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Automating networks through the machine learning driven insight

Many elements of infrastructure have the capability to adapt with principles such as scale on demand. Networks have generally stayed static due to their complexity and fixed nature of the underlay provider and the ability to perform consistent rapid change.

In recent times Artificial Intelligence has been integrated in almost all elements of information and communication technologies with the use of machine learning and deep learning becoming quite commonly applied in various day to day applications.

The majority of network components produce large amount of raw data much of which currently is ignored or discarded in favour on focusing on availability and key performance metrics.

Machine learning algorithms have been developed for communication networks to be applied to fundamental problems in networking, including traffic prediction, routing and classification, congestion control, resource, fault management, QoS and QoE management and network security.
Software defined networks (SDN) provide the ability to program network configuration through the use of open standards and DevOps tools such as Terraform and Ansible. Central orchestration engines provides the ability to deploy configuration to the edge through a controlled and consistent method.

So, we have the building blocks for an adaptable network, driven by metrics provided on a real or near real time basis.

Key Takeaways will be:

• Generation of real time metrics to provide insight in the performance of a network for end user
experience
• Consumption of metrics to be processed by the appropriate machine learning algorithm with
validation of learning by network professionals
• Dynamic configuration of networks through programmatic interface centrally orchestrated
• An iterative programmatic approach to continually change with appropriate lag to continually adapt to the needs of the business applications and introduction of new services
Recorded Oct 21 2020 43 mins
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Presented by
Martin Blunn, Chief Technology Officer, Solutionize Global
Presentation preview: Automating networks through the machine learning driven insight

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    Today policymakers and industry leaders are still dealing with the economic effects of the coronavirus pandemic. Small business owners are finding it very difficult to plan into the future given the uncertainty that we are all facing. Some businesses have decided to cut down costs by letting go of their employees, some are taking advantage of government grants to stay afloat, whilst others are taking advantage of this period to build a technological bridge for flexibility, agility, and innovation in the post-pandemic business environment.

    The business environment post-pandemic will be one where the new normal is constant change. Successful cloud adoption will be your foundation for a new bridge that will connect you to new markets and one that is flexible enough to adapt to constant changes in the regulatory and business environment. Businesses are now shifting from their on-prem and private cloud solutions to public clouds, hybrid cloud configurations, and multi-cloud solutions. For many, this means transitioning into unknown territory. They quickly recognize it is essential to bring in experts who can provide cloud-based software development services and solutions.

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  • Digital Transformation for Cloud Strategy and Adoption Nov 4 2020 12:00 am UTC 45 mins
    Sreenath C Lakshmanan, Founder & CEO, i4DigitalValue
    The webinar will cover the following areas:

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    - Integration of Digital Transformation Strategy, People, Process, Technology and Data analytics for Cloud Strategy and Adoption.
    - Successfully navigating through Solutions that work.

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    - Developing ideas to Problems for Cloud Strategy and Adoption
    - Defining a path for implementing Digital Transformation
    - Defining an approach to Cloud usage, Optimizing resources and costs
    - Aligning Cloud Strategy with Business Objectives
  • Cloud Strategy 101: 10 things to consider for your modern private cloud strategy Nov 3 2020 8:00 pm UTC 45 mins
    Siddick ELAHEEBOCUS | Technology strategist | Trainer | Speaker
    10 things from the trenches to consider for your modern private cloud strategy

    Private cloud remains an important component within the digital transformation and cloud-first strategy of many organisations to host critical data and workloads. In this vendor-agnostic webinar we will have a bird’s eye view of the ten top things from the trenches that must be taken into consideration for a successful modern private cloud strategy focusing around people, process and technology.

    The objectives of this webinar is to provide the attendees with the building blocks of a modern private cloud and to help them move to the starting block to cloud-ready their organisation's IT infrastructure.


    About the presenter
    Siddick ELAHEEBOCUS is quadrilingual technology strategist, trainer and speaker with eighteen years of international experience within the IT industry. His areas of expertise is focused around datacentre modernization (private cloud, hybrid cloud and public cloud), workplace modernization and IT security modernization. He is also a frequent technology speaker.

    Siddick currently works as Director for an IT services company providing vendor-agnostic technical and strategic advisory services, high-end professional IT services and training to organisations of all sizes to assist them in their digital transformation strategy.

