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O-RAN SC: 'Dawn' of RAN Intelligence What is O-RAN SC?O-RAN Software Community (O-RAN SC) was formed in April 2019 under Linux Foundation, sponsored by the O-RAN Alliance. Focus of O-RAN SC is to deliver open source enabling modular, open, intelligent, efficient, and agile disaggregated Radio Access Network (RAN).“The O-RAN Software Community is a collaboration between the O-RAN Alliance and Linux Foundation with the mission to support the creation of software for the Radio Access Network (RAN). The RAN is the next challenge for the open source community. The O-RAN SC plans to leverage other LF network projects, while addressing the challenges in performance, scale, and 3GPP alignment.” [1]RAN Intelligent Controller Applications (RICAPP), Near-Realtime RAN Intelligent Controller (RIC), Non-RealTime RAN Intelligent Controller (NONRTRIC), Operations and Maintenance (OAM), O-RAN Central Unit (OCU), O-RAN Distributed Unit High Layers (ODUHIGH), O-RAN Distributed Unit Low Layers (ODULOW), Infrastructure (INF), Simulations (SIM), Integration and Testing (INT) are key sub-projects that constitute the O-RAN SC.In August 2021, O-RAN Alliance announced the fourth release of O-RAN SC : “Dawn”. 60+ developers from about 10 companies worked together tirelessly to meet the release deadline for Dawn release with significant contributions to all the sub-projects [2]. Dawn release includes major enhancement to SMO (Service Management and Orchestration), ODUHIGH, SIM, and OAM projects to support “closed-loop automation” usecase. This usecase demonstrates the end-to-end automation of configuration and monitoring for any network events. Also there was a strong focus to harden the platform by complying with the Linux Foundation Core Infrastructure Initiative (CII) Best Practices Badging Program, which has emerged as one of popular and authorized barometers to guarantee the best practice “Open Source” in terms of its code review process, governance, security management, DevOps and so on. Most of the sub-projects completed the CII badging criteria to meet basic “passing” grade in this release. Overall, this release has been a stepping-stone to bring RAN innovation and openness on a secure platform and has also laid the framework for rApps (running on top of non-RT RIC platform) and xApps (running on top of near-RT RIC platform) development. Details for the D release can be found at O-RAN SC site [3].What is Samsung’s contribution in O-RAN SC?Samsung has been actively contributing into the O-RAN SC since 2019 with significant contributions to the RIC and RICAPP projects. Samsung contributors also hold a committer position in seven repositories (e2mgr[4], e2[5], a1[6], nodeb-rnib[7], hw-go[8], hw-python[9] and libe2ap [10]). Subhash Kumar Singh from Samsung Research India Bangalore is one of the top contributors (overall 12th position) in O-RAN SC and is holding the committer role for few key repositories related to RIC platform.Figure. The number of commits by organizations (counted since 21/01/01 to 21/08/25)Dr. Sunghyun Choi, Corporate SVP and Head of Advanced Communications Research Center, Samsung Research, Samsung Electronics, quoted in the official O-RAN SC press release about the focus and vision of Samsung’s contribution [11]."Making the RAN intelligent and context-aware is critically important for network optimization and automation. The focus of Samsung's O-RAN SC contribution has been towards enhancing the A1-Enrichment Information (A1-EI) & xApp Framework. Overall, we believe that strengthening the O-RAN AI/ML Framework will play a big role in making operators achieve proactive closed-loop optimization and automation of RAN operations."The near-RT RIC platform is a very critical component in O-RAN architecture for bringing intelligence to RAN. On top of the near-RT RIC platform, developers can build their own applications xApp to optimize network parameters by utilizing the data and the machine-learning (ML) framework provided by the platform. The accuracy of an ML algorithm is largely dependent on the number of data points that are available. Based on the use case, xApps might need information that is outside the purview of the RAN but has significant impact on the overall network performance, e.g., weather conditions. In this release, we focussed to implement A1-EI interface at near-RT RIC as per the specification provided by O-RAN Alliance. This feature will enable xApps to consume enrichment information from external source, which when used in conjunction with the data from the network should improve the accuracy of the prediction algorithm and in turn promote the usage of predictive closed-loop automation for RAN optimization. Additionally, the python libraries related to the xApp framework were improved to support an ML framework that can be used by xApp developers to apply ML Algorithms to RAN control.Further in this release, O2 interface implemented as per the WG6 use case “Deploy xApp in near-RT RIC” in