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000-740 IBM Storage Networking Solutions Version 1

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000-740 exam Dumps Source : IBM Storage Networking Solutions Version 1

Test Code : 000-740
Test designation : IBM Storage Networking Solutions Version 1
Vendor designation : IBM
: 138 true Questions

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IBM IBM Storage Networking Solutions

Microsoft Vs. IBM: One clear Winner | killexams.com true Questions and Pass4sure dumps

No result discovered, are attempting unusual keyword!IBM and Microsoft are two cloud ... ever higher economies of scale and rising network outcomes. truly, cloud computing is never well-nigh records storage for organizations. The superior winners in ...

Storage and AI work together in IBM’s multicloud method | killexams.com true Questions and Pass4sure dumps

a huge focal point of the bulletins from IBM Corp.’s feel convention ultimate week worried synthetic intelligence and making it attainable throughout complete cloud platforms. This “AI in every lone place” method applies to IBM’s storage strategy as neatly.

In December, IBM introduced a storage gadget co-designed with Nvidia Corp. for AI workloads and various facts tools, reminiscent of TensorFlow. AI reference architecture is additionally built-in in IBM’s power line of servers.

there is curiously a further most notable AI integration in the works, as IBM continues to focal point on the hybrid cloud. “We’re working on a third one presently with one other main server seller because they want their storage to live anyplace there’s AI and any location there’s a cloud — massive, medium or small,” pointed out Eric Herzog (pictured), chief advertising officer and vice president of international storage channels at IBM.

Herzog spoke with John Furrier (@furrier) and Stu Miniman (@stu), co-hosts of theCUBE, SiliconANGLE Media’s cellular livestreaming studio, complete the artery through the IBM feel event in San Francisco. They discussed IBM’s focus on cyber resilience in its storage products and assembly client needs in a multicloud atmosphere. (* Disclosure below.)

New points for resiliency

moreover multicloud and AI, IBM’s storage operation has additionally been focused on cyber resilience. In August, the company launched Cyber Incident recovery among the many points covered within the latest free up of its Resiliency Orchestration platform.

the unusual product become designed to rapidly salvage well facts and applications following a cyberattack. “sure, each person is used to the ‘superb wall of China’ keeping you, and then of course chasing the rotten man down after they transgression you,” Herzog stated. “however when they transgression you, it will bound live first-rate if every thing had facts at leisure encryption.”

Enhancements to IBM’s storage portfolio during the last 12 months gain been designed to accommodate customer environments that are more and more multicloud-oriented. The focus has been on application-described storage options that movement and give protection to suggestions in a Big ambit of compute ecosystems, as Herzog wrote in a fresh weblog submit.

“You may gain NTT Cloud in Japan, you may additionally gain Alibaba in China, you can moreover gain IBM Cloud Australia, after which you may gain Amazon in Latin the us,” noted Herzog, who appeared at the convention wearing a symbolic Hawaiian surfer shirt. “You don’t battle the wave; you journey the wave. And that’s what every person is coping with.”

Watch the complete video interview beneath, and compose confident to retract a study at more of SiliconANGLE’s and theCUBE’s insurance of the IBM reckon experience. (* Disclosure: IBM Corp. subsidized this section of theCUBE. Neither IBM nor different sponsors gain editorial control over content on theCUBE or SiliconANGLE.)

image: SiliconANGLE because you’re right here …

… We’d want to let you know about their mission and how you could assist us fulfill it. SiliconANGLE Media Inc.’s company model is in keeping with the intrinsic value of the content, now not promoting. unlike many on-line publications, they don’t gain a paywall or flee banner advertising, because they wish to hold their journalism open, devoid of move or the requisite to chase site visitors.The journalism, reporting and commentary on SiliconANGLE — together with reside, unscripted video from their Silicon Valley studio and globe-trotting video teams at theCUBE — retract loads of tough work, time and money. retaining the first-rate extreme requires the assist of sponsors who're aligned with their imaginative and prescient of advert-free journalism content.

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IBM i DevOps gets less complicated On Skytap Cloud | killexams.com true Questions and Pass4sure dumps

February 25, 2019 Alex Woodie

IBM i professionals who long for the administrative simplicity of Amazon web functions will quickly live rewarded when Skytap’s IBM i cloud becomes commonly attainable subsequent quarter. among the many IBM partners Skytap is tapping for the roll-out is Rocket application, which is integrating the Aldon suite of lifecycle administration tools to simplify DevOps in a probably ground-breaking unusual means.

Rocket application is in the procedure of certifying its Aldon Lifecyle supervisor for IBM i (LMi) application to flee on Skytap‘s public cloud providing for IBM i. Late closing yr, Skytap, which has Amazon’s Jeff Bezos as a Big investor and which is additionally based mostly in Seattle like Amazon, unveiled plans for Skytap Cloud for IBM i, with the goal to permit purchasers to spin IBM i environments up and down from the comfort of a web interface.

