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![Understanding MEC
5G/MEC use case
MBB: Mobile Broadband
mMTC: massive Machine
Type Communications
Dense Inf Society
Connected vehicles
VR office/factory/tactile
Throughput
Latency
Reliability
Availability
Energy
Efficiency
User/Device
density
Implications of 5G RAN and IoT on OpenStack based edge computing. より引用 [ OpenStack Summit にて AT&T, Ericsson 発表 ]
https://www.openstack.org/videos/sydney-2017/implications-of-5g-ran-and-iot-on-openstack-based-edge-computing
From AT&T‘s MEC POC](https://image.slidesharecdn.com/vtjedge20180814-180814003152/75/Edge-Computing-Architecture-using-GPUs-and-Kubernetes-17-2048.jpg)
![Understanding MEC
5G/MEC use case
MBB: Mobile Broadband
mMTC: massive Machine
Type Communications
Dense Inf Society
Connected vehicles
VR office/factory/tactile
Throughput
Latency
Reliability
Availability
Energy
Efficiency
User/Device
density
Implications of 5G RAN and IoT on OpenStack based edge computing. より引用 [ OpenStack Summit にて AT&T, Ericsson 発表 ]
https://www.openstack.org/videos/sydney-2017/implications-of-5g-ran-and-iot-on-openstack-based-edge-computing
From AT&T‘s MEC POC](https://crownmelresort.com/image.slidesharecdn.com/vtjedge20180814-180814003152/75/Edge-Computing-Architecture-using-GPUs-and-Kubernetes-17-2048.jpg)
Uploaded byVirtualTech Japan Inc.
Edge Computing Architecture using GPUs and Kubernetes
Here are the key points from the AT&T presentation on their "Network AI" framework: - AT&T is developing an open source framework called "Network AI" to drive their software-defined network transformation. - The goal is to apply AI/machine learning techniques to continuously optimize their network performance. This will be done by collecting massive amounts of network data and using it to train ML models. - As part of this effort, AT&T is contributing several open source projects to the Linux Foundation like Airship, Akraino, and Acumos. Airship provides tools for deploying OpenStack and Kubernetes on the edge, while Akraino is an edge computing framework. Acumos allows for developing and
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Similar to Edge Computing Architecture using GPUs and Kubernetes
Edge Computing Architecture using GPUs and Kubernetes
- 1. Edge Computing Architecture usingGPUs and Kubernetes 日本仮想化技術株式会社 VitrualTech.jp 2018/8/14 1
- 2. VirtualTech Japan Inc. 日本仮想化技術株式会社 •Company name: VirtualTech Japan Inc. (called VTJ) • Address: 1-8-1 Shibuya Shibuya-ku Tokyo • Founded: Dec 2006 • President and CEO: Toru Miyahara • Number of employees: 8 (Engineer: 7, Business Development: 1) • Our service: • Consulting NFV/OpenStack for Japan telco company • NTT Docomo’s large-scale OpenStack services • NTT West’s one of management systems of fixed network service using OpenStack • Plan to consulting Edge + GPU Computing • Corporate Web Site: http://virtualtech.jp 2 Corporate profile
- 3. Our expertise atOpenStack We are experts in Open Infrastructure, OpenStack and NFV. 3 2014/11 OpenStack Summit Paris We spoke the knowledge and tips when building and operating OpenStack Cloud on 100 Physical Servers. (Neutron HA, VXLAN performance,,,) 2012/10 OpenStack Summit San Diego We announced baremetal provisioning framework which handles barematel machine like a virtual machine. This is merged upstream in Grizzly. 2015/10 OpenStack Summit Tokyo We (NTT West, Canonical and VTJ) spoke ”Requirements for Providing Telecom Services on OpenStack-based Infrastructure”. Corporate profile
- 4. 1. OpenStack 2. Kubernetes 3.Kubernetes on OpenStack 4. OpenStack on Kubernetes 5. Edge Cloud 6. NFV Cloud Network Function Virtualization Definition of words 4 Kubernetes OpenStack OpenStack Kubernetes 3. Kubernetes on OpenStack 4. OpenStack on Kubernetes Kubernetes Hardware Hardware Under Cloud Over Cloud 5. Edge Cloud 6. NFV Cloud Relation of OpenStack and Kubernetes Using Cloud/Container technology at Telco company Device Kubernetes Hardware OpenStack OpenStack Hardware Access Point Inter net
- 5. Today‘s agenda • What’s“Edge” Computing? • Introduce to our Edge Computing POC project 5
- 6. Questions about “Edge”Computing We have any questions about “Edge” Computing. • Can you tell me about your “Edge” ? • What’s “Edge” Computing ? • What’s key points of “Edge” Computing ? 6 What’s “Edge” Computing?
