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000-281 - Foundations of IBM Cloud Computing(R) Architecture V2 - Dump Information

Vendor : IBM
Exam Code : 000-281
Exam Name : Foundations of IBM Cloud Computing(R) Architecture V2
Questions and Answers : 100 Q & A
Updated On : October 19, 2018
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000-281 Questions and Answers

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000-281 Foundations of IBM Cloud Computing(R) Architecture V2

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000-281 exam Dumps Source : Foundations of IBM Cloud Computing(R) Architecture V2

Test Code : 000-281
Test Name : Foundations of IBM Cloud Computing(R) Architecture V2
Vendor Name : IBM
Q&A : 100 Real Questions

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  • 000-281 Foundations of IBM Cloud Computing(R) Architecture V2

    Study Guide Prepared by Killexams.com IBM Dumps Experts


    Killexams.com 000-281 Dumps and Real Questions

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    000-281 exam Dumps Source : Foundations of IBM Cloud Computing(R) Architecture V2

    Test Code : 000-281
    Test Name : Foundations of IBM Cloud Computing(R) Architecture V2
    Vendor Name : IBM
    Q&A : 100 Real Questions

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    Foundations of IBM Cloud Computing(R) Architecture V2

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    No result found, try new keyword!While Microsoft, according to its site, doesn’t actually have a quantum computing lab in the Triangle, IBM does ... committed to “R&D efforts for upcoming compute opportunities at the edge of 5G netwo...

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    Definitions

    Edge computing is a relatively new concept that has already been associated with another term, 'fog computing', which can lead to confusion among non-specialist observers. Here are some definitions that will hopefully clarify the situation.

    Futurum ResearchUnlike Cloud Computing, which depends on data centers and communication bandwidth to process and analyze data, Edge Computing keeps processing and analysis near the edge of a network, where the data was initially collected. Edge Computing (a category of Fog Computing that focuses on processing and analysis at the network node level)...should be viewed as a de facto element of Fog Computing.

    State of the Edge 2018The delivery of computing capabilities to the logical extremes of a network in order to improve the performance, operating cost and reliability of applications and services. By shortening the distance between devices and the cloud resources that serve them, and also reducing network hops, edge computing mitigates the latency and bandwidth constraints of today's Internet, ushering in new classes of applications. In practical terms, this means distributing new resources and software stacks along the path between today's centralized data centers and the increasingly large number of devices in the field, concentrated, in particular, but not exclusively, in close proximity to the last mile network, on both the infrastructure and device sides.

    451 Research/OpenFog Consortium[Fog] begins on one 'end' with edge devices (in this context, we define edge devices as those devices where sensor data originates, such as vehicles, manufacturing equipment and 'smart' medical devices) that have the requisite compute hardware, operating system, application software and connectivity to participate in the distributed analytics Fog. It extends from the edge to 'near edge' functions, such as local datacenters and other compute assets, multi-access-edge (MEC) capabilities within an enterprise or operator radio access network, intermediate computing and storage capabilities within hosting service providers, interconnects and colocation facilities, and ultimately to cloud service providers. These locations have integrated or host 'Fog nodes', which are devices capable of participating in the overall distributed analytics system.

    David Linthicum (Chief Cloud Strategy Officer at Deloitte Consulting)"With edge, compute and storage systems reside at the edge as well, as close as possible to the component, device, application or human that produces the data being processed. The purpose is to remove processing latency, because the data needn't be sent from the edge of the network to a central processing system, then back to the edge...Fog computing, a term created by Cisco, also refers to extending computing to the edge of the network. Cisco introduced its fog computing in January 2014 as a way to bring cloud computing capabilities to the edge of the network...In essence, fog is the standard, and edge is the concept. Fog enables repeatable structure in the edge computing concept, so enterprises can push compute out of centralized systems or clouds for better and more scalable performance."