David Romo, the director of software engineering for Rocket application, which is based on Waltham, Massachusetts, says the aggregate of Aldon LMi and Skytap’s bendy cloud environment has the talents to alternate the DevOps sustain for IBM i gurus.

“the primary consume case could live for excellent assurance,” Romo tells IT Jungle. “so that you simply spin up a computing device. Aldon would installation the code to that machine. you can examine it, after which dispose of the computer – delete it – once you are accomplished testing.”

Skytap made a reputation for itself by artery of helping businesses to control complicated cloud-based mostly functions that span diverse operating structures, including AIX on energy and Linux and windows on X86. With the introduction of IBM i on power, Skytap will let shoppers add one other working device to their virtualized property.

Romo is exceptionally enamored of Skytap “environments,” that are collections of virtualized IBM vim and Intel X86 machines operating in Skytap’s cloud. The virtual machines are linked through Skytap’s utility defined community, and valued clientele can scale these divide environments up and down as a cohesive unit. once valued clientele gain configured an environment to their liking, they could set it aside as a examine-handiest template that they can designation every time they like.

“that you could instantiate these templates and then you gain got a all system,” Romo says. “if you had an atmosphere that blanketed a construction machine, a QA machine, and a construction desktop, which you could spin up as many of these as you need, and that they’re complete going to live operating in the period of time it takes for them to IPL.”

this will vastly diminish the friction that evolution groups invariably visage when tasked with spinning up construction and QA methods for testing unusual code. In an on-premise environment, getting construction and QA systems constantly entails filling out a ticket for the IT admins to fill. In a private cloud ambiance, getting these hardware supplies can involve sending an electronic mail request, and ready days for the unusual environments to log on.

“That’s some thing that they are able to carry out internally now with their Intel techniques,” Romo says. “we can spin those up and spin these down on an as-needed basis. but with the IBM i partitions, we’re not definitely in a position to carry out that yet. they are able to’t salvage a fresh, manufacturer-new partition to carry out checking out on, whereas with the VMware, that’s how we’re doing it.”

Skytap uses IBM PowerVM below the covers to spin IBM i and AIX photos up and down. however instead of disclosing to valued clientele the complexity of PowerVM – now not to mention the Hardware management Console (HMC) – it gives them a web UI or a RESTful API for managing IBM i and AIX materials.

“some of their clandestine sauce is the artery that they seize VM photographs, the style they tangle the storage, and then their total application-defined networking, which supports Layer 2 and above,” says Dan Jones, Skytap’s vp of product. “Aldon users could gain a amalgamate of interacting with the Aldon UI in addition to interacting with the Skytap UI. Then below the covers, the Aldon UI can provision an ambiance from a template, spin it up, deploy software to it, and then reserve it off as [another] template.”

The capacity to spin IBM i QA and construction environments up and down as mandatory will retailer shoppers Big amounts of cash and ache on the DevOps front, Jones predicts.

“in case you suppose about how most valued clientele flee IBM i today, as a result of the capital outlay on the hardware, they’re no longer in reality in a position the location they can spin up and spin down non-production workloads at will,” he says. “they've their hardware purchase, the location they simply sort of depart everything operating. And if they’re at capability and requisite to dawn up yet another venture, well ware they going to shut down to startup this other task? Are they going to gain to retract expend tens of heaps of greenbacks on one more server and tens of heaps of bucks on licensing to salvage an entire different atmosphere up and working?”

Rocket is moreover working with Skytap to certify two other products on its cloud, including the iCluster HA/DR software and the Cloud Connector for IBM i, which lets valued clientele consume BRMS to shop backups to the cloud. Skytap gained’t assist tape connectivity for backups (it makes consume of a proprietary SSD-based storage layer), so the Cloud Connector could live captivating, Romo says.

Skytap is moreover working with two other IBM i tall availability utility providers, HelpSystems and Syncsort, to salvage their solutions licensed on its IBM i cloud before it goes GA. Its working with HelpSystems to salvage the community-based mostly (i.e. non storage-primarily based) PowerHA replication offerings operating on its cloud, whereas it’s working with Syncsort to salvage MIMIX running. There can live extra HelpSystems products licensed by the time Skytap Cloud for IBM i goes are living, which is slated to circle up before June 30.

IBM moreover has an pastime in Skytap, for a yoke of reasons. First, Skytap is an IBM Cloud client, and complete of its power programs offerings will flee in IBM Cloud datacenters. Secondly, IBM will resell the IBM i and AIX cloud choices as a solution referred to as IBM Cloud for Skytap options, or ICSS.

Thirdly, IBM has been working with Skytap to salvage a hold of a more robust licensing mannequin for running application in a public cloud environments. The particulars aren’t public yet, but Jones says the early feedback from consumers has been quite fantastic.

