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
Free GitOps Workshop + Intro to Kubernetes & GitOpsWeaveworks
Follow along in this free workshop and experience GitOps!
AGENDA:
Welcome - Tamao Nakahara, Head of DX (Weaveworks)
Introduction to Kubernetes & GitOps - Mark Emeis, Principal Engineer (Weaveworks)
Weave Gitops Overview - Tamao Nakahara
Free Gitops Workshop - David Harris, Product Manager (Weaveworks)
If you're new to Kubernetes and GitOps, we'll give you a brief introduction to both and how GitOps is the natural evolution of Kubernetes.
Weave GitOps Core is a continuous delivery product to run apps in any Kubernetes. It is free and open source, and you can get started today!
https://www.weave.works/product/gitops-core
If you’re stuck, also come talk to us at our Slack channel! #weave-gitops http://bit.ly/WeaveGitOpsSlack (If you need to invite yourself to the Slack, visit https://slack.weave.works/)
RAPIDS – Open GPU-accelerated Data ScienceData Works MD
RAPIDS – Open GPU-accelerated Data Science
RAPIDS is an initiative driven by NVIDIA to accelerate the complete end-to-end data science ecosystem with GPUs. It consists of several open source projects that expose familiar interfaces making it easy to accelerate the entire data science pipeline- from the ETL and data wrangling to feature engineering, statistical modeling, machine learning, and graph analysis.
Corey J. Nolet
Corey has a passion for understanding the world through the analysis of data. He is a developer on the RAPIDS open source project focused on accelerating machine learning algorithms with GPUs.
Adam Thompson
Adam Thompson is a Senior Solutions Architect at NVIDIA. With a background in signal processing, he has spent his career participating in and leading programs focused on deep learning for RF classification, data compression, high-performance computing, and managing and designing applications targeting large collection frameworks. His research interests include deep learning, high-performance computing, systems engineering, cloud architecture/integration, and statistical signal processing. He holds a Masters degree in Electrical & Computer Engineering from Georgia Tech and a Bachelors from Clemson University.
Knative, Serverless on Kubernetes, and OpenshiftChris Suszyński
Is Serverless just running functions in a cloud? It’s more than that! Serverless computing refers to the concept of building and running applications that do not require server management.
It describes a deployment model where applications, bundled as one or more functions, are uploaded to a platform and then executed, scaled, and billed in response to the exact demand needed at the moment.
During the talk I’ll show how to use Knative both on Kubernetes and on OpenShift platform. Hopefully we will see why your organization should consider using Knative as one of its primary deployments models on hybrid cloud world.
Kafka for Real-Time Replication between Edge and Hybrid CloudKai Wähner
Not all workloads allow cloud computing. Low latency, cybersecurity, and cost-efficiency require a suitable combination of edge computing and cloud integration.
This session explores architectures and design patterns for software and hardware considerations to deploy hybrid data streaming with Apache Kafka anywhere. A live demo shows data synchronization from the edge to the public cloud across continents with Kafka on Hivecell and Confluent Cloud.
Traditional virtualization technologies have been used by cloud infrastructure providers for many years in providing isolated environments for hosting applications. These technologies make use of full-blown operating system images for creating virtual machines (VMs). According to this architecture, each VM needs its own guest operating system to run application processes. More recently, with the introduction of the Docker project, the Linux Container (LXC) virtualization technology became popular and attracted the attention. Unlike VMs, containers do not need a dedicated guest operating system for providing OS-level isolation, rather they can provide the same level of isolation on top of a single operating system instance.
An enterprise application may need to run a server cluster to handle high request volumes. Running an entire server cluster on Docker containers, on a single Docker host could introduce the risk of single point of failure. Google started a project called Kubernetes to solve this problem. Kubernetes provides a cluster of Docker hosts for managing Docker containers in a clustered environment. It provides an API on top of Docker API for managing docker containers on multiple Docker hosts with many more features.
Free GitOps Workshop + Intro to Kubernetes & GitOpsWeaveworks
Follow along in this free workshop and experience GitOps!