O-RAN Orchestration Use Cases v2.0. Now, xApp initiates registration on its startup. We improved the python framework to support the registration on startup. To make the encoding and decoding of E2AP v1.0 messages more simplified by introducing message structure and wrappers in libe2ap repository. As our focus we have also improved KPIMON xApp to implement E2SM KPM 2.0.3, which is recently approved by O-RAN Alliance. New E2SM model will include new KPI parameter and expose those details to RIC to bring new innovation and ideas. We are also focussed to promote O-RAN SC as developer friendly by bringing reference xApps (Hw-go and Hw-python). xApp developers can refer to it in order to get familiarized with the features of xApp framework and start building new apps for RAN-related decision.Our developers are paving path towards enabling RAN intelligence with consistent contributions to the O-RAN SC RIC & RICAPP projects . Following contributors from Samsung have been very active in the O-RAN SC:- Subhash Kumar Singh (Senior Chief Engineer at Samsung R&D Institute India-Bangalore)- Naman Gupta (Senior Engineer at Samsung R&D Institute India-Bangalore)- Heewon Park (Engineer at Samsung Research)- YoungCheol Jang (Engineer at Samsung Research)- JinWei Fan (Senior Professional at Samsung R&D Institute China-Beijing)- Jeongyeob Oak (Staff Engineer at Samsung Electronics Networks Business)- Timothy Ebido (Staff Engineer at Samsung Research)While the O-RAN SC near-RT RIC platform has AI/ML capabilities, the realisation of a complete AI/ML workflow (as defined in the O-RAN Alliance WG2) would require additional components for the model training such as ML designer and ML training host. It also requires ML model serving frameworks to deploy inference service and inference optimization to reduce latency with efficient resource utilization. The Advance Solution Team at Samsung Research in collaboration with Samsung Research India Bangalore is working on building this end-to-end workflow by utilizing various open source projectsWhat are the next step?The E Release of O-RAN SC is currently in the planning phase and scheduled for December 2021. In this release, we can expect to see new xApps, usecases, and more mature platform to lead industry towards open, intelligent, secure, and fully interoperable RAN. On the end-to-end AI/ML framework front, we plan to demonstrate the capabilities of the framework with practical usecases that can help operators realise the true potential of predictive closed-loop automation.Reference[1] https://o-ran-sc.org/[2] https://insights.lfx.linuxfoundation.org/projects/o-ran-f/dashboard[3] https://wiki.o-ran-sc.org/pages/viewpage.action?pageId=20878658[4] https://gerrit.o-ran-sc.org/r/admin/repos/ric-plt/e2mgr[5] https://gerrit.o-ran-sc.org/r/admin/repos/ric-plt/e2[6] https://gerrit.o-ran-sc.org/r/admin/repos/ric-plt/a1[7] https://gerrit.o-ran-sc.org/r/admin/repos/ric-plt/nodeb-rnib[8] https://gerrit.o-ran-sc.org/r/admin/repos/ric-app/hw-go[9] https://gerrit.o-ran-sc.org/r/admin/repos/ric-app/hw-python[10] https://gerrit.o-ran-sc.org/r/admin/repos/ric-plt/libe2ap[11] https://static1.squarespace.com/static/5ad774cce74940d7115044b0/t/611a53ea2436a96c6c7f3a01/1629115370586/O-RAN.EC.August-16-2021-PR.v01.00.pdf* Original Contents : https://research.samsung.com/blog/O-RAN-SC-Dawn-of-RAN-Intelligence#none September 1, 2021
Samsung Research opens CredData on github Samsung Research opens CredData(https://github.com/Samsung/CredData) on github. CredData (Credential Dataset) is a set of files including credentials in open source projects. Unprotected credentials that are shared through code repositories are leading to undesirable incidents such as leakage of personal information. There are several Open Source projects detecting these credentials, but there is no reference dataset to evaluate the tools and very few tools can detect 'password' type. CredData is reference dataset which includes suspicious lines with manual review results and more information such as credential types including 'password' type for each suspicious line. The information that can be used to predict which Open Source projects are included is minimized and actual credentials are obfuscated. CredData can be used to develop new tools or improve the performance of existing tools. Furthermore, Samsung Research also released the benchmark result of the CredData which includes a new tool to be released in October. With the benchmark result, users can choose a proper tool among open source credential scanning tools according to their use case. Details you can find, in here : https://github.com/Samsung/CredData Samsung Research will continue to transparently open vulnerability-related activities. August 18, 2021