“We’ve been doing lots of evaluation, modeling, and engineering work to pattern out how will they try this translation between a licensing model that’s tied to the actual world, how carry out they translate that to clients who are working within the digital world,” Jones tells IT Jungle. “We’re relatively near to finalizing that. so far, the comments has been excellent, and that i believe we’ve been able to salvage it transcribed into a cloud-pleasant model. They believe they now gain that mannequin in region. They requisite to flee a few more simulations just to live confident that they don’t sojourn up underwater each and every month with giant IBM i licensing bills.”

connected STORY

Skytap Says It’s structure a ‘genuine Cloud’ offering for IBM i


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Huawei Enterprise presents innovative networking solutions at MWC 2019 | killexams.com true questions and Pass4sure dumps

No result found, try unusual keyword!Huawei Enterprise announced its presence at the Mobile World Congress (MWC 2019) in Barcelona in a bid to retract on rivals such as IBM, Cisco, HPE, Oracle, Microsoft, Juniper Networks ... storage produc...

HPC in Life Sciences portion 1: CPU Choices, soar of Data Lakes, Networking Challenges, and More | killexams.com true questions and Pass4sure dumps

For the past few years HPCwire and leaders of BioTeam, a research computing consultancy specializing in life sciences, gain convened to examine the condition of HPC (and now AI) consume in life sciences.

Without HPC writ large, modern life sciences research would quickly grind to a halt. It’s apt most life sciences research computing is less focused on tightly-coupled, low-latency processing (traditional HPC) and more relative on data analytics and managing (and sieving) massive datasets. But there is plenty of both types of compute and disentangling the two has become increasingly difficult. Sophisticated storage schemes gain long been de rigueur and recently speedily networking has become notable (no astonish given lab instruments’ prodigious output). Lastly, striding into this shifting environment is AI – profound learning and machine learning – whose deafening hype is only exceeded by its transformative potential.

Ari Berman, BioTeam

This year’s discussion included Ari Berman, vice president and generic manager of consulting services, Chris Dagdigian, one of BioTeam’s founders and senior director of infrastructure, and Aaron Gardner, director of technology. Including Dagdigian, who focuses largely on the enterprise, widened the scope of insights so there’s a nice blend of ideas presented about biotech and pharma as well as traditional academic and government HPC.

Because so much material was reviewed they are again dividing coverage into two articles. portion One, presented here, examines core infrastructure issues around processor choices, heterogeneous architecture, network bottlenecks (and solutions), and storage technology. portion Two, scheduled for next week, tackles the AI’s trajectory in life sciences and the increasing consume of cloud computing in life sciences. In terms of the latter, you may live intimate with NIH’s STRIDES (Science and Technology Research Infrastructure for Discovery, Experimentation, and Sustainability) program which seeks to slit costs and ease cloud access for biomedical researchers.

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HPCwire: Let’s tackle the core compute. last year they touched potential soar of processor diversity (AMD, Intel, Arm, Power9) and certainly AMD seems to gain foster on strong. What’s your retract on changes in core computing landscape?

Chris Dagdigian: I can live quick and dirty. My view in the commercial and pharmaceutical and biotech space is that, aside from things like GPUs and specialized computing devices, there’s not a lot of movement away from the mainstream processor platforms. These are people affecting in 3-to-5-year purchasing cycles. These are people who standardized on Intel after a few years of pain during the AMD/Intel wars and it would retract something of huge significance to compose them shift again. In commercial biopharmaceutical and biotech there’s not a lot of tantalizing stuff going on in the CPU set.

The only other thing that’s tantalizing that’s happening is as more and more of this stuff goes to the cloud or gets virtualized, a lot of the CPU stuff actually gets hidden from the user. So there’s a growing portion of my community (biomedical researchers in enterprise) where the users don’t even know what CPU their code is running on. That’s particularly apt for things like AWS batch, and AWS Lambda (serverless computing services) and that sort of stuff running in the cloud. I reflect I’ll discontinue here are stutter on the commercial side they are leisurely and conservative and it’s quiet an Intel world and the cloud is hiding a lot of the apt CPU stuff particularly as people retract serverless.

Aaron Gardner: That’s an tantalizing point. As more clouds gain adopted the Epyc CPU, some people may not realize they are running on them when they start instances. I would stutter moreover that the soar of informatics as a service and workflows as a service is going to abstract things even more. It’s relatively light today to flee most code with some flush of optimization across the Intel and AMD CPUs. But the gap widens a bit when you talk about, is the code, or portions of it being GPU accelerated, or did you switch architectures from AMD64 to Power9 or something like that.