- 7. Can you tellme about your “Edge” ? • I know that the definition of “Edge” is different for each person. 1. Edge of Network nodes 2. Edge of Cloud / Computing 3. Server side of IoT Application etc • We want ”Edge” Computing that can be used in various use cases. 7 What’s “Edge” Computing?
- 8. What’s “Edge” Computing? • We want ”Edge” Computing that can be used in various use cases. • I joined OpenStack Summit Vancouver. I watched some Telco Edge Computing projects. (AT&T, China Mobile and Verizon) • China Mobile’s use cases of “Edge” Computing From presentation “ Edge TIC – Future edge cloud for China mobile” • Enterprise Private Network (as like SD-WAN) • CDN Deployment • Live Sporting Event • Real time data backhaul of Unmanned Aerial Vehicle • V2X Service (V is Vehicle) 8 What’s “Edge” Computing?
- 9. What’s “Edge” Computing? • We want ”Edge” Computing that can be used in various use cases. • AT&T and China Mobile are combining NFV, “Edge” and MANO, and are beginning to create the Next-gen Network Service Infra. 9 What’s “Edge” Computing? NFV Edge MANO MA NO MANO: NFV Management and Orchestration NF V NF V Ed ge Ed ge Ed ge Regional (4+) Province (100+) City (600+) County (3000+) AP (100K+) Software • MANO: ONAP • NFV: OPNFV (Based OpenStack) • Edge: Akraino (Based Kubernetes on OpenStack) The number above is the assumed value of China Mobile.
- 10. What’s key pointsof “Edge” Computing ? • It’s important to think about both ”Technical side” and ”Business side” for success “Edge” Computing. • Technical side • We have to solve the technical problem related to “Edge” Computing. • Container , Kubernetes and Kubernetes ecosystem (include Kubernetes on OpenStack) • Running Kubernetes production, logging and problem solving • Business side • We have to think the business model using “Edge” Computing. • We are ready to help thinking your services and solutions leveraging “Edge” Computing + GPUs. • Cost reduction, Operation optimization • Create new business and new revenue (ex. Selling edge nodes for advertise items) 10 What’s “Edge” Computing?
- 11. “Edge” Computing +GPUs is Big impact! • Operation side Ex. Auto healing for Cloud Infra. • Service side Ex. Live Sporting Event 11 What’s “Edge” Computing? NFV Edge MANO Big data & Log Streaming GPU 1. Error occur at Network services 2. Detect error from logs Policy Engine 3. Action (change routing) OpenStack Auto healing SIG is alpha. Edge Edge GPU Football Stadium Camera Camera Edge 1. Streaming from Cameras 2. Processing Streaming Data GPU Users3. Streaming GPU power-ed live videos 0. Booked Edge nodes
- 12. Summary • I knowthat the definition of “Edge” is different for each person. • We want ”Edge” Computing that can be used in various use cases. • AT&T and China Mobile are combining NFV, “Edge” and MANO, and are beginning to create the Next-gen Network Service Infra. • It’s important to think about both ”Technical side” and ”Business side” for success “Edge” Computing. • “Edge” Computing + GPUs is Big Impact! • We are ready to help thinking your services and solutions leveraging “Edge” Computing + GPUs. 12 What’s “Edge” Computing?
- 13. Today‘s agenda • What’s“Edge” Computing? • Introduce to our Edge Computing POC project 13
- 14. Summary of OurEdge Computing POC • This’s a use case of Japanese telecom company. • Starting 5G/Edge Computing POC project using Kubernetes and NVIDIA GPUs. • This Edge Computing runs CPUs/GPUs at edge nodes. • Kubernetes manage Edge Computing Infra + GPUs. • We’re using Canonical Juju/MAAS (Provisioning tools) for Zero- touch provisioning. 14 Edge Computing POC
- 15.
