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C5050-287 Foundations of IBM Cloud Reference Architecture V5

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C5050-287 exam Dumps Source : Foundations of IBM Cloud Reference Architecture V5

Test Code : C5050-287
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: 60 Real Questions

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IBM Foundations of IBM Cloud

Google close to Launching IBM i Cloud provider, Will Says | killexams.com Real Questions and Pass4sure dumps

June four, 2018 Alex Woodie

probably the most laments of vigour chip kinds everywhere is the lack of a public cloud carrier for energy functions. while Linux and home windows folks can run their X86 workloads on numerous public clouds, the opportunities for internet hosting IBM i, AIX, or power Linux workloads are restricted to so-known as deepest clouds. but in accordance with IBM i chief architect Steve Will, that might soon be altering.

whereas neither IBM nor Google have made any professional bulletins about Google running IBM i in its public cloud, Will talked brazenly in regards to the relationship between both tech giants at ordinary‘s PowerUp convention in San Antonio, Texas, two weeks ago. all over the way forward for IBM i panel on Sunday, may additionally 20, Will brought up that Google “became on your doorstep” of offering an IBM i provider, and that they should be keeping a watch on the information for that announcement.

This wouldn’t be magnificent, but it could be news. Ever considering that IBM and Google started working collectively during the OpenPower groundwork and Google all started the use of Power8 processors in its public cloud offering manner back in 2014, there has been hypothesis that Google may, if it desired to, run the IBM i operating equipment and IBM i workloads. (enterprise issues, as opposed to technical ability, are typically the limiting factors in these styles of preparations.)

That hypothesis of a Google-IBM i connection endured this spring, when the net large introduced that it become now not simplest constructing its own systems with Power9 chips, but that it turned into adopting new Power9-based mostly energy Linux servers from IBM to change one of the vital X86 servers powering its ubiquitous search engine.

Google spent about $30 billion to build and expand its eight world information facilities from 2014 to 2017.

Will pointed out getting Google to move from the usage of vigour techniques servers to run search engine workloads to the usage of energy programs servers to run real construction company workloads on the Google Cloud Platform could be simply yet another step in the ongoing relationship.

“They have not yet made any announcement about being capable of run AIX or IBM i in their Google Cloud,” Will said during the panel. “but as a cloud company, they’re looking to get mid-dimension and large agencies to turn over some of their computing. with a purpose to do this, they’re going to should do this with i, AIX, and z. What make sure to be hunting for in the news is when does that start to happen.”

large companies had been general to make use of the chance of internet hosting big iron workloads as a carrot to get concessions from private cloud suppliers for his or her X86 workloads. a lot of managed provider suppliers (MSPs) have advised IT Jungle as plenty through the years, and it’s some thing so that you can repeated on the PowerUp display, too.

however, it’s a enterprise apply that no public cloud company can emulate for the fundamental proven fact that no public cloud company at present helps huge iron workloads. IBM doesn’t even guide IBM i workloads with its SoftLayer cloud, which it currently renamed IBM Cloud private, even though it can store IBM i backup statistics there as BLOBs in an object shop; IBM i backups can also be saved on Amazon internet functions S3 object system, too.

however storing IBM i statistics or backup data is distinctive than truly running IBM i workloads. in line with Will, these limitations on operating IBM i workloads on public cloud platforms are about to exchange.

Chief Architect of IBM i Steve Will

“I actually have conferences on my calendar with other public cloud providers [besides Google] who need to be able to sell cloud into enterprise,” Will talked about. Bringing cloud to company “is exceptional if you’re developing games to run on these telephones. that you can try this on a bunch of little home windows, or extra probably Linux, servers. in case you wish to run business, you’ve received to run mainframe and also you’ve acquired to run i. That’s just the way it's. finally three years from now, I don’t be aware of if Amazon may have, though i believe they are going to, an i providing. however they understand that Google is on your step.”

right through a briefing with IT Jungle the following day, Will changed into requested even if Microsoft Azure, the third essential public cloud, can be a different vicinity the place IBM i may run at last. while he didn’t offer any specifics, he indicated that conversations have taken vicinity.