AGENDA:
Welcome - Tamao Nakahara, Head of DX (Weaveworks)
Introduction to Kubernetes & GitOps - Mark Emeis, Principal Engineer (Weaveworks)
Weave Gitops Overview - Tamao Nakahara
Free Gitops Workshop - David Harris, Product Manager (Weaveworks)
If you're new to Kubernetes and GitOps, we'll give you a brief introduction to both and how GitOps is the natural evolution of Kubernetes.
Weave GitOps Core is a continuous delivery product to run apps in any Kubernetes. It is free and open source, and you can get started today!
https://www.weave.works/product/gitops-core
If you’re stuck, also come talk to us at our Slack channel! #weave-gitops http://bit.ly/WeaveGitOpsSlack (If you need to invite yourself to the Slack, visit https://slack.weave.works/)
RAPIDS – Open GPU-accelerated Data ScienceData Works MD
RAPIDS – Open GPU-accelerated Data Science
RAPIDS is an initiative driven by NVIDIA to accelerate the complete end-to-end data science ecosystem with GPUs. It consists of several open source projects that expose familiar interfaces making it easy to accelerate the entire data science pipeline- from the ETL and data wrangling to feature engineering, statistical modeling, machine learning, and graph analysis.
Corey J. Nolet
Corey has a passion for understanding the world through the analysis of data. He is a developer on the RAPIDS open source project focused on accelerating machine learning algorithms with GPUs.
Adam Thompson
Adam Thompson is a Senior Solutions Architect at NVIDIA. With a background in signal processing, he has spent his career participating in and leading programs focused on deep learning for RF classification, data compression, high-performance computing, and managing and designing applications targeting large collection frameworks. His research interests include deep learning, high-performance computing, systems engineering, cloud architecture/integration, and statistical signal processing. He holds a Masters degree in Electrical & Computer Engineering from Georgia Tech and a Bachelors from Clemson University.
Knative, Serverless on Kubernetes, and OpenshiftChris Suszyński
Is Serverless just running functions in a cloud? It’s more than that! Serverless computing refers to the concept of building and running applications that do not require server management.
It describes a deployment model where applications, bundled as one or more functions, are uploaded to a platform and then executed, scaled, and billed in response to the exact demand needed at the moment.
During the talk I’ll show how to use Knative both on Kubernetes and on OpenShift platform. Hopefully we will see why your organization should consider using Knative as one of its primary deployments models on hybrid cloud world.
Kafka for Real-Time Replication between Edge and Hybrid CloudKai Wähner
Not all workloads allow cloud computing. Low latency, cybersecurity, and cost-efficiency require a suitable combination of edge computing and cloud integration.
This session explores architectures and design patterns for software and hardware considerations to deploy hybrid data streaming with Apache Kafka anywhere. A live demo shows data synchronization from the edge to the public cloud across continents with Kafka on Hivecell and Confluent Cloud.
Traditional virtualization technologies have been used by cloud infrastructure providers for many years in providing isolated environments for hosting applications. These technologies make use of full-blown operating system images for creating virtual machines (VMs). According to this architecture, each VM needs its own guest operating system to run application processes. More recently, with the introduction of the Docker project, the Linux Container (LXC) virtualization technology became popular and attracted the attention. Unlike VMs, containers do not need a dedicated guest operating system for providing OS-level isolation, rather they can provide the same level of isolation on top of a single operating system instance.
An enterprise application may need to run a server cluster to handle high request volumes. Running an entire server cluster on Docker containers, on a single Docker host could introduce the risk of single point of failure. Google started a project called Kubernetes to solve this problem. Kubernetes provides a cluster of Docker hosts for managing Docker containers in a clustered environment. It provides an API on top of Docker API for managing docker containers on multiple Docker hosts with many more features.
Autoscaling of workloads in the Kubernetes environment. A slidedeck about Pod and Node autoscaling and the machinery behind it that makes it happen. Few recommendations for Pod and Node autoscaling while implementing it.
In this session, Diógenes gives an introduction of the basic concepts that make OpenShift, giving special attention to its relationship with Linux containers and Kubernetes.