    Here's how the OpenFog Consortium visualises the relationship between data-generating 'things' at the network edge, cloud data centres at the core, and the fog infrastructure in between:

    openfogdiagram.png

    openfogdiagram.png

    Image: OpenFog Consortium Market estimates

    According to B2B analysts MarketsandMarkets, the edge computing market will be worth $6.72 billion by 2022, up from an estimated $1.47bn in 2017 -- a CAGR (Compound Annual Growth Rate) of 35.4 percent. Key driving factors are the advent of the IoT and 5G networks, an increase in the number of 'intelligent' applications, and growing load on cloud infrastructure:

    Edge computing market dynamics

    Drivers
  • Growing load on cloud infrastructure
  • Wide range of applications in different industries
  • Increase in the number of intelligent applications
  • Restraints
  • Security and privacy concerns related to edge computing
  • Opportunities Challenges
  • Inadequate industry standards and interoperability issues
  • [Data: MarketsandMarkets]

    Among the vertical segments considered by MarketsandMarkets, Telecom and IT is expected to have the biggest market share during the 2017-2022 forecast period. That's because enterprises faced with high network load and increasing demand for bandwidth will need to optimise and extend their Radio Access Network (RAN) in order to deliver an efficient Mobile (or Multi-access) Edge Computing (MEC) environment for their apps and services.

    The fastest-growing segment of the edge computing market during the forecast period is likely to be retail, says MarketsandMarkets: high volumes of data generated by IoT sensors, cameras and beacons that feed into smart applications will be more efficiently collected, stored and processed at the network edge, rather than in the cloud or an on-premises data centre.

    Grand View Research takes a more conservative view, estimating that the edge computing market will be worth $3.24 billion by 2025, although that's still a 'phenomenal' CAGR of 41 percent over the 2017-2025 forecast period. Regionally, North America will lead the market due to increasing penetration of IoT devices in the US and Canada, said the research firm, while the vertical segment with the highest CAGR will be healthcare and life sciences, thanks to "storage capabilities and real-time computing offered by edge computing solutions". SMEs will witness the highest CAGR (46.5%) over the forecast period, said Grand View Research, thanks to the ability of edge computing solutions to reduce operating costs.

    The most optimistic growth estimate comes from 451 Research, in an October 2017 study -- Size and Impact of Fog Computing Market -- commissioned by the OpenFog Consortium. This wide-ranging research puts the market opportunity for fog computing at $18.2 billion by 2022, up from $1.03bn in 2018 and $3.7bn in 2019 -- a CAGR of 104.9 percent between 2018 and 2022.

    451-openfogmarket-forecast-1.png

    451-openfogmarket-forecast-1.png

    Data: 451 Research & OpenFog Consortium / Chart: ZDNet

    According to 451 Research, the leading verticals for fog computing in 2022, in terms of market share, will be utilities, transportation, healthcare, industrial and agriculture.

    451-openfogmarket-forecast-22.png

    451-openfogmarket-forecast-22.png

    Image: 451 Research & OpenFog Consortium

    When it comes to the fog computing ecosystem in 2022, 451 Research breaks down the components like this:

    451-openfogmarket-forecast-3.png

    451-openfogmarket-forecast-3.png

    Data: 451 Research & OpenFog Consortium / Chart: ZDNet

    Hardware components are well out in front, with a 42.1 percent slice of the 2022 pie, followed by fog applications/platforms (21.5%) and fog services (20.4%). No wonder hardware vendors and cloud application/services providers are queueing up to get involved in the fast-developing edge/fog market.

    Despite their different emphases, these forecasts make it clear that the 'perfect storm' for edge computing is being created by a rapidly increasing number of internet-connected devices and the imminent advent of high-bandwidth, low-latency 5G networks. Ericsson's June 2018 Mobility Report summarises the expected developments in these areas.