    You can find more about Siddick by scanning the QR code on the title slide.
  • What's Changing In Start-Ups & Innovation? Insights from HBR author Alex Lazarow Oct 28 2020 4:00 pm UTC 60 mins
    Alex Lazarow - Venture Capitalist and author of 'Out-Innovate' and Harriet Jamieson - Senior Content Manager, BrightTALK
    Startups have changed the world. In the United States, many startups, such as Tesla, Apple, and Amazon, have become household names. The economic value of startups has doubled since 1992 and is projected to double again in the next fifteen years. For decades, the hot center of this phenomenon has been Silicon Valley. This is changing fast. Thanks to technology, startups are now taking root everywhere, from Delhi to Detroit to Nairobi to Sao Paulo. Yet despite this globalization of startup activity, our knowledge of how to build successful startups is still drawn primarily from Silicon Valley.

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    The new playbook for innovation and startup success is emerging from beyond Silicon Valley—at the "frontier."
  • Data Center Modernization? Is it inside-out?, or outside-in? Recorded: Oct 22 2020 46 mins
    Susmitha Marupaka, PM and Engineer
    Starting from 1940-till date, Data Center boundaries were pushed, torn apart, automated, and rebuilt which resulted in the metamorphosis of the whole enterprise ecosystem.Learn more about the Data Center modernization, which is the best-of-the both worlds solution, for both legacy, and next-generation agile workloads.
  • Journey to Resiliency: How AI & ML Improve Predictive Maintenance & Optimization Recorded: Oct 22 2020 54 mins
    Andrew Graham, Critical Environments Group | Lars Strong, Upsite Technologies
    For several years, artificial intelligence (AI) and machine learning (ML) have been trendy buzzwords in the data center industry, offering the promise of an automated data center that is more resilient with a lower operating cost. The reality is, most data center operators are still living in a reactive world; chasing down problems, issues, and putting out fires. We’re all hoping that predictive maintenance driven by AI/ML will change that, but this has become a longer journey than stakeholders first realized. The first step in this journey is to identify where your organization sits on the path of reactive, preventative, proactive, or predictive maintenance. The next step is to develop a plan for migrating towards predictive maintenance driven by AI/ML that will optimize your data center while improving resiliency.

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    There is clear evidence that the presence of COVID-19 has disrupted the technology industry. Pre-COVID, technology was relied upon now it is the core focus of our personal and business livelihoods. If you were not tech savvy, this disruption forced you to adapt and use it.
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    2. As a result of this disruption, what is the future out-look of data center operations?
    3. What are the environmental trends of data centers and their outlook?
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    Nima Torabi, Co-founder and CEO, Liberatii Ltd
    Migrating enterprise application suites (applications and data) over to the cloud is thought of as a strategic plan rather than a technical one for most businesses. Such migration projects need months of planning and put CIOs and CTOs under a huge amount of pressure as a range of factors such as budget, time, compliance, GDPR, and business continuity implications have to be carefully implemented into the plan.

    The challenges of cloud migration are mostly connected to time, cost, and the risks involved in rewriting enterprise applications for cloud databases. These rewriting projects typically take years to complete with constant scope revisions. When faced with such a seemingly bleak landscape, one might ask “Is there a magic tool which enables on-premise applications to run on cloud databases instantly, without touching the application?”. That’s where Liberatii comes to the rescue!

    In this webinar, following topics will be covered:
    Problem with modernizing legacy databases and applications (with industry-specific examples)
    Introduction to Liberatii data virtualization technology
    Benefits of Liberatii data virtualization
    Features of Liberatii data virtualization
    Cloud migration process using Liberatii's data virtualization
    Product demo
    By the end of the presentation, participants will learn how Liberatii's data virtualization technology helps enterprises reduce the time, cost and the risk of migrating applications to the cloud. This virtualization approach enables faster migration and provides a shortcut to realize the benefits of the cloud.
  • Super-charge your Data Analytics Journey with FPGA-accelerated computing Recorded: Oct 22 2020 51 mins
    Alok Gupta, Xilinx Inc. | Mr. Ambrose Finnerty, Xilinx Inc.
    Enterprise and scientific users are becoming increasingly aware of the value contained within the vast quantities of data now collected from the physical and virtual worlds. Demand for data analytics is typically proportional to the amount of data being generated. As the quantity of data continues to expand exponentially, the need for data analytics will grow at a similar rate. Contemporary hardware and software architectures cannot be leveraged cost-effectively to meet the data generation, storage, and analytics needs. Hence, there is an urgent need for new and novel approaches based on heterogeneous compute platforms that appropriately couple CPU and FPGA resources. FPGAs, with their configurability, flexibility, scope for parallelism, and power efficiency, ensure effective and efficient acceleration of data-processing workloads.