Open-Source Project for MPEG-5 EVC (Essential Video Coding) The COVID-19 outbreak has changed our lives and relationships over the past year. We now have no other choice but to communicate more often through the Internet. One of the key technologies for talking via the Internet is, definitely, video compression (coding) technology. However, a very old codec, H.264/AVC, is still the primary technology used in video conference applications, whose standardization was finalized about 20 years ago. Experts had undoubtedly developed a more efficient video codec called HEVC, but it is not dominantly available yet because of its complex license policy or computational complexity issues for video conferences.In June 2021, Samsung Research released an open-source video encoder (XEVE: eXtra-fast Essential Video Encoder, https://github.com/mpeg5/xeve) and decoder (XEVD: eXtra-fast Essential Video Decoder, https://github.com/mpeg5/xevd), which are software implementations of the state-of-the-art video coding standard, MPEG-5 Essential Video Coding (EVC), providing better visual quality for video calls and alleviating the expensive royalty for video codecs.The EVC standard completed by the ISO/IEC Moving Picture Experts Group (MPEG) in April 2020 defines two profiles: (1) the Baseline profile, which is royalty-free as it only consists of technologies that are more than 20 years old, and (2) the Main profile, which contains enhanced tools to improve the compression efficiency. At an equivalent level of visual quality, the Baseline and Main profiles save bit rate by approximately 40% compared to the H.264/AVC and HEVC standards, respectively. For your reference, HEVC saves approximately 40% of the bit rate compared to H.264/AVC.The main purpose of our source code release is to make the MPEG-5 EVC standard more widely and easily used in the industry. For example, the high-performance, commercial-ready, open-source encoder XEVE can be directly deployed to over-the-top (OTT) services without additional development and enable high-quality encoding of video contents. XEVD, a lightweight, open-source decoder, can be directly deployed on embedded devices such as smartphones to play video streams from OTT services. Moreover, XEVE and XEVD can provide improved visual quality and cost-efficient delivery for real-time video conference services, and we believe these services will continue to be popular even after the pandemic.In addition to this effort, Samsung has been striving to adopt the Baseline profile of EVC into the WebRTC standard for real-time video communication on web browsers and mobile applications. Its integration to the WebRTC standard shall prompt better experiences on virtual video communication at a lower cost.* Original Contents : https://research.samsung.com/news/Open-Source-Project-for-MPEG-5-EVC-Essential-Video-Coding July 23, 2021
Engineering Lead at Samsung Research Wins Multiple Top Awards in Robotics Community Samsung Research America’s Open-Source Robotics, Engineering Lead Steve Macenski was awarded by the global Robot Operating System (ROS) community top awards at the 2021 ROS Developer’s Day conference. This is the second year in a row Samsung Research has received awards from the robotics community.Steve Macenski was awarded, for the second consecutive year, the Top Developer Award for his on-going contributions to ROS and ROS2. He is the Technical Steering Committee (TSC) representative for Samsung and leads the community Navigation Working Group. As a core leader in ROS, he focuses on building highly reliable mobile robotics technology, community engagement, and mentorship. This award highlights his continued technical achievements in the field of robotics, including mapping, path planning, control, and architectural innovations. It also speaks to the success of his leadership in building a vibrant community. Steve’s initiatives have resulted in a community containing hundreds of developers, mentoring opportunities, and hundreds of contributions to high impact projects.Further, the community project, Nav2 (formerly known as Navigation2) was awarded the Top Software Award. This project is led by Steve Macenski of Samsung Research America with close collaboration with Alexey Merzlyakov of Samsung Research Russia. This project aims to provide the highest quality mobile robot navigation solution in the world. Today, it supports Ackermann, Differential Drive, Omnidirectional, and Legged robots with a wide range of sensing capabilities. In the last year, innovations in filters, path planning, control, and behavior trees have been made, which are enabling the next generation mobile robots. It is being used by dozens of companies, researchers, and hobbyists all over the world.Samsung Research’s Open Source Group is a leader in the next generation of robotics technology. They focus on developing the missing technologies holding back new and innovative applications of robotics. Further, this work is made to be well documented with guides and tutorials such that they can be easily integrated into any project. This focus on education and community has earned a strong reputation for Samsung in the ROS community. “[Steve’s] work for educational purposes and attitude in promoting robotics are very valuable and remarkable.” said Markus Buchholz, Principle Software Engineer at Canrig Robotics, “Frankly speaking and open minded [people] … help others to grow and live better.”* Original Contents : https://research.samsung.com/news/Engineering-Lead-at-Samsung-Research-Wins-Multiple-Top-Awards-in-Robotics-Community July 23, 2021