    Whereas PCs, laptops, tablets and (to a lesser extent) mobile phones show flat growth between 2017 and 2023, IoT devices are taking off: those with wide-area connections will see 30 percent CAGR, with short-range IoT devices showing significant but slower growth (17% CAGR). This results in an almost 80 percent (79.4%) increase in the number of connected devices between 2017 (17.5 billion) and 2023 (31.4 billion):

    ericsson-connected-devices.png

    ericsson-connected-devices.png

    * Cellular IoT devices are a subset of Wide-area IoT devices.

    Data: Ericsson Mobility Report, June 2018 / Chart: ZDNet

    As far as 5G is concerned, Ericsson expects the first data-only devices from the second half of 2018 and the first 5G smartphones in 2019. By 2023, following the advent of third-generation chipsets in 2020, the company forecasts that 1 billion 5G devices will be connected worldwide.

    ericsson-5g-devices.png

    ericsson-5g-devices.png

    CPE/FWT: Customer-Provided Equipment/Fixed Wireless Terminal

    Image: Ericsson Mobility Report, June 2018

    The first module-based 5G IoT devices, supporting ultra-low latency communications for industrial process monitoring and control, are expected during 2020, says Ericsson.

    Standards & organisations

    Any new IT initiative requires standards and best practices, and the early stages are often characterised by multiple groups and consortia with different agendas (despite often significant overlap in membership). Edge/fog computing is no exception.

    Fog computing, a term coined by Cisco, is backed by the OpenFog Consortium, which was founded in 2015 by Arm, Cisco, Dell, Intel, Microsoft and the Princeton University Edge Laboratory. Its mission statement reads (in part):

    Our efforts will define an architecture of distributed computing, network, storage, control and resources that will support intelligence at the edge of IoT, including autonomous and self-aware machines, things, devices, and smart objects. OpenFog members will also identify and develop new operational models. Ultimately, our work will help to enable and drive the next generation of IoT.

    Edge computing is promoted by the EdgeX Foundry, an open-source project hosted by The Linux Foundation. EdgeX Foundry's goals include: building and promoting EdgeX as a common platform unifying IoT edge computing; certifying EdgeX components to ensure interoperability and compatibility; providing tools to quickly create EdgeX-based IoT edge solutions; and collaborating with relevant open-source projects, standards groups and industry alliances.

    According to EdgeX Foundry, "The project's sweet spot is edge nodes such as embedded PCs, hubs, gateways, routers, and on-premises servers to address key interoperability challenges where 'south meets north, east, and west' in a distributed IoT fog architecture".

    EdgeX Foundry's technical steering committee includes representatives from IOTech, ADI, Mainflux, Dell, The Linux Foundation, Samsung Electronics, VMWare and Canonical.

    There are two other industry bodies in this area: the Japan-focused EdgeCross Consortium, which was founded in November 2017 by Omron Corporation, Advantech, NEC, IBM Japan, Oracle Japan and Mitsubishi Electric; and the Industrial Internet Consortium, founded in 2014 by AT&T, Cisco, General Electric, Intel, and IBM.

    What the surveys say

    Edge Computing Index: From Edge to Enterprise

    futurumreport-cover.png

    futurumreport-cover.png

    Futurum Research surveyed over 500 North American companies (ranging from 500 to 50,000 employees) in late 2017 to discover their position on edge computing -- adoption and deployment, investment intent, and more. All respondents exerted influence on edge computing investment decisions, said Futurum, with 41.8 percent being 'operational staff' and 25.6 percent at 'director, manager, team lead' level; only 8.6 percent were classed as 'executive, C-suite, owner, partner' though.

    Futurum reported that nearly three-quarters (72.7%) of companies had already implemented an edge computing strategy, or were in the process of doing so. Furthermore, almost all (93.3%) intended to invest in edge computing in the next 12 months:

    futuruminvestmentoutlookchart.png

    futuruminvestmentoutlookchart.png

    Data: Futurum Research / Chart: ZDNet

    Futurum also curates a general Digital Transformation Index, which in 2018 put 68 percent of companies in the 'leaders' and 'adopters' categories. So the fact that 72.7 percent of respondents are already investing in edge computing shows that this is a hot topic for tech-savvy businesses. However, Futurum also noted that "the eagerness of 93.3% of businesses to invest in edge computing in the next 12 months does not speak to the size of their investment".