Slide deck from my "OpenStack and MySQL" presentation at Oracle OpenWorld 2015:
"This session details exactly how MySQL fits in throughout OpenStack, takes a deeper look at the database-as-a-service (DBaaS) offering with OpenStack Trove with MySQL, and discusses how Oracle supports this thriving ecosystem."
An Architectural Deep Dive With Kubernetes And Containers Powerpoint Presenta...SlideTeam
Introducing An Architectural Deep Dive With Kubernetes And Containers PowerPoint Presentation Slides. Present the need for the containers in an organization with the help of a readily available PPT slideshow. Discuss container architecture, use cases details to make your presentation elaborative. Showcase the features, architecture, installation roadmap, and the 30-60-90 day plan in Kubernetes with the help of modern-designed PPT infographics. Familiarize your viewers with the various components of Kubernetes with the help of content-ready Kubernetes Docker PPT visuals. Make full use of high-quality icons to make your presentation attention-grabbing and meaningful. Compare and contrast Kubernetes with docker swarm based on various parameters with the help of this attention-grabbing PPT slideshow. Elaborate on Kubelet, Kubectl, and Kubeadm with the help of labeled diagrams. Showcase the networking model of Kubernetes, security measures, and the development process with this easy-to-use docker Architecture PowerPoint template. Therefore, hit the download button now to grab this amazing presentation. https://bit.ly/3vtLeFb
AI firsts: Leading from research to proof-of-conceptQualcomm Research
AI has made tremendous progress over the past decade, with many advancements coming from fundamental research from many decades ago. Accelerating the pipeline from research to commercialization has been daunting since scaling technologies in the real world faces many challenges beyond the theoretical work done in the lab. Qualcomm AI Research has taken on the task of not only generating novel AI research but also being first to demonstrate proof-of-concepts on commercial devices, enabling technology to scale in the real world. This presentation covers:
The challenges of deploying cutting-edge research on real-world mobile devices
How Qualcomm AI Research is solving system and feasibility challenges with full-stack optimizations to quickly move from research to commercialization
Examples where Qualcomm AI Research has had industrial or academic firsts
5G is going mainstream across the globe, and this is an exciting time to harness the low latency and high capacity of 5G to enable the metaverse. A distributed-compute architecture across device and cloud can enable rich extended reality (XR) user experiences. Virtual reality (VR) and mixed reality (MR) are ready for deployment in private networks, while augmented reality (AR) for wide area networks can be enabled in the near term with Wi-Fi powered AR glasses paired with a 5G-enabled phone. Device APIs enabling application adaptation is critical for good user experience. 5G standards are evolving to support the deployment of AR glasses at a large scale and setting the stage for 6G-era with the merging of the physical, digital, and virtual worlds. Techniques like perception-enhanced wireless offer significant potential to improve user experience. Qualcomm Technologies is enabling the XR industry with platforms, developer SDKs, and reference designs.
Check out this webinar to learn:
• How 5G and distributed-compute architectures enable the metaverse
• The latest results from our boundless XR 5G/6G testbed, including device APIs and perception-enhanced wireless
• 5G standards evolution for enhancing XR applications and the road to 6G
• How Qualcomm Technologies is enabling the industry with platforms, SDKs, and reference designs
Fast, Scalable Quantized Neural Network Inference on FPGAs with FINN and Logi...KTN
This presentation, delivered by Yaman Umuroğlu, Research Scientist, Xilinx, was the second presentation of the Implementing AI: Vision Systems Webinar.
Application developers are key to the success of an edge compute strategy. They are the backbone for any digital ecosystem and their requirements drive the platform architecture. Edge computing is no different. In this talk, we will focus on some key requirements, challenges and possible solutions for a developer centric architecture for multi-access edge computing including abstraction of the service provider’s network complexity, low footprint cloud native builder models, micro-services, hardware abstractions, intelligence layers and massive monitoring of application instances.