    Artificial intelligence and data analytics are the defining workloads of the coming decade. Xilinx hardware and software solutions accelerate the development and deployment of AI and data analytics workloads in the data center, cloud and intelligent edge. Eventually taking the leap in data centre modernization requires three things and Presenters will talk about how to handle these challenges with Xilinx technology:

    • Need of Advancement in computing power that enable real-time, in-memory processing of vast amounts of data.
    • Tools that let data scientists develop analytic models using machine-learning techniques that can extract value from unstructured data.
    • Frameworks that enable software developers to easily incorporate data science models in the applications they develop.

    Take Away for attendees:
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    • You will learn how Xilinx technology can supercharge your data science activities.
    • You will learn the Top N challenges in Data Analytics and how to tackle them.
  • Computational Storage Workloads - Implications for Datacenter Architectures Recorded: Oct 21 2020 32 mins
    Jamon Bowen, Product Planning & Storage Segment Director, Xilinx
    Xilinx is deeply involved in several computational storage products with a range of partners.  From this vantage point we have identified the common elements of workloads that map well to
    Computations Storage Drives (CSDs), Computational Storage Processors (CSPs), and Computational Storage Arrays (CSAs).  The properties of these workloads will be outlined with brief examples. 

    There is a growing effort to standardize the programming and deployment interfaces for computational storage and the programming interface (api) of Xilinx computational storage platforms will be covered with some discussion of extending computational storage over a fabric.
  • Managing Software Defined of Everything in Data Tsunami Environment Recorded: Oct 21 2020 40 mins
    Dr. Shahin Arefzadeh, CTO/Problem solver, ReadRite
    Key takeaways from this presentation:
    - How hybrid IT will be operating in on-premises, cloud, edge, colocation or managed hosting
    - How data centers are shifting towards business-driven business models
    - Is automation still a nice-to-have?
    - How relevant will asset inventory of infrastructure products, people, processes and providers become?
    - Understanding resiliency and data governance for vertical markets
    - What about 5G hype?


    Dr. Arefzadeh has over 20 years’ experience in the IT, Telecommunication, and TV Broadcast industries, serving in a variety of CISO, CTO, and principal engineering roles for numerous multinational corporations, such as Granite and Ericsson.

    Dr. Arefzadeh has also helped launch several German tech start-ups and was responsible for Dimetis’ products in Broadcast OSS for distribution and contribution networks and grew the company size nearly tenfold in 6 years while multiplying the revenue.

    Dr. Arefzadeh is a published author and a featured speaker at leading industry events such Telco Cloud Forum, Digital Transformation World, 5G World, Blockchain East, and Broadband Forum on topics such as AI, Blockchain, IoT, and Next Generation Networks and Systems.
  • Constructing Holistic Networks 4G, 5G and IoT Recorded: Oct 21 2020 33 mins
    Chris Bower, Technical Consultant, UKConnect
    Resiliency and availability are two key words when it comes to data centre communications. No matter if you are operating a local or Co-Lo data centre, businesses will always want a solution that covers them both.

    As UK Connect’ Technical Consultant I will share my thoughts and knowledge on 4G, 5G and IoT networks. Not only that, but some key insights on how the construction industry has utilised this mobile broadband infrastructure.
  • Collaborative Computing Agents in Construction of Self-Organized IoT Recorded: Oct 21 2020 31 mins
    Yeghisabet Alaverdyan, Head of Systems Integration Department, Yerevan
    The Internet of Things that use sensors to capture data with embedded information exchange capability promotes newer technological value creation. Conventional IoT may comprise computing devices, finite state machines, objects, or biological beings. In the age of big data, IoT opens up a new world of data sources and motivates Intelligent Data Analytics.