    The positive vibes among Futurum's respondents continued when they were asked about the importance of edge computing data streams in their business processes, with 71.8 percent describing these as 'critically' (22.2%) or 'very' (49.6%) important:

    futurumimportancechart.png

    futurumimportancechart.png

    Data: Futurum Research / Chart: ZDNet

    What were the key drivers of this enthusiasm for edge computing? For Futurum's respondents, it was 'improved application performance', followed by 'real-time analytics/data streaming':

    futurumuse-caseschart.png

    futurumuse-caseschart.png

    Data: Futurum Research / Chart: ZDNet

    The analyst firm interpreted these priorities as a reflection of the need for operational efficiency, suggesting that the relatively low ranking for IoT strategy -- often quoted as a canonical edge computing use case -- "will likely increase in the coming years".

    Only 15.6 percent of Futurum's respondents aimed to keep edge computing and cloud computing separate -- a decision often driven by data and system security concerns, and a focus on compartmentalised operations, the research firm said. That leaves nearly 64 percent (63.9%) who had already deployed (28.3%) or were seeking (35.6%) combined edge/data centre analytics solutions, plus 20.5 percent who were unsure whether to combine these functions or keep them separate:

    futurumintegrationchart.png

    futurumintegrationchart.png

    Data: Futurum Research / Chart: ZDNet

    The 'unsure' and 'seeking' responses amount to 56.1 percent of the survey sample, which clearly represents a significant opportunity for edge computing providers.

    2018 Outlook for Fog Computing

    openfogsurvey-cover.png

    openfogsurvey-cover.png

    The OpenFog Consortium surveyed its 61 member organisations on the state of fog computing in December 2017, finding that an impressive 70 percent of CEOs were aware of the fog computing initiatives happening on their watch.

    Budgets for fog computing in 2018 were generally increasing (40%) or staying the same (51%), with just 5 percent of respondents reporting a decrease. Initiatives were primarily based in the R&D department (51%) and overwhelmingly had IoT applications as their primary focus area (70%).

    Security was the number-one concern among OpenFog respondents (32%), followed by worries about early/unproven technology, interoperability and unclear ROI. The main drivers of interest in fog computing were latency and bandwidth issues. Respondents expected manufacturing, smart cities and transportation to be the top industry segments adopting fog computing, followed by energy, healthcare and smart homes.

    Key vendors

    Edge/fog computing can pull workloads away from cloud data centres, so it's no surprise to see the cloud giants taking steps to prevent those workloads from escaping their orbit.

    AmazonIntroduced at Amazon's 2016 re:Invent developer conference, AWS Greengrass builds on the company's existing IoT and Lambda (serverless computing) offerings to extend AWS to intermittently connected edge devices.

    "With AWS Greengrass, developers can add AWS Lambda functions to a connected device right from the AWS Management Console, and the device executes the code locally so that devices can respond to events and take actions in near real-time. AWS Greengrass also includes AWS IoT messaging and synching capabilities so devices can send messages to other devices without connecting back to the cloud," said Amazon. "AWS Greengrass allows customers the flexibility to have devices rely on the cloud when it makes sense, perform tasks on their own when it makes sense, and talk to each other when it makes sense -- all in a single, seamless environment."

    aws-greengrass.png

    aws-greengrass.png

    Image: Amazon Web Services

    These are 'smart' edge devices, of course: Greengrass requires at least 1GHz of compute (either Arm or x86), 128MB of RAM, plus additional resources for OS, message throughput and AWS Lambda execution. According to Amazon, "Greengrass Core can run on devices that range from a Raspberry Pi to a server-level appliance".