- 16. About Multi-Access EdgeComputing (MEC) External Factor 5G Network is ready Edge Throughput: 100Mbps Latency: 1ms Peak Data Rate: 20Gbps All Telco company need to promote 5G Network Internal Factor Cost reduction and productivity improvement Next-generation Network Virtualization (NFV / SD-WAN) production is planning Edge Computing POC
- 17. Understanding MEC 5G/MEC usecase MBB: Mobile Broadband mMTC: massive Machine Type Communications Dense Inf Society Connected vehicles VR office/factory/tactile Throughput Latency Reliability Availability Energy Efficiency User/Device density Implications of 5G RAN and IoT on OpenStack based edge computing. より引用 [ OpenStack Summit にて AT&T, Ericsson 発表 ] https://www.openstack.org/videos/sydney-2017/implications-of-5g-ran-and-iot-on-openstack-based-edge-computing From AT&T‘s MEC POC
- 18. Disaggregated CoreDisaggregated RAN UnderstandingMEC (cond.) AT&T’s MEC Architecture 5G Application Ecosystem IoT Connected Car MBB RU DU UPF UPF Macro Radio & Small cell Antennas 5G Base Stations Edge Cloud Centralized Cloud CCF Internet CU-CP CU-UP NFV MANO (Management & Orchestration) CU: Centralized Unit CP: Control Plane UP: User Plane UPF: User Plane Function CCF: Core Control Function RU: Radio Unit DU: Digital Unit Implications of 5G RAN and IoT on OpenStack based edge computing. より引用
- 19. Understanding MEC (cond.) •Building Docker / Kubernetes controller • Zero-touch Provisioning is key • Planning thousands of locations • Support emerging technology at edge node （GPU, SmartNIC, FPGA, etc） • Planning collaboration with SDN/NFV and Orchestration Feedback from AT&T’s MEC project Edge Computing POC
- 20.
- 21. Proof of Concept(POC)#1 The scope of POC#1 is the following. • Building edge controller and container nodes using Kubernetes • Zero-touch Provisioning • Support GPUs at container nodes The scope of POC#2 is planning. Edge Computing POC
- 22. Container / Compute Nodes Edge Computing+ GPUs Architecture NFV MANO Edge Controllers Physical Provisioning Application Provisioning SDN / SDS Monitoring / Alerting Orchestrator GPU Hi speed networking General purpose Low energy Hi speed storage GPU Server GPU Server Storage Server Storage Server Object Storage Servers w/t SmartNIC Servers Scope of Edge Cloud ServerServer Server Edge Computing POC
- 23. Container nodes Scope ofEdge Computing + GPUs POC#1 NFV MANO Edge Controllers Physical Provisioning Application Provisioning SDN / SDS Monitoring / Alerting Orchestrator GPU Hi speed networking General purpose Low energy Hi speed storage GPU Server GPU Server Storage Server Storage Server Object Storage Servers w/t SmartNIC Servers Scope of Edge Cloud ServerServer Server Edge Computing POC
- 24. Components for EdgeComputing Components • Edge Cloud • Edge Controllers • Physical Provisioning: Ubuntu MAAS • Application Provisioning: Ubuntu Juju • Orchestrator: Kubernetes • SDN(Software Defined Network): Flannel (I believe Juniper Contrail needs it) • Monitoring/Alerting: Prometheus, Grafana • Container nodes • GPU Server • General Purpose Server: Intel and ARM Server Edge Computing POC
- 25. Questions: VM vsContainer • Existing Apps running on VMs will remain VMs. (You can migrate VMs to Containers, but cost does not match.) • New Apps such as IoT, Edge Computing and AI will be advanced with Containers. • NFV (their service infrastructure such as 5G and Fixed service) is currently VMs, Next generations will be Containers. (AT&T planed) • Large size (Servers > 100), prepare "Kubernetes on OpenStack" and let the user choose VMs or Containers. • Middle size (20 < Servers < 100), the user choice "Kubernetes" or "OpenStack". • Small size (Servers < 20), the user choice "Kubernetes". 25 Edge Computing POC
- 26. Kubernetes Kubernetes vs ”Kuberneteson OpenStack” • Kubernetes • Kubernetes on OpenStack 26 Kubernetes Container ContainerContainer Container ContainerContainer Kubernetes’s Good: • common to use Kubernetes to manage containers • Light weight controller • Auto healing is very good Kubernetes’s Bad: • No Multi-Tennant • No Network Policy related SDN • No Persistent Storage Kubernetes OpenStack “Kubernetes on OpenStack“ add missing features of Kubernetes. However, OpenStack’s controller isn’t Light weight. We have to think to apply it. Edge Computing POC
- 27.