“simply as a result of they haven’t run everybody yet doesn’t suggest we’re no longer going to,” Will referred to during the panel discussion. “We partnered with Google because Google desired to partner with us and Amazon didn’t are looking to accomplice with us. So hi there Google is going to be successful with energy. Now I have Amazon calling, asking us. What happens more commonly than no longer,” Will endured, “is that the cloud issuer will go to a customer and the consumer will say ‘smartly which you can have my computer stuff in the cloud if you take my i with you.’ So now the cloud providers are coming to me and asserting ‘neatly, how do I get your i within the cloud?’ smartly, thank you very an awful lot.”

linked stories

IBM i Finds A Youthful Swagger Down In Texas

past And Future Collide At PowerUp 18

Google exhibits Its own Power8 Motherboard; Can It Run IBM i?


dear Colleague Letter: Addition of IBM as a Cloud useful resource company to the FY 2018 BIGDATA Solicitation | killexams.com Real Questions and Pass4sure dumps

This document has been archived.

April 13, 2018

dear Colleagues:

via this expensive Colleague Letter (DCL), the national Science foundation's (NSF) Directorate for laptop and suggestions Science and Engineering (CISE) desires to notify the community that IBM has joined as probably the most cloud resource suppliers for the fiscal yr (FY) 2018 important concepts, applied sciences, and Methodologies for Advancing Foundations and applications of massive facts Sciences and Engineering (BIGDATA) program solicitation(see https://www.nsf.gov/funding/pgm_summ.jsp?pims_id=504767 for more tips concerning the program).

As historical past, NSF announced last yr the availability of a cloud choice as part of the FY 2017 BIGDATA solicitation, with participation by using Amazon web capabilities (AWS), Google Cloud (GCP), and Microsoft Azure. The cloud alternative enabled tasks to request cloud substances in guide of their huge data analysis and schooling activities, mainly specializing in colossal-scale experimentation and scalability reports.

This alternative continues to be in vicinity for the FY 2018 BIGDATA solicitation, with AWS, GCP, and Microsoft Azure continuing their participation. moreover, IBM has now joined the BIGDATA program as one of the crucial cloud aid suppliers, beneath the same phrases and stipulations as applicable to the entire other cloud suppliers. The corresponding phrases and conditions are described in the FY 2018 BIGDATA program solicitation, purchasable at https://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf18539.

Proposers might also use here IBM resources to strengthen the full cost of cloud materials along with an annual usage plan over the length of the initiatives:

As described within the solicitation, the request for cloud substances will be reviewed along with the leisure of the proposal. credit might be allocated both for the cloud provider requested within the concept, or for equivalent elements from an option cloud provider.

Please read the total solicitation cautiously before making ready your inspiration.

Please notice that the submission time limit for the FY 2018 BIGDATA solicitation is might also 7-14, 2018.

As referred to within the application solicitation, the NSF BIGDATA program webpage discovered at https://www.nsf.gov/funding/pgm_summ.jsp?pims_id=504767 will proceed to be up-to-date to listing all cloud providers presently participating in the software. As of the date of this DCL, these are Amazon, Google, Microsoft, and now IBM.

Questions about the BIGDATA application solicitation, together with the cloud choice, may still be directed to the cognizant application directors listed within the solicitation.

truly,Jim KuroseAssistant DirectorComputer and advice Science and Engineering


Cloud profits Makes Up 20% of IBM’s income in 3Q | killexams.com Real Questions and Pass4sure dumps

IBM grew its cloud and safety revenue in the third quarter of 2017, helping large Blue beat Wall highway’s expectations despite posting an common decline for the twenty second straight quarter.

Cloud now represents 20 % of IBM’s total earnings. This profits movement hit $15.8 billion over the ultimate one year, up 25 p.c 12 months-over-12 months. Third-quarter cloud revenues expanded 20 p.c to $four.1 billion.

The business’s third-quarter safety profits ($600 million) jumped fifty one % from a year earlier.

in the meantime complete salary within the third quarter was $19.2 billion, a lower of under 1 percent year-over-12 months.

On an profits call with analysts, IBM CFO Martin Schroeter credited protection and cognitive features embedded within the business’s hardware and application items with boosting its protection earnings.

“consumers found threats 60 times faster than guide investigations, and sophisticated evaluation went from an hour to lower than a minute,” Schroeter talked about.

each cloud and protection, along with as-a-provider choices, Watson, and mobile are a part of IBM’s strategic imperatives enterprise, which represents forty five % of IBM profits. Strategic imperatives profits reached $34.9 billion over the remaining 12 months, becoming 10 % year-over-12 months. Third quarter profits was up eleven percent.

As IBM Cloud has struggled to keep tempo with opponents Amazon web services (AWS) and Microsoft Azure, the business has taken steps to position its cloud as the most business-friendly cloud. This contains building a world community of cloud facts facilities and concentrated on specific industries like healthcare and monetary functions with its cloud-based mostly Watson artificial intelligence (AI) and blockchain features.