We talked last year about a transition from compute clusters being a hub fed by large-spoke data systems towards a data cluster where the hub is the data lake with its various affecting pieces and storage tiers, but the spokes are complete the different types of heterogeneous compute services that span and back the workload flee on that system. They definitely gain seen movement towards that model. If you study at complete Cray’s announcements in the last few months, everything from what they are doing with Shasta and Slingshot, and work towards making the CS (cluster supercomputers) and XC (tightly coupled supercomputers) work seamlessly, interoperably, in the identical infrastructure, we’re seeing companies like Cray and others gearing up for a heterogeneous future where they are going to back multiple processor architectures and optimize for multiple processor architectures as well as accelerators, CPUs and GPUs, and gain it complete work together in a coherent whole. That’s actually very exciting, because it’s not about betting on one particular horse or another; it’s about how well you are going to integrate across architectures, both traditional and non-traditional.

Ari Berman: Circling back to what Chris said. Life sciences historically has been sort of leisurely to jump in and adopt unusual stuff just to try it or to observe if it will live three percent faster because the differences gained in learning generation at this point in life science for those three percent are not ground breaking – it’s fine to wait a miniature while. Those days, however, are dwindling because of the amount of data being generated and the urgency with which it has to live processed and moreover the backlog of data that has to live processed.

So they are not in life sciences at a point where – other than the differentiation of GPUs – applications are being designed specifically for different system processors other than for Intel. There’s some caveats to that. Normally as long as you can compile it and flee it on one of the main system processors and it can flee on a customary version of Linux, they are not optimizing for that; the exceptions to that are some of the built in math libraries that can live taken handicap of on the Intel system platform, some of the data offloading for affecting data to and from CPUs from remote or even internally, remembrance bandwidth really matters a lot, and some of those things are differentiated based on what kind of research you are doing.

HPCwire: It sounds a miniature like the battle for mindshare and market share among processor vendors doesn’t matter as much in life sciences, at least at the user level. Is that fair?

Ari Berman: Well, they really like a lot of the future architectures. AMD is coming out with for better remembrance bandwidth to handle things like PCIe links, having unusual interconnects between CPUs, and moreover the connection to the motherboard. One of the Big bottlenecks Intel quiet has to resolve is how carry out you salvage data to and from the machine from external sources. Internally they gain optimized the bandwidth a all lot, but if you gain huge central sources of data from parallel file systems, you quiet gain to salvage it in and out of that system, and there are bottlenecks there.

Aaron Gardner: With the Rome architecture affecting forward, AMD has provided a much better approach to remembrance access, affecting away from NUMA (nonuniform memory) to a central remembrance controller with uniform latency across dies. This is really notable when you gain up to 64 cores per socket. affecting back towards a more auspicious remembrance access model on a per node design flush I reflect is really going to assist provide advantages to workloads in the life sciences and that is certainly something they are looking at testing and exploring over the next year.

Ari Berman: I carry out reflect that for the first time in a while Power9 has some potential relevance, mostly because Summit and Sierra (IBM-based supercomputers) coming into play and those machines being built on Power9. I reflect people are exploring it but I don’t know that it will compose much of a play outside of just pure HPC. The other thing I meant to bring up is a location where I reflect AMD is ahead of Intel in fab technology. AMD is already manufacturing at 7nm versus the 14nm. I thought that it was really innovative of AMD to carry out a multiple nanometer fabrication for their next release of processors where the IO core is 14nm and the processing core is 7nm because, just for power and distribution efficiency.

Aaron Gardner: In terms of market share, I reflect AMD has been extremely strategic over the last 18 months because when you study at places that got burned by AMD in the past when it exited the server market, there were not enough benefits to warrant jumping back in fully right away. But AMD is really geared towards the economies-of-scale nature plays such as in the cloud where any handicap in efficiency is going to live appreciated. So I reflect they gain been strategic [in choosing target markets] and we’ll observe over the next yoke of years how it plays out. I reflect they are at the instant not in a location where the client needs to specify a unavoidable processor. They are going to observe the integrators influence here, what they pick to set together in their heterogeneous HPC systems portfolio, influence what CPUs people salvage and that may really effect the winners and losers over time.

ARM they observe continue to grow but not explosively and I’d stutter Power is certainly interesting. Having the large Power systems at the top of the TOP500 has really validated Power9 for consume in capability supercomputing. How those are used though versus the GPUs for target workloads is interesting. In generic they may live headed to a future where the CPU is used to circle on the GPU for unavoidable workloads. Nvidia would probably favor that model. It’s just very tantalizing the interplay between CPU and GPU; it really does gain to carry out with whether you are accelerating a miniature number of codes to the nth degree or you are trying to gain more diverse application back which is where multiple CPU and GPU architectures are going to live needed.

Ari Berman: Using GPUs is quiet a huge thing for lots of different reasons. At the instant GPUs are hyped for AI and ML, but they gain been used extensively for a lot of the simulation space, Schrodinger suite, molecular modeling, quantum chemistry, those sorts of things, and moreover down into phylogenetic inference, special inheritance, things like that. There are many noteworthy applications for realistic processors, but really I would disagree with others that it really boils down to system processors and GPUs at the instant in life sciences. I did hear anecdotally from a yoke of folks in the industry that were using the IBM Q cloud just to try quantum [computing], just to observe how it worked with really tall flush genomic alignment and they kind of got it to work and I’ll leave it at that.