Samsung Electronics Adopts International Open Source Standard Samsung Electronics today announced the adoption of OpenChain ISO (International Organization for Standardization) / IEC (International Electrotechnical Commission) 5230:2020, the first international standard for open source compliance. The company joins a growing community of companies in the field of consumer electronics, automotive, cloud computing and telecommunications in using this standard to manage supply chains. The OpenChain Project began in 2016 as an initiative of the Linux Foundation, a non-profit organization in the United States. It aims to establish an effective and consistent open source compliance system. The OpenChain Project was adopted as an ISO / IEC international standard in 2020. The project evaluates each company’s open source compliance capabilities and grants certification if they met the criteria. “Samsung Electronics leads the adoption and use of open source technology to create innovative products,” said Seungbeom Choi, Executive Vice President and Head of R&D Strategy Team at Samsung Electronics. “Underlying this are organizations and processes specifically established to safely and efficiently utilize open source. Our adoption of OpenChain ISO 5230 reflects our ongoing commitment to excellence in our field. Samsung Electronics is expected to enhance its credibility by receiving recognition for its capacity to utilize open source through this certification. We look forward to collaborating with other industry leaders around this standard.” “Open source provides an unmatched platform for innovation,” said Shane Coughlan, General Manager of OpenChain. “To get the most out of this platform, the key is to have effective, efficient processes. OpenChain ISO 5230 delivers this for license compliance activities. We are delighted to welcome Samsung Electronics to our community of conformance. Their leadership in this area will help accelerate our mission throughout the supply chain.” Since 2012, Samsung Research, Samsung Electronics’ advanced R&D hub that leads the development of future technologies for its consumer product business, has been conducting various activities for safe and efficient use of open source with specialized organizations and systems. The company has established a global integrated open source policy with global research institutes, and established a system to identify open source licenses and comply with obligations at the stage of development from software planning to implementation and verification, and have operated online / offline education programs to enhance the understanding of developers.* Original Contents : https://news.samsung.com/global/samsung-electronics-adopts-international-open-source-standard July 16, 2021
[Upcoming event] SOSCON Global India Virtual Open Source Conference (5G, IoT and Edge Computing) :Date: 3rd July 2021Time 8.30 am to 2 pm (IST), 12:00 pm to 5:30 pm(KST)Link to Register : http://bit.ly/ComSoc_July3 Fast emerging technologies such as 5G, IoT, and Edge Computing are changing the landscape of the technology industry and bringing significant value to end consumers. At the same time, open-source platforms are rapidly evolving and playing an important role in meeting the agile demands of the industry. Join us to learn from the industry-leading experts on the value, innovation, and benefits of deploying emerging technologies using open source platforms.You will also learn how to develop and deploy Kubernetes Operator, LF Home Edge and O-RAN SC XApp through developer sessions. June 17, 2021
Open Source Kubernetes for the next level of network virtualization We as Samsung Research have recently presented a research achievement as a global team work with Samsung R&D Institute Poland and Samsung Research America for improving the Kubernetes open source project into the next level of competency in IEEE INFOCOM 2021.What is a background of this research?Container technology has revolutionized the way software is being packaged and run. The telecommunications industry, now challenged with the 5G transformation, views containers as the best way to achieve agile infrastructure that offers high throughput and low latency for 5G edge applications. These challenges make optimal scheduling of performance-sensitive workflows a matter of emerging importance.How to solve this? Do not worry, we have Kubernetes open source project!Kubernetes is a de-facto standard open source project for container orchestration in IT industries and has been deployed to various cloud solutions including AWS, Google, Microsoft, IBM, VMWare, and so on. It is now in Cloud Native Computing Foundation (CNCF) of Linux Foundation, and is a very dynamic project since