Schroeter emphasized this theme on the incomes call. “keep in mind, the IBM Cloud is developed for the business. it is the best cloud that integrates public, deepest, multi-cloud and conventional information facilities through a single structure and is designed for cognitive workloads.”

In a research word, BMO Capital Markets analyst Keith Bachman known as IBM’s third quarter profits “most economical outcomes” and raised its stock target price to $a hundred and seventy from $167.

“final analysis, they suppose IBM had an affordable quarter,” Backman wrote. “We agree with a key for IBM’s stock will be IBM’s capacity to retain or increase CY18 operating margins and/or working earnings, at the same time as they continue to be skeptical that IBM can develop CY18 revenues.”


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Foundations of IBM Cloud Reference Architecture V5

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What’s behind Linux’s new Cloud Native Computing Foundation? | killexams.com real questions and Pass4sure dumps

Today a group of 19 companies, led primarily by Google, created a new open source foundation that aims to specify how clouds should be architected to serve modern applications.

The Cloud Native Computing Foundation is housed in the Linux Foundation and includes big names such as Google, IBM, Intel, Box, Cisco, and VMware, along with a variety of smaller companies like Docker, Cycle Computing, Mesosphere and Weaveworks.

artforbrandon

+MORE AT NETWORK WORLD: Linux Foundation gathers heavy hitters for container orchestration body | Google releases v1 of cloud and container manager Kubernetes +

 One of the foundation’s headlining responsibilities is to set the direction for Google’s open source container management software named Kubernetes. But there’s a lot more to this announcement beyond that.

What’s actually happening?

This group of 19 companies hopes to create a reference infrastructure architecture for  applications hosted in the cloud.

The Cloud Native Computing Foundation (CNCF) wants to put together a blueprint of what components are needed and how they should be assembled to support distributed, scale-out applications. The foundation also wants to allow vendors and users to plug in their own components to that architecture too.

It’s sort of like creating instructions to build a Lego set, but saying you can use whatever colored pieces you want to actually construct it.

The initial parts of the project include Google’s Kubernetes and Mesosphere’s data center operating system, named DCOS, both of which are open source projects.

Didn’t they just create a new open source container project?

To astute observers of the cloud and container market, the creation of the CNCF may sound like déjà vu. It was less than a month ago when Docker announced the Open Container Initiative. The focus of that project is deliberately narrow and focuses on standardizing what a container is (it’s runtime and format, in technical terms), says Bryan Cantrill, CTO of Joyent and a member of the CNCF’s technical committee.

The CNCF has a broader goal of defining what an entire infrastructure stack looks like that supports cloud-native applications and containers.

In the Lego example, the Open Container Initiative (OCI) is getting everyone to agree on what size the Lego blocks are, while the CNCF is creating the instructions of how to build the Lego set.

Why should I care?

Containers are all the rage nowadays, but as people have started to use containers they are realizing shortfalls in the technology. The CNCF is trying to fix that.

It’s one thing to create a container – but it’s a whole other thing to manage clusters of them. Stuart Miniman (@stu on Twitter) wrote about this in a post describing the components that are needed to run containers. It includes things like container networking, service discovery, scheduling and security. The CNCF is arguing that a whole infrastructure blueprint should be designed to support containers and cloud-native applications.

The CNCF is advancing the discussion to consider how containers should be managed, not just how they’re created. That’s a good thing for the industry, and for end users. Big enterprise buyers aren’t going to really use containers until there are are mature platforms for managing them.

Who’s in, who’s out

To really drive home what the CNCF is trying to do, it’s telling to examine which vendors are part of this collaborative effort and which are not. The OCI had 21 members. Today’s CNCF has 22 members.

The OCI included members like Amazon Web Services, EMC and Microsoft. But those three vendors are NOT in the CNCF. Why? Because the CNCF is attempting to create a reference architecture for running applications and containers, and Google’s Kubernetes will likely play a big role in that. AWS and Microsoft already have a reference architecture for running containers and they’re not looking to support competitor Google’s. Amazon CTO Werner Vogels came out this week with a detailed explanation of the Amazon Elastic Container Service (ECS), which is AWS’s way of managing containers. Microsoft supports both Linux and Windows containers in its Azure cloud. But, AWS and Microsoft are on board with the OCI’s effort to standardize what a container is.

Most CNCF members are not tied to a specific infrastructure stack. Companies like Box, Cycle Computing and Twitter, want to advance the cause of cloud-native applications, but they don’t necessarily care where those applications run.