HPCwire: They probably don’t consecrate enough coverage to networking given its significance driven by huge datasets and the soar of edge computing. What’s the condition of networking in life sciences?

Chris Dagdigian: In pharmaceuticals and biotech, Ethernet rules the world. The tall hasten low latency interconnects are quiet in niche environments. When they carry out observe non-ethernet fabrics in the commercial world they are being used for parallel filesystems or in specialized HPC chemistry & molecular modeling application environments where MPI message passing latency actually matters. However I will bluntly stutter networking hasten is now the most critical issue in my HPC world. I feel that compute and storage at petascale are largely tractable problems. affecting data at scale within an organization or outside the boundaries of your firewall to a collaborator or a cloud is the lone biggest rate limiting bottleneck for HPC in pharma and biotech. Combine with that the cost tall hasten Ethernet has not gone down as speedily as the cost of commoditization in storage and compute. So they are in this double whammy world where they desperately requisite speedily networks.

The corporate networking people are fairly smug about the 10 gig and 40 gig links they gain in the datacenter core whereas they requisite 100 gig networking going outside the datacenter, 100 gig going outside the building, sometimes they requisite 100 gig links to a particular lab. Honestly the artery that I handle this in enterprise is I am helping research organizations become a champion for the networking groups; they traditionally are under budgeted and don’t typically gain 40 gig and 100 gig and 400 gig on their radar because you know they are looking at bandwidth graphs for their edge switches or their firewalls and they just don’t observe the insane data movement that they gain to carry out between the laboratory instrument and a storage system. The second thing, and I gain utterly failed at it, is articulating that there are products other than Cisco in the world. That argument does not flit in enterprise because there is a tremendous installed base. So I am in the tangle 22 of I pay a lot of money for Cisco 40 gig and 100 gig and I just gain to live with it.

Ari Berman: I would disagree networking is one of the major challenges. Depending on what granularity you are looking at, I reflect most of the HPCwire readers will suffuse a lot about interconnects on clusters. Starting there, I would stutter they are seeing a fairly even distribution of pure Ethernet on the back sojourn because of vendors like Arista for instance, which is producing more affordable 100 gig low latency Ethernet that can live set on the back sojourn so you don’t gain to carry out the all RDMA versus TCP/IP dance necessarily. But most clusters are quiet using InfiniBand on their back end.

In life sciences I would stutter that they quiet observe Mellanox predominantly as the back end. I gain not seen life-science-directed organizations [use] a all lot of Omni-Path (OPA). I gain seen it at the NSF supercomputer centers, used to noteworthy effect, and they like it a lot, but not really so much in life sciences. I’d stutter the hasten and diversity and the abilities of the Mellanox implementation could really outclass what is available in OPA today. I reflect the delays in OPA2 gain distress them. I carry out reflect the unusual interconnects like Shasta/Slingshot from Cray are paving the artery to producing a reasonable competitor to where Mellanox is today.

Moving out from that, Chris is right. There are so many people using the cloud that don’t upgrade their internet connections to a wide enough bandwidth or retract their security enough out of the artery or optimize it enough so that people can effectively consume the cloud for data-intensive applications, that getting the data there is impossible. You can consume the cloud but only if the data is already there. That’s a huge problem.

Internally, a lot of organizations gain moved to heated spots of 100 gig to live able to drag data effectively between datacenters and from external data sources but a lot of 10 gig quiet predominates. I’d stutter that there is a lot of 25 gig implementations and 50 gig implementations now. 40 gig sort went by the wayside. That’s because of the 100 gig optical carriers where they are actually made up of four individual wavelinks and so what they did was to just wreck those out and so the configuration factors gain shrunk.

Going back to the cluster back end. In life sciences the intuition tall performance networking on the back sojourn of a cluster is really notable isn’t necessarily for inter-process communications, it’s for storage delivery to nodes. Almost every implementation has a large parallel distributed file system where complete of the data are coming from at one point or another. You gain to salvage them to the CPU and that backend network needs to live optimized for that traffic.

Aaron Gardner: That’s a common case in the life sciences. They primarily study at storage performance to bring data to nodes and even to drag between nodes versus message passing for parallel applications. That’s starting to shift a miniature bit but that’s traditionally been how it is. They usually gain looked at a lone tall performance fabric talking to a parallel files system. Whereas HPC as a all has for a long time dealt with having a speedily fabric for internode communications for large scale parallel jobs and then having a storage fabric that was either brought to complete of the nodes or anywise shunted into the other fabric using IO router nodes.