About the speaker: Shamik Mishra is currently Assistant Vice President (AVP), Technology and Innovation at Aricent. He is a practice leader for new product architectures. He has extensive experience and contributions in software development in cloud, wireless technologies, edge computing and platform software. His research interests are Network Function Virtualization (NFV), Cloud and edge computing and Machine Learning (ML). He has spoken in several conferences and his work is regularly covered in the media. Shamik has a bachelor’s and a master’s degree from Indian Institute of Technology (IIT) Kharagpur, India.
Autoscaling of workloads in the Kubernetes environment. A slidedeck about Pod and Node autoscaling and the machinery behind it that makes it happen. Few recommendations for Pod and Node autoscaling while implementing it.
In this session, Diógenes gives an introduction of the basic concepts that make OpenShift, giving special attention to its relationship with Linux containers and Kubernetes.
Slide deck from my "OpenStack and MySQL" presentation at Oracle OpenWorld 2015:
"This session details exactly how MySQL fits in throughout OpenStack, takes a deeper look at the database-as-a-service (DBaaS) offering with OpenStack Trove with MySQL, and discusses how Oracle supports this thriving ecosystem."
An Architectural Deep Dive With Kubernetes And Containers Powerpoint Presenta...SlideTeam
Introducing An Architectural Deep Dive With Kubernetes And Containers PowerPoint Presentation Slides. Present the need for the containers in an organization with the help of a readily available PPT slideshow. Discuss container architecture, use cases details to make your presentation elaborative. Showcase the features, architecture, installation roadmap, and the 30-60-90 day plan in Kubernetes with the help of modern-designed PPT infographics. Familiarize your viewers with the various components of Kubernetes with the help of content-ready Kubernetes Docker PPT visuals. Make full use of high-quality icons to make your presentation attention-grabbing and meaningful. Compare and contrast Kubernetes with docker swarm based on various parameters with the help of this attention-grabbing PPT slideshow. Elaborate on Kubelet, Kubectl, and Kubeadm with the help of labeled diagrams. Showcase the networking model of Kubernetes, security measures, and the development process with this easy-to-use docker Architecture PowerPoint template. Therefore, hit the download button now to grab this amazing presentation. https://bit.ly/3vtLeFb
AI firsts: Leading from research to proof-of-conceptQualcomm Research
AI has made tremendous progress over the past decade, with many advancements coming from fundamental research from many decades ago. Accelerating the pipeline from research to commercialization has been daunting since scaling technologies in the real world faces many challenges beyond the theoretical work done in the lab. Qualcomm AI Research has taken on the task of not only generating novel AI research but also being first to demonstrate proof-of-concepts on commercial devices, enabling technology to scale in the real world. This presentation covers:
The challenges of deploying cutting-edge research on real-world mobile devices
How Qualcomm AI Research is solving system and feasibility challenges with full-stack optimizations to quickly move from research to commercialization
Examples where Qualcomm AI Research has had industrial or academic firsts
5G is going mainstream across the globe, and this is an exciting time to harness the low latency and high capacity of 5G to enable the metaverse. A distributed-compute architecture across device and cloud can enable rich extended reality (XR) user experiences. Virtual reality (VR) and mixed reality (MR) are ready for deployment in private networks, while augmented reality (AR) for wide area networks can be enabled in the near term with Wi-Fi powered AR glasses paired with a 5G-enabled phone. Device APIs enabling application adaptation is critical for good user experience. 5G standards are evolving to support the deployment of AR glasses at a large scale and setting the stage for 6G-era with the merging of the physical, digital, and virtual worlds. Techniques like perception-enhanced wireless offer significant potential to improve user experience. Qualcomm Technologies is enabling the XR industry with platforms, developer SDKs, and reference designs.
Check out this webinar to learn:
• How 5G and distributed-compute architectures enable the metaverse
• The latest results from our boundless XR 5G/6G testbed, including device APIs and perception-enhanced wireless
• 5G standards evolution for enhancing XR applications and the road to 6G
• How Qualcomm Technologies is enabling the industry with platforms, SDKs, and reference designs
Fast, Scalable Quantized Neural Network Inference on FPGAs with FINN and Logi...KTN
This presentation, delivered by Yaman Umuroğlu, Research Scientist, Xilinx, was the second presentation of the Implementing AI: Vision Systems Webinar.