Meanwhile, there are a group of 10 vendors that are in both the OCI and CNCF. These include Cisco, Docker, Goldman Sachs, Intel, Red Hat and VMware. These companies are looking to strategically support both open source initiatives.

Join the Network World communities on Facebook and LinkedIn to comment on topics that are top of mind.

Making Dark Medical Data Visible | killexams.com real questions and Pass4sure dumps

According to a recent market survey conducted by HIMSS Media, an average of 66 percent of the unstructured data in healthcare enterprises remains inaccessible and unavailable for patient care decisions. Because a major portion of this data seems to be invisible and hard to manage, many organizations are overwhelmed by the abundance of data, rather than enabled and empowered.

In addition, InfoWorld published that most data scientists spend only 20 percent of their time on actual data analysis and 80 percent of their time finding, cleaning, and reorganizing huge amounts of data – an unfortunate and inefficient data strategy, indeed.

In an industry that is becoming even more data-driven and evidence-based, organizations must embrace new technologies that will help them manage data efficiently and uncover the many meaningful insights still hidden in their mountains of data.

Deploying a robust and holistic data strategy that enables healthcare organizations to leverage all their growing volumes of data usually dispersed across geographic and organizational boundaries is key to accelerating precision medicine and impacting the health of individuals. At the heart of this strategy lies a scalable, agile and sustainable IT foundation that can support the demands of precision medicine and is based on three key principles:

First, the architecture must be based on software-defined infrastructure (SDI) solutions that offer advanced policy-driven data and resource management capabilities. Although this infrastructure is built upon hardware solutions with chips and processors and data that resides in storage systems, they need to remember that the ability to operate, orchestrate, protect and manage data intelligently exists in the software, or in the middleware that sits between the hardware and the applications. This IT architecture must also support an open framework and the hundreds, if not thousands, of applications being developed in the areas of genomics, imaging, clinical analytics, artificial intelligence and deep learning. Many of these applications are isolated in functional and operational siloes, creating the need for a shared compute and storage infrastructure based on advanced software to consolidate and transform static, siloed systems into dynamic, integrated, and intelligent infrastructure, resulting in faster analytics and greater resource utility.

Second, any solution needs to follow a proven reference architecture that has been fully-tested. The deep experience they have at IBM with world-class healthcare and life sciences customers has taught us that software capabilities can easily be dictated by the underlying hardware building blocks (CPU vs GPU, on-premises vs cloud, x86 vs Power9) and even more so by the applications they need to serve. Without a consistent framework and roadmap in the form of a reference architecture, things can fall apart very quickly. Initially, building a robust data strategy and underlying IT infrastructure may take more effort, but the value and benefits that your organization can gain will be much more long-lasting and wide-reaching in terms of speed, scale, collaboration, ease of use and costs.

Finally, the architecture needs to be part of a global ecosystem. They all realize that collaboration does not exist within the four walls of a single organization anymore. They see many research initiatives between top cancer centers, genome centers and large pharma R & D and biotech companies that involve strategic partnerships around the globe. The common reference architecture they all use enables them to easily collaborate and share data.

For example, a research hospital can develop a cancer genomics pipeline and share it with another institution quickly, either by sending the XML-based script or publishing it in a cloud-based portal like an application store. They have also started to see early examples of data sharing using metadata and RESTful APIs. Based on this approach, parallel communities or consortia are being formed for digital medical imaging, translational research and big data analytics. This makes parallel discovery possible.

[Learn more about Advance precision medicine with trusted data and AI solutions] The journey of the reference architecture

IBM’s high-performance data and AI (HPDA) architecture for healthcare and life sciences was designed to boost medical research efforts. It is based on best practices that have been tested with top healthcare solution providers and partners, and most importantly with customers that are at the forefront of precision medicine, such as Sidra Medicine.

For the first generation of the references architecture that was established in 2013, they designed a “Datahub” as an abstraction layer for handling demanding genomics requirements such as high-throughput data landing, information life cycle management and global namespace regardless of sharing protocol. These requirements could sometimes be met easily on a single workstation or small cluster, but the capability to handle hundreds of servers and petabytes of data is what made the Datahub so unique and essential. And what made the Datahub even more valuable was its intrinsic scalability to start small (or big) and grow and scale out rapidly based on the workloads. As the next-gen sequencing technologies were rapidly advancing, the data and workloads could grow at a rate of 100% every six months. The Datahub fulfills these requirements through software in concert with storage building blocks (flash, disk and tape library) that support tiering based on performance and cost objectives.