- 28. Container nodes POC#1 environment(H/W) Edge Controllers • Physical Provisioning • Monitoring /Alerting • Application Provisioning • Orchestrator • SDN POC#1のControllersの多重化は行わない想定 • GPU • General purpose Edge Computing POC
- 29. Container nodes POC#1 environment(S/W) Edge Controllers • Physical Provisioning • Monitoring /Alerting • Application Provisioning • Orchestrator • SDN POC#1のControllersの多重化は行わない想定 • GPU • General purpose MAAS/Juju Prometheus / Grafana Kubernetes Flannel nvidia docker docker Edge Computing POC
- 30. ･Normal x86_64 Server ･Juju/MAAS ･Prometheus ･Grafana ･aptlocal repository ･Normal x86_64 Server ･Kubernetes Master node ･docker image pool ･Normal x86_64 Server ･Kubernetes Master node (･docker image pool) ･Normal x86_64 Server w/GPU ･Kubernetes Worker node ･Normal x86_64 Server ･Load Balancer ･ARM64 Server ･Kubernetes Worker node ･1GbE以上の Switch ･10GbE Switch IPMI IPMI IPMI IPMI IPMI Port VLANでも構いませ ん IPMI ･作業用端末 MAAS, メンテナンス用 for Podデプロイ, 一般通信用 ･確認用端末 ※Podデプロイの通信を独立させる構想は、以後のPoCでの検証対象とします 必要に応じて移動 • Ubuntu Server • Juju/MAAS • Kubernetes • GPU Server • ARM Server • Flannel • Prometheus • Grafana POC#1 environment (Our Testbed) Edge Computing POC
- 31. Next Step • TryOSS about Edge Computing + AI/DL • From AT&T OSS • Airship: Infrastructure project for OpenStack and Kubernetes • Akraino: Edge Computing Framework • Acumos AI: develop ML models for cloud optimization use-cases • From Kubernetes issues • Container Network (Calico, Tungsten Fabric, Cilium, etc) • Container Security (Istio, etc) • Persistent Storage (Ceph, Rook, etc) • Application deployment (Spinnaker, etc) 31
- 32. Summary of OurEdge Computing POC • This’s a use case of Japanese telecom company. • Starting 5G/Edge Computing POC project using Kubernetes and NVIDIA GPUs. • This Edge Computing runs CPUs/GPUs at edge nodes. • Kubernetes manage Edge Computing Infra + GPUs. • We’re using Canonical Juju/MAAS (Provisioning tools) for Zero- touch provisioning. 32 Edge Computing POC
- 33. Apendix • What’s Kubernetes •OpenStack Summit Feedback 33
- 34. Kubernetes 参考) Kubernetesとは • Kubernetes(以降、K8sと記す)はコンテナのオーケストレー ションツールです。 •コンテナの配置だけでなく、ロードバランシングや、コンテナ のオートスケールやオートヒーリングを実現します。 • コンテナ基盤のセルフヒーリングやローリングアップデートの 機能を備えます。 34 C C C Server C C C Server C C C Server Orchestrator Dockerなど のコンテナ ソフトウェア
- 35. 参考) Kubernetes とOpenStack • レイヤの異なるものなので比較するものではありません • コンテナの管理に特化したのが Kubernetes • 仮想マシンやコンテナやベアメタルサーバを管理するのが OpenStack • OpenStack上でKubernetesを動かすK8s on OpenStackもあり ます • アプリケーションがコンテナ/仮想マシンを選択することにな ります。 • 仮想マシン上のアプリケーションをコンテナに移植することは可能で すが、全てのアプリケーションを移行することは現実的ではありませ ん。 35
- 36. OpenStack Summit Feedback(1 1) AT&T's "Network AI" Network AI: AT&T’s Framework for Its Open Source Efforts That Will Drive our Software-Defined Network in 2018 and Beyond http://about.att.com/innovationblog/att_framework 36
- 37. 37 “The OpenStack andKubernetes Smørrebrød (Open Sandwich)”より引用
- 38. OpenStack on Kubernetes 38 Under Cloud Over Cloud Server Server Server Server ServerServer Server Server Server Server Server Server Server Server Server Server Server Server Server Server Server Server Server Server Control Plane Control Plane Control Plane Control Plane Control Plane Control Plane Control Plane Control Plane Control Plane Contain er node Contain er node Control Plane Contain er node Control node Control node Control node Control node Control node Control node Control node Compute node Compute node Control node Compute node 1. Single Node Bootstrap 2. Expand Control Plane 3. Deploy Additional Masters 4. Deploy Compute Hosts Kubeadm Self-hosted Deployment •Keystone •Nova •Glance •Heat •Ironic •Ceph Discover baremetal servers using Ironic Over Cloud で OpenStack Under Cloud で Kubernetes
- 39. OpenStack Summit Feedback2) 2) Acumos AI Project A federated platform for managing AI and ML applications and sharing AI models. AT&T and Tech Mahindra contributed the initial Acumos code, now freely available for download. The Linux Foundation Launches Open Source Acumos AI Project https://www.acumos.org/news/2018/03/26/the-linux- foundation-launches-open-source-acumos-ai-project/ 39
- 40. OpenStack Summit Feedback3) 3) Telus, Canadian telco comapny, AI Challenge Telus's AI Challenge is excellent. You can watch the following video. I will share interesting slide by email. Artificial Intelligence driven Orchestration, Challenges and Opportunities https://www.openstack.org/videos/vancouver-2018/artificial- intelligence-driven-orchestration-challenges-and- opportunities 40
- 41. In 2020, Beginto utilize Containers and AI 41
- 42. “Software Defined ServiceOperation” 42
- 43. Challenge to utilizeAI/ML at NFV and Edge 43
- 44. AI/ML Orchestration Ecosystem 44
- 45.