“One of the things that is very tantalizing with Cray announcing Slingshot is the aptitude to speak both an internal low latency HPC optimized protocol as well as Ethernet, which in the case of HPC storage removes the requisite for IO router nodes, instead allowing the HCA (host channel adapters) and switching to handle the load and protocol translation and complete of that. Depending on how transparent and light it is to implement Slingshot at the miniature and mid-scale I reflect that is a potential threat to the continued prevalence of traditional InfiniBand in HPC, which is essentially Mellanox today.”

HPCwire: We’ve talked for a number of years about the revolution in life sciences instruments, and how the gush of data pouring from them overwhelms research IT systems. That has set stress on storage and data management. What’s you sense of the storage challenge today?

Chris Dagdigian: My sense is storing vast amounts of data is not particularly challenging these days. There’s a lot of products on the market, very many vendors to pick from, and the actual act of storing the data is relatively straightforward. However, no one has centrally cracked the how they manage it, how carry out they understand what we’ve got on disk, how carry out they carefully curate and maintain that stuff. Overwhelmingly the preponderant storage pattern in my world is if they are not using a parallel files system for hasten it’s overwhelmingly scale-out network attached storage (NAS). But they are definitely in the era where some of the incumbent NAS vendors are starting to live seen as dinosaurs or being placed on a 3-year or 4-year upgrade cycle.

The other thing is there’s quiet a lot of interest in hybrid storage, storage that spans the cloud and can live replicated into the cloud. The technology is there but in many cases the pipes are not. So it is quiet relatively difficult to either synchronize or replicate and maintain a consistent storage namespace unless you are a really solid organization with really speedily pipes to the outside world. They quiet observe the problems of lots of islands of storage. The only other thing I will stutter is I am known for maxim the future of scientific data at relaxation belongs in an demur store, but that it’s going to retract a long time to salvage there because they gain so many dependencies on things that await to observe files and folders. I gain customers that are buying petabytes of network attached storage but at the identical time they are moreover buying petabytes of demur storage. In some cases they are using the demur storage natively; in other cases the demur storage is their data continuity or backup target.

In terms of file system preference, the commercial world is not only conservative but moreover incredibly concerned with admin tribulation and value so almost universally it is going to live a mainstream choice like GPFSsupported by DDN or IBM. There are lots of really tantalizing alternatives like BeeGFS but the issue really is the enterprise is nervous about fancy unusual technologies, not because of the fancy unusual technologies but because they gain to bring unusual people in to carry out the suffuse and feeding.

Aaron Gardner: Some of the challenges with how they observe storage deployed across life science organizations is how near to the bottom gain they been driven. With traditional supercomputing, you’re trying to salvage the fastest storage you can, and the most of it, for the least amount of money. The back needed is not the primary driver. In HPC as a whole, Lustre and GPFS/Spectrum Scale are quiet the predominate players in terms of parallel file system. The tantalizing stuff over the last year or so has been Lustre trading hands (from Intel to DDN). With DDN leading the charge, the ecosystem is quiet being kept open and I reflect carefully crafted so other vendors can provide solutions independently from DDN. They carry out observe IBM stepping up Spectrum Scale performance and Spectrum Scale 5offering a lot of apt features proven out and demonstrated on the apex and Sierra nature systems, making Spectrum Scale every bit as apposite as it ever was.

As far as performant parallel file systems there are tantalizing alternatives. There is more presence and momentum behind BeeGFS than they gain seen in prior years. They observe some adoption and clients interested in trying and adopting it but the number deployments in production and at a large scale is quiet pretty limited.

These days demur storage is seen more like a tap that you circle on and you are getting your demur storage through AWS or Azure or GCP. If you are buying it for on-premise, there’s miniature differentiation seen between demur vendors. That’s the perception at least. They are seeing interest in what they convoke next generation storage systems and file systems – things like WekaIO that provide NVMe over fabrics (NVMeOF) on the front sojourn and export their own NVMeOF native file system as opposed to conceal storage. This removes the requisite to consume something like Spectrum Scale or Lustre to provide the file system and can drain icy data to demur storage either on premise or in the cloud. They carry out observe that as a viable model affecting forward.

I would add stutter that speaking to NVME over fabrics in general; that it seems to live growing and becoming established as most of the unusual storage vendors coming on the scene are currently architecting that way. That’s apt in their book. They certainly observe performance advantages but it really matters how it’s done—it is notable that the software stack driving the NVME media has been purpose built for NVME over fabrics or at least significantly redesigned. Something ground up like WekaIO or VAST will perform very well. On the other hand you could pick NVME over fabrics as the hardware topology for a storage system, but if you then layer on a legacy file system that hasn’t been updated for it you might not observe much benefit.