over 400 commits are being contributed to it every month. Samsung is also contributing various ideas into this project with a collaboration with community members.Okay, we have an open source which is free, but is that enough? It is not so simple.It is only logical that there are also many new capabilities in the scheduling area. Grabowski and Tyczynski described Kubernetes scheduler and its features available as of Kubernetes v1.16 [1]. It is able to execute the same decision tree policy as Google’s Borg does with the proper configuration [2], but it is not the default choice in Kubernetes, so it requires additional operator’s intervention to activate it. Several improvements have been proposed to Kubernetes scheduler to make it more suitable for public cloud, but they are not considering any network metrics, or examining any inter-application relations and node communication delays, or requiring information about the service function chains that is provided manually, which are all crucial in most of telecommunication use cases in terms of high throughput, low latency orchestration operated in a fully automated manner.In addition, the most critical drawback of the existing scheduler enhancement proposals is their incompatibility to the default scheduler of Kubernetes. No matter how excellent the proposed scheduler guarantees, it requires a custom configuration of selectively activating that scheduler for a specific use case – this is a huge blocker in the telecommunication industry in terms of wide deployment of the scheduler solution. When you consider of realizing the better world of technologies with your great idea using open source like Kubernetes, the most important criteria is its generality of deployment in various use cases that in the end should also guarantee compatibility to the existing open source mainstream.So what have we been researching and developing for general deployment of the industries?We design and implement NetMARKS – Kubernetes scheduler extender that uses information collected by Service Mesh to schedule pods based on current network metrics. Our solution does not conflict with current Kubernetes scheduler plugins or other extenders, and it can be used simultaneously with them to ensure backward compatibility. NetMARKS can automatically discover inter-application relations as well as schedule the application in a way to save the inter-node network bandwidth and to reduce the application response delay by extending the default Kubernetes scheduler including network metrics awareness, to ensure an efficient placement of Service Function Chains (SFCs). In this context, we propose a novel approach to collect network metrics for the scheduler using Istio Service Mesh.Kubernetes for a baseline scheduler, but what is Istio and how it works in NetMARKS?Istio has a sidecar-based service mesh design as shown in Fig. 1. This architecture assumes that there is an adjacent container, as a sidecar for every application that acts as a proxy and intercepts all the network traffic. Istio uses a powerful proxy named Envoy [3]. It provides multiple functionalities including mutual TLS, L3/L4 traffic filtering, HTTP L7 filtering and routing, telemetry, and advanced load balancing with circuit breaking and automatic retries. To benefit from those features, Envoy Proxy has to be configured properly and has to be provided with certificates. This is done by istiod, which is an essential part of Service Mesh controlplane that governs all Envoy Proxies. Istio is configured using Kubernetes CRD which allows a user to interact with it using Kubernetes objects.Fig. 1. An architecture of Istio Service Mesh.As Envoy participates in communication between services, it adds some delay to it. Based on [4], Istio generally adds around 3-ms latency for a mesh with 1,000 requests per second across 16 connections. This result can be improved [5] using a Container Network Interface (CNI) plugin, which supports SOCKMAP from the Linux kernel, such as Calico [6] and Cilium [7].As the communication is always intercepted by at least one Envoy Proxy, the traffic can be easily traced and monitored. Every Envoy instance can be configured to collect metrics on the traffic that it is passing. These metrics are further collected and stored by Prometheus [8], which can be deployed as a part of Istio control plane. Users can use the data in multiple ways depending on their needs, e.g. for observability and diagnostics using Kiali [9], which visualizes the structure of mesh and presents flows between components.NetMARKS is intended to be fully backward compatible with kube-scheduler. The most effective way to achieve this is to utilize Kubernetes Scheduler Extension mechanism. Extenders, including NetMARKS, are implemented as separate HTTP services that are contacted by the scheduler whenever a new pod needs to be scheduled. It is assumed that Istio is enabled for all of cluster namespaces, and Prometheus service is deployed as a part of Istio control plane.NetMARKS uses data collected by the Prometheus to make the scheduling decision. It retrieves two metrics from there: istio_request_bytes_sum and istio_response_bytes_sum, which contain the number of bytes that is transferred in requests and responses respectively. The application entity does not exist in Kubernetes, so it is defined by Istio as a set of pods residing in the same namespace and having the same app label.Both requests and responses metrics are summed in (1) to calculate F_(t_1,t_2)^(A,B), which is an average data flow between applications A and B in time period [t_1,t_2 ] in bytes per second. 