    MicrosoftIntroduced at Microsoft's BUILD 2017 developer conference and generally available since June 2018, Azure IoT Edge allows cloud workloads to be containerised and run locally on smart devices ranging from a Raspberry Pi to an industrial gateway.

    Azure IoT Edge comprises three components: IoT Edge modules; the IoT Edge runtime; and IoT Hub. IoT Edge modules are containers that run Azure services, third-party services or custom code; they are deployed to IoT Edge devices and execute locally. The IoT Edge runtime runs on each IoT Edge device, managing the deployed modules, while IoT Hub is a cloud-based interface for remotely monitoring and managing IoT Edge devices.

    Here's how the different Azure IoT Edge elements fit together:

    azure-iot-edge.png

    azure-iot-edge.png

    Images: Microsoft

    With general availability, Microsoft added new capabilities to Azure IoT Edge, including: open-source support; device provisioning, security and management services; and a simplified developer experience.

    google-edge-tpu.jpg

    google-edge-tpu.jpg

    Google's Edge TPU ASIC, compared to a 1 cent coin.

    Image: Google

    GoogleIn July 2018, Google announced two products for developing and deploying smart connected devices at scale: Edge TPU and Cloud IoT Edge. Edge TPU is a purpose-built small-footprint ASIC chip designed to run TensorFlow Lite machine-learning models on edge devices. Cloud IoT Edge is the software stack that extends Google's cloud services to IoT gateways and edge devices.

    Cloud IoT Edge has three main components: a runtime for gateway-class devices (with at least one CPU) to store, translate, process and extract intelligence from edge data, while interoperating with the rest of Google's Cloud IoT platform; the Edge IoT Core runtime that securely connects edge devices to the cloud; and the Edge ML runtime, based on TensorFlow Lite, that performs machine-learning inference using pre-trained models.

    google-cloud-iot-edge.png

    google-cloud-iot-edge.png

    Image: Google

    Both Edge TPU and Cloud IoT Edge are at the alpha testing stage at the time of writing (September 2018).

    Outlook

    The edge/fog computing transformation is one of those shifts in focus that happen periodically in computing -- from mainframes to desktop PCs, to on-premises data centres, to cloud data centres, for example. Now we're looking at a mix of existing elements, along with billions of smart IoT devices, bound together by an intervening 'fog' of gateways and nodes. Device connectivity has been a bottleneck holding back this transformation, but that's about to get a huge boost with the advent of 5G mobile networks.

    Any industry sector that can derive benefit from the timely analysis of IoT data streams -- and that's pretty much all of them -- will be interested in edge/fog computing. That's why there are huge opportunities for vendors at all levels of the technology stack -- standards, networking, compute, storage, applications and services.

    With ever more data being generated, processed and stored in ever more locations, issues surrounding infrastructure management and data security, privacy and governance will become even more important than they are today. Let's hope those issues are addressed sooner rather than later.

    RECENT AND RELATED CONTENT

    Understanding Edge ComputingThe edge is that theoretical space where a data center resource can be accessed in the minimum amount of time. The location could be in the data center, on the desktop, or wherever there's a need.

    Microsoft Azure gets new tools for edge computing and machine learning (TechRepublic)Announced at the Microsoft Ignite conference today, these new features are designed to streamline the collection, processing and analysis of large volumes of data.

    VMware taps IoT to extend hybrid and multi-cloud environments to the edge (TechRepublic)At VMworld 2018, VMware unveiled its extended edge computing strategy to better control, secure, and scale customers' edge and IoT applications and solutions.

    IT leader's guide to edge computing (Tech Pro Research)Companies of all sizes and across various industries are moving to edge computing to generate, collect, and analyze data so they can take immediate action on that information. This guide looks at the pros and cons of edge computing and how its real-world usage has been working out.