Couple of other quick notes. It seems like storage benchmarking in HPC has been receiving more attention both in terms of measuring throughput and metadata operations, with the latter being valued and seen as one of the primary bottlenecks that govern the absolute utility of a cluster. For projects like the IO500 we’ve seen an uptick in participation, both from national labs as well as vendors and other organizations. The last thing worth mentioning is data management. Scraping data for ML training data sets, for example, is one of the things driving us to understand the data they store better than they gain in the past. One of the simple ways to carry out that is to tag your data and they are seeing more files systems coming on the scene with a focus on tagging as a core in-built feature. So while they foster at the problem from different angles you could study at what companies like Atavium is doing for primary storage or Igneous for secondary storage, providing the aptitude to tag data on ingest and the aptitude to drag data (policy-driven) according to tags. This is something that they gain talked about for a long time and gain helped a lot of clients tackle.”

Link to portion Two (HPC in Life Sciences portion 2: Penetrating AI’s Hype and the Cloud’s Haze)


Microsoft Vs. IBM: One clear Winner | killexams.com true questions and Pass4sure dumps

(Source: imgflip)

Dividend growth investing is one of the most powerful ways of compounding both income and wealth over time. But the universe of income investing is vast and not limited to stodgy leisurely growing companies and industry.

Cloud computing is one of the hottest growth industries right now and expected to remain so for the foreseeable future.

Analyst solid Gartner forecasts that from 2017 to 2021 the global cloud computing market will grow nearly 18% CAGR, or more than four times as speedily as the global economy.

Synergy Research estimates the cloud computing market is already $250 billion in size, and growing even faster, 32% in 2018, with parts of the industry posting 50% sales growth.

So it's no astonish that tech giants are racing to lock in market share in this large, tall margin and rapidly growing business. But unless you're Warren Buffett, you gain limited funds to invest, and most people want to maintain their portfolio to a manageable number of companies. This means income growth investors requisite to live selective with what cloud computing stocks they buy.

(Source: ZDNet)

So let's retract a study at two common dividend cloud companies, Microsoft (MSFT) and IBM (IBM), who are some of the biggest players in cloud computing. Specifically, observe how they compare in the six most notable categories dividend investors suffuse about.

Most importantly, learn why Microsoft has IBM beat, hands down, as the far better cloud computing dividend growth stock, even considering valuation. In fact, I await Microsoft to deliver about double IBM's total returns over the coming five years.

Dividend Profile: Winner Microsoft

Since dividend growth investing is complete about income, let's start by looking at how each company's dividend profile stacks up, starting with long-term growth records.

(Source: Simply Safe Dividends)

Since IBM has been paying dividends for much longer, initially you might reflect it has the edge. After all, it's very near to becoming a dividend aristocrat, while Microsoft won't achieve that status for another 16 years.

And in terms of dividend growth rates, IBM at first seems to measure up well to Microsoft, at least over the past 20 years. But note that IBM's dividend growth has been slowing down over time, while Microsoft's has remained stable (9.5% hike for 2019).

  • 2018 IBM dividend hike: 4.7%
  • 2017 dividend hike: 7.1%
  • 2016 dividend hike: 7.7%
  • That speedily payout growth from MSFT is courtesy of a vastly superior business model and growth trajectory (more on this later). But dividend growth rates and track records are just two parts of the dividend profile, safety is by far the most important.

    Company Yield TTM FCF Payout Ratio

    Simple Safe Dividends Safety Score (Out Of 100)

    Microsoft 1.6% 42% 98 (Very Safe) IBM 4.5% 49% 65 (Safe)

    (Source: Simply Safe Dividends)

    While IBM may tender three times the yield, Microsoft has one of the safest dividends on Wall Street. That's not just due to a slightly lower payout ratio, but a far superior equilibrium sheet.

    Company Net Debt/EBITDA Interest Coverage Ratio S&P Credit Rating

    Average Interest Cost

    Microsoft -1.0 12.8 AAA 3.6% IBM 1.6 18.3 A 1.7% Safe Limit 3 Or Less 8 Or More BBB- Or Better NA

    (Sources: Morningstar, Simply Safe Dividends, F.A.S.T Graphs, Gurufocus)

    Microsoft actually has $53.7 billion more cash than debt and only has higher borrowing costs because it mostly sticks to selling US bonds, while IBM is more dynamic in overseas bonds where rates are much lower. But note that Microsoft is just one of two companies with a AAA credit rating (JNJ is the other) which is higher than the US Treasury's.

    And they can't forget that IBM is going to retract on a lot of debt to fund its $34 billion acquisition of Red Hat (RHT). This purchase (the largest software company acquisition in US history) is portion of IBM's latest efforts to circle around its struggling business. Here's what Virginia Rometty (CEO since 2012) said regarding the strategic rationale for the purchase.

    “The acquisition of Red Hat is a game-changer. It changes everything about the cloud market...IBM will become the world’s #1 hybrid cloud provider." - Virginia Rometty (emphasis added)

    But while it's apt that Red Hat is a potentially smart and bold drag for IBM, according to the Harvard business Review about 80% of M&A fails to deliver long-term shareholder value. That's especially apt if a company overpays and IBM is paying a 63% premium for RHT. 10 and 30 times sales and free cash current is a loaded expense to pay that means IBM has miniature margin of mistake when it comes to executing on its integration and growth plans for its future hybrid cloud business (and its track record on overall execution is poor).