Application developers are key to the success of an edge compute strategy. They are the backbone for any digital ecosystem and their requirements drive the platform architecture. Edge computing is no different. In this talk, we will focus on some key requirements, challenges and possible solutions for a developer centric architecture for multi-access edge computing including abstraction of the service provider’s network complexity, low footprint cloud native builder models, micro-services, hardware abstractions, intelligence layers and massive monitoring of application instances.
About the speaker: Shamik Mishra is currently Assistant Vice President (AVP), Technology and Innovation at Aricent. He is a practice leader for new product architectures. He has extensive experience and contributions in software development in cloud, wireless technologies, edge computing and platform software. His research interests are Network Function Virtualization (NFV), Cloud and edge computing and Machine Learning (ML). He has spoken in several conferences and his work is regularly covered in the media. Shamik has a bachelor’s and a master’s degree from Indian Institute of Technology (IIT) Kharagpur, India.
Kubernetes Native Infrastructure and CoreOS Operator Framework for 5G Edge Cl...Hidetsugu Sugiyama
This session will discuss K8s solutions and Telco Intelligent-edge possibilities by integrate with CoreOS Operator Framework that can manage CNFs, state-full and other complex stateless container applications.
Connectivity is here (5 g, swarm,...). now, let's build interplanetary apps! (1)Samy Fodil
Webinar recording: https://youtu.be/t30Aa-mq93Q
Do you need to build scalable 5G and IoT applications? Or, maybe distribute the computing required by AR/VR throughout the data path? Perhaps you need to implement Digital Twins? Well you've come to the right place.
Edge Computing is a paradigm that distributes computing and data storage between the Cloud and the users. In fact, the data center infrastructure that sits between you and the Cloud is actually larger than all the Cloud data centers combined. For over two decades, thanks to that Edge infrastructure you've been able to watch videos and smoothly surf the web. Today the "Edge" is powering all the automation around you; for example, smart cities, smart cars, smart factories, etc.
IoT is one of the biggest topics in IT system today.
In this session, we will discuss how we can achieve an effective IoT system on OpenStack.
Firstly we'll describe IoT use cases, and summarize some generic requirements for IoT backend.
Secondly, we'll present our reference design of IoT backend on OpenStack IaaS.
Finally, we'll discuss the result of fit and gap analysis of OpenStack itself as a platform for IoT backend.
This session includes following items.
* What kind of components we need to enable IoT backend
* How to design and create network model to gather up all data from distributed sources
* How to support flexible data gathering, storing and processing of massive data
* How to achieve multi-tenanty required for IoT platform
https://openstacksummitoctober2015tokyo.sched.org/event/0ca80f968b4e1e3dd23137405a7deb15#.VjSxm2s3LJA
Edge optimized architecture for fabric defect detection in real-timeShuquan Huang
In textile industry, fabric defect relies on human inspection traditionally, which is inaccurate, inconsistent, inefficient and expensive. There were automatic systems developed on the defect detection by identifying the faults in fabric surface using the image and video processing techniques. However, the existing solution has insufficiencies in defect data sharing, backhaul interconnect, maintenance and etc. By evolving to an edge-optimized architecture, we can help textile industry improve fabric quality, reduce operation cost and increase production efficiency. In this session, I’ll share:
What’s edge computing and why it’s important to intelligence manufacturing
What’s the characteristics, strengths and weaknesses of traditional fabric defect detection method
Why textile industry can benefit from edge computing infrastructure
How to design and implement an edge-enabled application for fabric defect detection in real-time
Insights, synergy and future research directions
DevOps Fest 2020. Pavlo Repalo. Edge Computing: Appliance and ChallangesDevOps_Fest
Over the last years booming of cloud technologies created a lot of opportunities for business and together with IoT expansion established new niche: Edge Computing. Since it's one of the first speech within the UA community we will go through main points about the origin, business use cases, main frameworks, and challenges. Why DevOps people should start learning embedded programming aspects and why we shouldn't allow to register a cloud node after reboot? That's the questions what we'll also review with professional part of the audience.