    Cloud Computing Test Bed: Live Notes From The Conference Call | killexams.com real questions and Pass4sure dumps

    Hewlett Packard, Intel and Yahoo announced the Cloud Computing Test Bed this morning. Executives from the three companies are holding a 9 am PST conference call to discuss the new venture. Participating are Prith Banerjee, Senior Vice President, Research, HP and Director, HP Labs; Prabhakar Raghavan, Head of Yahoo! Research; and Andrew Chien, Vice President, Corporate Technology Group, Intel and Director, Intel Research.

    The product is a distributed computing platform for third party research and application building. My live call notes are below.

    Notes, in chronological order:

    …waiting for call to begin

    Prith Banerjee from HP began the call and introduced Andrew Chien and Prabhakar Raghavan. Summarizing the key news: HP, Intel and Yahoo are partnering with governments and academic institutions to create an open source cloud computing test bed with six distributed centers. Global, distributed, Internet scale platform. The main goal is to remove financial and logistical barriers for people to develop cloud computing application. Partners include the University of Illinois at Urbana-Champaign, and the Karlsruhe Institute of Technology (KIT) in Germany.

    HP believes we are entering an era of “everything as a service.” Businesses and users will use the services, which will anticipate your needs based on location, etc. This shift towards everything as a service will require a new approach. HP will conduct research in two areas: intelligent infrastructure and cloud services. They say they’ll experiment with radically new data center structures.

    Andrew Chien from Intel: cloud computing is a big challenge. important technology issues around hardware stack to drive performance, energy usage, etc. This isn’t a “test tube” study, it’s a large scale distributed global platform. “Intel has a long history of open collaboration” he says.

    Prabhakar Raghavan from Yahoo: Says Yahoo is pleased to be a cofounder of the project. Want to take Internet research “to the next level.” Says the next generation of the web demands collaborative research. Discussing M45 data center they launched with Carnegie Mellon and other projects where they experimented with cloud computing. Says this announcement is in the spirit of the earlier partnerships. Building and contributing to an “intellectual commons.”

    Questions:

    – how are each company contributing?

    Each company is providing people and resources, and each is creating one of the six test beds. Research can be conducted across the stack. Yahoo has contributed open source software, from the OS to Hadoop. Chien reiterates support for open source software. Says some of the pieces of the data centers are up and running now.

    – Size of investment by each company?

    not disclosing financial terms. each facility will have 1,000- 4,000 processor cores.

    – web needs a new architecture…please expand?

    They want people to take the cloud for granted, so people can create applications at any scale.

    – have they measured how much collective computing power? Why not part of IBM/Google research announced last year?

    we’re complimentary to IBM/Google, and also different. they are going to allow people to run low levels of customized software. IBM/Google is focused on application level right now. In terms of scale, they say not to focus on total computational capability, but to focus on scalability.

    – idea of timeline? what will finished products look like?

    some of this is underway and being used. M45 datacenter has been in operation since 2007, this takes it to a broader level. they are looking to see publication of research by all parties, contribution to an intellectual commons.

    – have they received government R&D funds?

    says they are partnering with the national science foundation and various academic organization, never really answered the question.

    – can others join this group? IP ownership?

    Chien says they are taking a leadership step. open to more people contributing. On IP ownership, they are making clear statements about what is open source, commitment to openness.

    Note: I was not allowed to ask a question for some reason. Things I would have asked:

    1. How do third parties open their own facilities/data centers? What if Stanford wants to open a facility?

    2. Pricing: How will resources be allocated to people building on the platform?

    3. Where to people go for information on APIs and other tools needed to access the platform?

    4. Yahoo kept referring to M45 as a version of this already deployed. Is that their contribution or are they building out a new facility.

    Overall this is super squishy, and appears to be more of a hype release than anything. More details are needed. A lot more.



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    IBM 000-281 Exam (Foundations of IBM Cloud Computing(R) Architecture V2) Detailed Information



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