- 46. 参考）仮想化通信 コンテナ関連記事２ Kubernetesで永続ストレージを構築するツールのRook(の最新版)を使う https://tech.virtualtech.jp/entry/2018/07/17/121740 JujuでCalicoを使ったKubernetes環境を構築する(前編) https://tech.virtualtech.jp/entry/2018/06/15/115735 JujuでCalicoを使ったKubernetes環境を構築する(後編) https://tech.virtualtech.jp/entry/2018/06/15/162143 Juju +MAAS を使用したOpenstack構築 + 監視設定 https://tech.virtualtech.jp/entry/2018/04/24/131339 Juju + MAAS を使用したKubernetes構築 + 監視設定 https://tech.virtualtech.jp/entry/2018/03/29/104216 Airshipを試してみた https://tech.virtualtech.jp/entry/2018/07/19/175614 46
- 47.
Editor's Notes
- #6 Let’s start presentation. Today’s agenda is two. 1 is “What’s Edge Computing ?” I will talk with definition and use case of edge computing. 1 is “Introduce to our Edge Computing POC project” I will talk about Edge Computing POC that NVIDIA and VTJ proposed and building and running it.
- #7 First, I have questions about Edge computing for you. 1 is “Can you tell me about your “Edge” ?” I know that the definition of “Edge computing” is different for each person. I will talk about the definition of edge computing. 1 is “What’s “Edge” Computing ?” I will talk about use-case of edge computing. Last month, I joined events, OpenStack. I will feedback other telco company, AT&T and China Mobile, from OpenStack Summit. 1 is “What’s key points of “Edge” Computing ?” I will talk for success “Edge” Computing.
- #8 the definition of “Edge” is different for each person. 1 is Edge of Network nodes Telco user is almost it. 2 is Edge of Cloud / Computing Cloud user is it, maybe. 3 is Server side of IoT Application IoT Application user is it. In this presentation, the definition of Edge Computing includes everything. And, I will focus MEC, Multi-access Edge Computing, Mobile Edge Compuring , I talk about it.
- #9 Last month, I joined OpenStack Summit Vancouver. I watched Telco Edge Computing projects. (AT&T, China Mobile and Verizon). China mobile’s use case is the bellow. You can check at YouTube. Keyword is “Edge TIC china mobile”.
- #10 I was surprised by the activities of ATT and China Mobile. I am NFV consultant. NFV, I know, MANO,,,Orchestration for NFV, I know. They talked combining NFV, MANO and Edge. In Japan, NFV project and Edge project is deferent. I was surprised. Can you watch right side pictures in this slides ? This is China mobile use case. Reginal and province are NFV running . City, county and AP are Edge running. All NFV and Edge manage MANO. And, MANO, NFV and Edge is running OSS. Edge computing OSS, Akaraino, I watched first time.
- #11 I was mistake about some edge computing projects. I think for success “Edge” Comporting, we are thinking both “Technical side” and “Business side”. Technical side, technology of edge computing is not mature, many many technical problem. We are solving those technical problems. We have to think involving LOB and business development. NVIDIA and VTJ are ready to help thinking your projects. Cost reduce, Operation Optimization, It’s OK. Create new business, for example selling edge nodes for advertise items, It’s OK, I know big challenge.