〖req〗_t^(A,B) is the number of bytes in requests from application A to application B until t in bytes, and 〖resp〗_t^(B,A)- same for responses from B to A, with respect to 〖req〗_t^(A,B).(1)Metrics are collected periodically while keeping the average flow, since the start of data collection using (2).(2)Let F(t_i) be the current flow at a given time t_i, after expanding F_(t_(i-1), t_i)^(A,B) in (2) with (1). Then, its final numerical model can be derived as follows.(3)This data flow metric is used to assess each feasible node that has not been filtered out. The algorithm has two input parameters: a Pod to be scheduled and a Node. Current state of pods assignment to nodes is required to determine where to bind the new Pod, so NetMARKS retrieves this information via Kubernetes API.Operation "Get all traffic neighbors of Pod" selects data flow metrics, where namespace and application label of the Pod match either source or destination of the traffic.The result of the algorithm can be understood as a sum of the traffic bandwidths between the Pod communication peers assigned to the Node. To calculate the Score, the algorithm iterates over all the pods that intersect between a set of pods assigned to the Node and a set of Pod communication partners. Then, it adds the flow data to the final result if namespaces are matched.Scheduling example: Consider 4 applications:- F: farm, producing grain- W: well, producing water- P: pig farm, producing pigs, requiring grain and water- S: slaughter, producing meat, requiring pigsFig. 2 shows relation and traffic flows between applications. Assuming that F, W, and S are already running on nodes, the algorithm calculates the score in order to place pod with P as follows:- Node1: State={F},Score=30+50=80- Node2: State={W},Score=40+70=110- Node3: State={S},Score=60+100=160- Node4: State={},Score=0The node3 receives the highest score, because placing pig farm together with slaughter allows to use intra-node communication, the expected volume of which is bigger than others.Has NetMARKS been validated from rigorous experiments? Yes!!We validated our solution using different workloads and processing layouts. Based on our analysis, NetMARKS can reduce application response time up to 37 percent and save up to 50 percent of inter-node bandwidth in a fully automated manner. This significant improvement is crucial to Kubernetes adoption in 5G use cases, especially for multi-access edge computing and machine-to-machine communication.Publications: https://infocom.info/day/3 ↓(Day3: Containers and Data Centers session “NetMARKS: Network Metrics-AwaRe Kubernetes Scheduler Powered by Service Mesh”)What is the role of Samsung Open Source Group?We have been contributing our idea into various open source projects in technical domains such as telecommunication, IoT, cloud, robotics, artificial intelligence, and so on with various developers across Samsung Electronics and others from various companies and R&D institutes, in order to make the better technical innovation and the bigger ecosystem in an open collaboration. If you are interested in our recent activities, please visit our official website https://opensource.samsung.com/.Reference[1] W. T. Marek Grabowski, “Kubernetes scheduling features or how can i make the system do what i want,” in KubeCon + CloudNativeCon Europe, 2017. ↓[Online]. Available: https://www.youtube.com/watch?v=bbPcb2JuJPw[2] A. Verma, L. Pedrosa, M. R. Korupolu, D. Oppenheimer, E. Tune, and J. Wilkes, “Large-scale cluster management at Google with Borg,” in Proceedings of the European Conference on Computer Systems (EuroSys), Bordeaux, France, 2015.[3] “The envoy proxy.” [Online]. Available: https://www.envoyproxy.io/[4] “Istio performance best practices.” [Online]. ↓Available:https://istio.io/latest/blog/2019/performance-best-practices/[5] N. Kapocius, “Performance studies of kubernetes network solutions,” in 2020 IEEE Open Conference of Electrical, Electronic and Information Sciences (eStream), 2020, pp. 1–6.[6] “Project calico.” [Online]. Available: https://www.projectcalico.org/[7] “Project cilium.” [Online]. Available: https://cilium.io/[8] “The prometheus project.” [Online]. Available: https://prometheus.io/[9] “Kiali - service mesh management for istio.” [Online]. Available: https://kiali.io/* Original Contents : https://research.samsung.com/blog/Open-Source-Kubernetes-for-the-next-level-of-network-virtualization June 17, 2021