QNAP 針對物聯網打造私有雲平台,QIoT Suite Lite 提供開發板如 Arduino Yun Raspberry Pi 及Intel Edison 快速連結到QNAP NAS,並提供客製化NodeRED 及Dashboard 做裝置控管及資料呈現(Data Visualization) 。在Intranet 即可提供服務,也提供Interface 與其他第三方服務連結 如Power BI 及 QVR Pro 等
5G and edge computing - CORAL perspectiveRichard Scott
Charles Turyagyenda from InterDigital Europe Ltd presented an overview of the opportunities and technical aspects of 5G edge computing at the first of Digital Catapult Centre Brighton's 5G workshops. These workshops were designed to raised awareness of the opportunities and features of 5G within small digital businesses, as well as identifying potential use cases to be take forward to be explored within the National 5G testbed for digital businesses in Brighton.
We are inviting small digital businesses to get in contact to discuss how they might exploit the 5G testbed. If you are interested in how you might do so please email digicatbrighton@wiredsussex.com
Open Source Possibilities for 5G Edge Computing DeploymentIgnacio Verona
Session delivered together with my colleague Hyde Sugiyama during ONS Amsterdam 2018. We discussed about how open source and edge computing will enable a new B2B2X market for CSPs.
Session 1908 connecting devices to the IBM IoT CloudPeterNiblett
IBM MessageSight and the IBM Internet of Things cloud enable connectivity across a wide variety of devices - from existing devices in silos and systems through the wide range of new devices that are appearing on a daily basis. This session covers patterns of connectivity, how to make it happen, including sending events like measurements and receiving of commands. The session goes into detail on how to use the industry standard MQ Telemetry Transport protocol to achieve this and encompasses best practices for topics and message format.
Open Source Edge Computing Platforms - OverviewKrishna-Kumar
IEEE 11th International Conference - COMSNETS 2019 - Last MilesTalk - Jan 2019. This talk is for Beginner or intermediate levels only. Kubernetes and related edge platforms are discussed.
Similar to Edge Computing Architecture using GPUs and Kubernetes (20)
NTT Docomo's Challenge looking ahead the world pf 5G × OpenStack - OpenStack最...VirtualTech Japan Inc.
タイトル:NTT Docomo's Challenge looking ahead the world pf 5G × OpenStack
アジェンダ:
- Current Challenge
-- DOCOMO Cloud Platform
-- BizDevOps
- Challenge for the future
-- DOCOMO 5G Open Cloud
-- Next Challenge
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
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 at OpenStack
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
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 tell me 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 points of “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 know that 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?
14. Summary of Our Edge 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
16. About Multi-Access Edge Computing (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 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
18. Disaggregated CoreDisaggregated RAN
Understanding MEC (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
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 of Edge 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 Edge Computing
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 vs Container
• 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 ”Kubernetes on 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
30. ・Normal x86_64 Server
・Juju/MAAS
・Prometheus
・Grafana
・apt local 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
• Try OSS 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 Our Edge 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
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
38. OpenStack on Kubernetes
38
Under
Cloud
Over
Cloud
Server
Server
Server
Server
Server Server
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 Feedback 2)
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 Feedback 3)
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
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.
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.
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 ApplicationIoT 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.
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”.
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.
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.
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.
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.
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.
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.
Half years ago, I joined OpenStack Summit Sydney, I watched AT&T Edge Computing project journey presentation.
I was inspired by that material.
This slide is External and Internal Factor of MEC.
Refer from AT&T document
I understood that 5g network is several use-case.
Each use-case has different system requirement.
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.
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.
This is introduction about our poc project.
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.
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.
1st phase of our POC is Edge controller and GPU Servers and General purpose servers.
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.
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.
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.
This slides our POC environment.
This is our testbed.
Using Juju/M.AAS, we can build same environment.
This slide is next step for our poc.
We have many issue. We will try to solve issues.
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.