- #12 This slide is use-cases of Edge Computing + GPUs. I‘m talking those use-cases usually. Left side of slide, It’s Operation side use-case. Error occurred NFV or Edge, Network is down or slowly. At Bigdata & Log Streaming system, detect errors from log. We believe that you can find errors efficiently by using GPUs. Operate MANO via Policy Engine to change NFV and Edge settings. Change routing and change band-width at NFV and Edge. And, OpenStack Auto-healing SIG is alpha now. OpenStack Auto-healing covered Collect logs, Detect error and apply Policy engine. This is future function. Right side of slide. It’s Service side use-case. Live Sporting Event, Imaging such as Olympic Tokyo 2020. Streaming data of many cameras upload to Edge node with GPUs. Process from streaming data to such as panorama image and player view image and so. Publish streaming data from the edge node to the users.
- #13 It‘s summary. ”Edge” Computing can be used in various use cases. And This session was focus MEC. AT&T and China Mobile are combining NFV, “Edge” and MANO, and are beginning to create the Next-gen Network Service Infra. It’s important to think about both ”Technical side” and ”Business side”. If need to help, NVIDIA and VTJ will help your projects.
- #14 Next is Our Edge Computing POC project This is Japanese customer use case. NVIDIA and VTJ are promoted GPU MEC POC project. This POC system is running.
- #15 This is summary of this POC project. Using Containers , Kubernetes and NVIDIA GPUs. Kubernetes is managing containers and container orchestration. This project’s Kubernetes manage many containers and GPUs.
- #16 Half years ago, I joined OpenStack Summit Sydney, I watched AT&T Edge Computing project journey presentation. I was inspired by that material.
- #17 This slide is External and Internal Factor of MEC.
- #18 Refer from AT&T document I understood that 5g network is several use-case. Each use-case has different system requirement.
- #19 This slide is AT&T‘s MEC High level Architecture. Right side of slide is Centralized Cloud, called “Core Network”. Left side of slide is Radio network for Mobile Network. Center side of slide is Edge Cloud using Edge Computing. Upper side of slide is NFV MANO. NFV MANO is Orchestrator for Telecom service networks. NFV MANO manage Centralized Cloud and Edge Cloud.
- #20 This slide is feedback from at&t mec projects. MEC is running at telco central center, city and county and so. There are limitation space for server of edge computing. This AT&T project choose container and Kubernetes. There are many node of edge computing, and management from remote site is necessary. At Edge computing, Zero-touch provisioning is key feature.
- #21 This is introduction about our poc project.
- #22 The proof of Our POC is bellow. This POC is first phase. Proposed at November of last year, research and build POC system. This POC system is running now.
- #23 This is Edge Computing + GPUs Architecture. The upper side of slide is Edge Controller. The bottom side of slide is Container nodes/Compute nodes. For several use-case for edge computing, we will prepare variable type of Container nodes.
- #24 1st phase of our POC is Edge controller and GPU Servers and General purpose servers.
- #25 This slide is components for our edge computing. We are used Ubuntu Juju/MAAS for zero-touch provisioning. SDN is flannel is good, may be. GPU is used. And, General purpose server is used Intel server and ARM server. ARM server is challenging. In this project, We ware asking Canonical, Canonical deliver Ubuntu Support Service. We ware made Kubernetes on ARM.
- #26 This slide is question about VM versus Container. Generally, User choose VM or Container according to system requirements. The VM is already in use, the Container will be used for future application development. As NFV Consultant, I think that the Container is not mature of virtualized network and hardware offloads for high speed network. This slide is question about VM vs Container in case of MEC. This is my knowledge. MEC have problem about space limitation. Small Edge node is 1 rack or 2 racks, I heard. Under 20 servers MEC environments, User of infra. choose usually Container and Kubernetes. Over 100 servers MEC environments, User of infra. build VM and OpenStack. if needed, install Kubernetes on VM. We call “Kubernetes on OpenStack”. User of Application choose VMs or Containers.
- #27 This slide is Kubernetes vs Kubernetes on OpenStack. Kubernetes is good solution. Light weight controller and built-in auto-healing. But, today’s Kubernetes is no Multi-tenant and no network policy related SDN. If needed, we are choose Kubernetes on OpenStack.
- #28 This slides our POC environment.
- #31 This is our testbed. Using Juju/M.AAS, we can build same environment.
- #32 This slide is next step for our poc. We have many issue. We will try to solve issues.
- #33 This is summary of this POC project. Using Containers , Kubernetes and NVIDIA GPUs. Kubernetes is managing containers and container orchestration. This project’s Kubernetes manage many containers and GPUs. If interested MEC and our MEC projects, please ask NVIDIA and VTJ.