We also designed an “Orchestrator” as the second abstraction layer for handling application requirements and mapped it towards the computing building blocks. It has specified functions such as parallel computing and workflow automation which can be fulfilled by software in concert with computing resource such as an HPC cluster or virtual machine farms.

This software-defined blueprint was essential to future-proof the infrastructure and sustain the usability of applications so that the hardware building blocks could be expanded or replaced without impacting the operation of the system, the running of the application, and ultimately the user experience.

The reference architecture has continued to evolve throughout the years to reflect the enormous changes on numerous fronts that healthcare and life sciences organizations have had to face due to disruptive market forces that constantly reshape the industry and the way patient care is delivered.

The main investments we’ve made in the last two years were focused on positioning the reference architecture as a true data-driven, cloud-ready, AI-capable solution that addresses very complex data at scale and the most demanding analytics requirements with cost-effective high-performance capabilities.

At this point, the second generation of the reference architecture has been developed and includes advanced features and solutions based on feedback we’ve received from users in fields of research and clinical practices such as genomics, metabolomics, proteomics, medical imaging, clinical analytics, biostatistics and even real-world evidence (RWE) and the internet of things (IoT).

One of the most exciting things that they observe is that this collaboration across fields has actually started to bring more and more users together to work and share their experiences.

We are fortunate to witness and document these challenges and the needs of leading institutes at the frontiers of precision medicine. Thanks to their HPDA-based solutions, they are experiencing significantly faster times to results, along with many other benefits. The results can be a genomics analysis of clinical variants for patients, or an AI model developed to diagnose Alzheimer’s disease, or new biomarkers for cancer. In all these cases, traditional desktop computing could no longer keep up with the workloads or the data storage. Previously, these users had to wait days or even weeks for data to be transferred and loaded, then even longer for processing and analysis. But after implementing the HPDA reference architecture – not anymore.

Learn more about some of the leading precision medicine initiatives around the globe supported by IBM’s high performance data and AI (HPDA) architecture at Bio-IT world.


Lightbend's Reactive Architecture Course on CognitiveClass.ai Reaches 17,000 Students Enrolled | killexams.com real questions and Pass4sure dumps

SAN FRANCISCO, March 28, Mar 28, 2019 (GLOBE NEWSWIRE via COMTEX) -- SAN FRANCISCO, March 28, 2019 (GLOBE NEWSWIRE) -- Lightbend today announced that less than a year after its original launch, its self-paced training series -- Lightbend Reactive Architecture: Foundations and Lightbend Reactive Architecture: Advanced -- have reached 17,000 students enrolled, making them one of IBM Cognitive Class' fastest-growing course series. IBM's Cognitive Class features a series of free data science and cognitive computing courses, with a virtual lab environment that enables users to practice what they learn.

The Lightbend Reactive Architecture series are a crash course in building distributed cloud-native systems using microservices, with a self-paced format and guidelines from Lightbend experts. The Lightbend Reactive Architecture series have codified lessons learned, best practices, reference architectures, design patterns and analysis techniques, drawing from Reactive's track record of success at companies like LinkedIn, Verizon Wireless, Capital One and Walmart Canada.

The Reactive Manifesto, originally published anonymously but later revealed as the work of Lightbend co-founder and Akka creator Jonas Boner, for the first time set out key principles for building systems that react to modern demands on distributed services at scale. Translated into 15 languages with endorsements by more than 23,000 technologists, the Reactive movement has become the de facto guideline for distributed system design.

The Lightbend Reactive Architecture series features two Cognitive Learning Paths, each containing three self-paced, free courses:

1- Lightbend Reactive Architecture: Foundations

  • Introduction to Reactive Principles
  • Domain Driven Design
  • Reactive Microservices
  • 2- Lightbend Reactive Architecture: Advanced

  • Building Scalable Systems
  • Distributed Messaging Patterns
  • CQRS & Event Sourcing
  • Next Steps If You Are Interested to Enroll in Lightbend Reactive Architecture Series:

  • Read the full course descriptions
  • Sign up for free self-paced training
  • About LightbendLightbend (@Lightbend) is leading the enterprise transformation toward real-time, cloud-native applications. Lightbend Platform provides scalable, high-performance microservices frameworks and streaming engines for building data-centric systems that are optimized to run on cloud-native infrastructure. The most admired brands around the globe are transforming their businesses with Lightbend, engaging billions of users every day through software that is changing the world. For more information, visit www.lightbend.com.

    Editorial ContactLonn Johnston+1 650.219.7764lonn@flak42.com

    (C) Copyright 2019 GlobeNewswire, Inc. All rights reserved.



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