    The heterogeneity of things mostly resembles the human body where the set of interconnected separate organs with individual functioning and communication capabilities serves a vital purpose. With this regard, adoption of relevant technologies along with Adaptive Software development methodologies may create strong premises for organic systems construction. Here, in order to resolve issues in intelligence, security and governance of intelligent IoT, the whole network of Things may be enhanced to the Internet of self-organized and collaborative computing agents.

    For the purpose, the following concepts in Computing science should emerge:

    • Multi-agent cognitive systems
    • Information integration to serve a targeted purpose
    • Predicate logic to govern deductive agents
    • Semantic graph to model the enhanced IoT
  • Automating networks through the machine learning driven insight Recorded: Oct 21 2020 43 mins
    Martin Blunn, Chief Technology Officer, Solutionize Global
    Many elements of infrastructure have the capability to adapt with principles such as scale on demand. Networks have generally stayed static due to their complexity and fixed nature of the underlay provider and the ability to perform consistent rapid change.

    In recent times Artificial Intelligence has been integrated in almost all elements of information and communication technologies with the use of machine learning and deep learning becoming quite commonly applied in various day to day applications.

    The majority of network components produce large amount of raw data much of which currently is ignored or discarded in favour on focusing on availability and key performance metrics.

    Machine learning algorithms have been developed for communication networks to be applied to fundamental problems in networking, including traffic prediction, routing and classification, congestion control, resource, fault management, QoS and QoE management and network security.
    Software defined networks (SDN) provide the ability to program network configuration through the use of open standards and DevOps tools such as Terraform and Ansible. Central orchestration engines provides the ability to deploy configuration to the edge through a controlled and consistent method.

    So, we have the building blocks for an adaptable network, driven by metrics provided on a real or near real time basis.

    Key Takeaways will be:

    • Generation of real time metrics to provide insight in the performance of a network for end user
    experience
    • Consumption of metrics to be processed by the appropriate machine learning algorithm with
    validation of learning by network professionals
    • Dynamic configuration of networks through programmatic interface centrally orchestrated
    • An iterative programmatic approach to continually change with appropriate lag to continually adapt to the needs of the business applications and introduction of new services
  • Expanding Storage Through Disaggregation - And Now What? Recorded: Oct 20 2020 45 mins
    Michael Schuette, DataSecure LLC | Bojian Wang, Fungible | Ryan O'Donnell & Peter Donnelly, Atto
    Disaggregated data storage allows for more flexible and cost-effective resource allocation. Using conventional storage servers is not taking advantage of the latest technology and adds unnecessary hardware, performance bottlenecks, power consumption and cost compared to a modern switch fabric. We’ll be discussing various types of innovative novel approaches including different strategies for NVMeoE, Direct Attached Storage over Fibre Channel (DASoFC) and their advantage in different environments. Finally, managing the deluge of data within a switch fabric is becoming an overwhelming challenge that needs to be addressed by dedicated Data Processing Units (DPUs) to streamline communication and data access between storage and processing units.
    Key points:
    • Server bottlenecks
    • Disaggregating storage via NVMeoE and DASoFC
    • Managing the deluge of data through DPUs

    Presenters: Michael Schuette, Ph.D., Co-Founder and CTO, DataSecure LLC.
    Ryan O'Donnell, Product Line Marketing Manager, Atto
    Peter Donnelly, Manager, Products Group, Atto
    Bojian Wang, Principal Solution Architect, Fungible
  • How can databases capitalize on Computational Storage? Recorded: Oct 20 2020 40 mins
    Tong Zhang, Chief Scientist & Co-Founder | JB Baker, VP of Marketing & Product Management, Scaleflux
    Systems and storage are evolving, with a new category of products called Computational Storage Devices emerging to alleviate problems with database performance bottlenecks and the costs of ever-growing datasets.

    Do you need to modify your database to capitalize on this emerging class of storage?
    What advantages can you get without code changes?
    Can using “wasteful” data structures actually reduce storage footprint while improving performance?

    Join us as we answer these questions and provide examples of benefits you can see today and in the near future through combining Computational Storage with Database operations.
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The Enterprise Architecture channel presents the next generation of Enterprise IT: recognizing the strategic importance of digital transformation and the data center to make companies more nimble and competitive. These presentations will help demanding IT and BizOps professionals achieve flexibility, scalability and performance with reduced risk and complexity.

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