-compose

PTL: Alex Stancu

Jira: Count of Epics, User Stories, Tasks, and Issues:  5 issues

H release highlights/accomplishments (15 Dec 2022 ):23 Jun 2023 ):

• Updated simulated O-RU YANG models according to latest release (March 2023) OpenFronthaul Management Plane specification
• Implement the Monitoring NETCONF connectivity feature for the O-RUs, according to chapter 6.7 (Monitoring NETCONF connectivity) in O-RAN.WG4.MP.0-R003-v11.00
• Created a mechanism to locally build simulated O-DU with 3GPP YANG modelsTODO

H release source code, container images and deployment instructions

Source code:

• TODO

Container images are described TODO-link.

Instructions: no specific instructions.

Code coverage: in progress (sonar for C/C++ code in LF repos)

H release highlights/accomplishments:

• Diversify training data source for Training host
  • Obtaining training data from DME in Non-RT RIC 
  • Creating Feature groups with data source and feature information

• Kserve adapter

  • Deploy and manage AI models in Near-RT RIC/Non-RT RIC

  • Integrate Inference host with O-Cloud( RICDMS ) and Management Functions of RIC. 

• Training pipeline Enhancement

  • Provide sample pipelines by default

• AIMLFW feature enhancements
  • Options for edit, retrain and delete training jobs 

EPICs considered for H-release:

PTL: Joseph Thaliath 

Wiki: AI/ML Framework

Tasks / Backlog / JIRA:  https://jira.o-ran-sc.org/projects/AIMLFW/issues

Gerrit / Code:

• aiml-fw/awmf/tm:  Training Manager : Training job and model management
• aiml-fw/athp/tps/kubeflow-adapter: Adapter for Kubeflow
• aiml-fw/athp/sdk/model-storage: Sdk for accessing Model storage
• aiml-fw/athp/sdk/feature-store: Sdk for accessing Feature store
• aiml-fw/athp/data-extraction: Retrieving features for training from Data lake
• aiml-fw/aimlfw-dep: Deployment scripts aiml workflow 
• portal/aiml-dashboard: GUI for AIML Workflow
• ric-app/qp-aimlfw: Sample ML Assist xApp for QoE prediction
• aiml-fw/aihp/ips/kserve-adapter: kserve adapter for near-RT RIC

Sonar / Test Coverage Reports:

• https://sonarcloud.io/project/overview?id=o-ran-sc_aiml-fw-athp-tps-kubeflow-adapter
• https://sonarcloud.io/project/overview?id=o-ran-sc_aiml-fw-athp-sdk-feature-store
• https://sonarcloud.io/project/overview?id=o-ran-sc_aiml-fw-athp-sdk-model-storage
• https://sonarcloud.io/project/overview?id=o-ran-sc_aiml-fw-athp-data-extraction
• https://sonarcloud.io/project/overview?id=o-ran-sc_aiml-fw-awmf-tm