    But the large amount of debt IBM is taking on is a certainty, and S&P has already downgraded its credit rating from A+ to A over the far more bloated equilibrium sheet.

    Moody's has set IBM's credit rating on watch for a downgrade citing:

    "a substantial expand in leverage... and a departure from IBM's historical acquisition philosophy of making small, tuck-in acquisitions that limit integration risk." - Moody's (emphasis added)

    IBM will effectively live doubling its leverage ratio (debt/EBITDA) putting it above the 3.0 that's considered safe for most companies. As a result, IBM has said it will suspend buybacks for 2020 and 2021 to focus on deleveraging, but that will almost certainly imply even slower dividend growth in the years ahead.

    And they can't forget that doubling leverage this late in the economic cycle moreover carries its own risks. Bond yields, even for investment-grade debt, can live highly volatile, spiking during times of pecuniary market warning (as occurs in corrections and tolerate markets).

    Chart Data by YCharts

    With a recession possibly coming in 2020 or 2021, IBM might find itself facing tighter credit markets and higher refinancing costs that means it needs to execute flawlessly on its plan to recur to about a 1.7 leverage ratio by the sojourn of 2021.

    Growth Profile: Winner Microsoft

    Even more impressive than Microsoft's already large cloud revenue is the fact that it continues to grow that business at a breakneck pace and gain market share.

    That's at the expense of IBM, who has steadily been losing market share to larger, better funded, and nimbler giants like Amazon (AMZN), Alphabet (GOOG) and Alibaba (BABA). This explains Microsoft's far more impressive growth profile, both in terms of its top and bottom line.

    Microsoft Growth Profile

    (Source: Simply Safe Dividends)

    Since Satya Nadella took over as CEO of Microsoft from Steve Ballmer in 2014, the company's cloud and mobile first strategies gain seen it recur to solid revenue growth.

    That includes impressive growth in its most recent quarter of

  • 12% revenue growth
  • 18% operating income growth
  • 15% EPS growth
  • Cloud revenue grew 20%, fueled by 76% growth in Azure (92% full-year growth), Microsoft's cloud platform. Even more impressive is that commercial cloud (48% YOY growth) vulgar margins increased 5% to 62% over the past year, showing that Microsoft's overall cloud ecosystem is benefitting from ever larger economies of scale and rising network effects.

    Basically, cloud computing isn't just about data storage for companies. The ultimate winners in the industry will live companies that can combine data storage with advanced AI-based software and data analytics offerings that assist customers maximize efficiency and profits.

    Microsoft's one-stop shop in terms of productivity software, which is deeply integrated into Azure (as is LinkedIn now), is the main intuition Microsoft is able to achieve some of the industry's fastest growth rates while continuing to relish stout pricing power (wide moat).

    IBM Growth Profile

    (Source: Simply Safe Dividends)

    In contrast, IBM has struggled with declining or flat sales since 2012, when it began its latest major corporate turnaround effort. That involves selling declining legacy hardware businesses and focusing on strategic imperatives or SI, which includes analytics, cloud computing, security, and mobile. Basically, SI is the future tech divisions IBM hopes to fuel its eventual recur to tall single-digit earnings and free cash current growth.

    (Source: IBM investor presentation)

    However, while the street may gain liked IBM's most recent results (the capitalize of very low expectations) the company quiet reported a 3% decline in revenue (-1% in constant currency).

    (Source: Motley Fool)

    And nonexistent of its business segment posted impressive growth, including cognitive solutions, which is home to IBM's much-hyped Watson AI platform. The huge decline in systems was caused by the launch of the Z-mainframe rolling off its comps and shows that IBM's brief 2018 recur to positive top-line growth was not a trend reversal, but a temporary occurrence.

    In fairness to IBM, SI did compose up 53% of revenue in Q4 and 50% in 2018, which is a goal the company has spent years trying to reach. And in absolute terms, SI is growing strongly.

  • Quarterly SI sales growth: 15% YOY
  • TTM SI sales growth: 22% YOY
  • However, it should live pointed out that IBM has been suffering from steadily falling growth rates in SI and this is the collection of businesses that are suppositious to recur it to modest top-line growth in the future. Thus far they've been unable to accomplish that and with IBM losing market share in cloud, that slowing growth could continue, causing IBM to deliver bottom-line growth that's far below what management is guiding for over the long-term.

    In fact, according to FactSet Research analysts don't reflect current management can deliver anywhere near to tall single-digit EPS growth, but just 2.3% CAGR over the next five years (with sub 2% growth through 2020). Morningstar's 6.1% earnings growth forecast is the most bullish I've seen for the company, yet moreover has the company falling far short of its guidance.

    And those growth estimates now embrace Redhat, which is a very speedily growing and cash-rich company (over 30% FCF margins).

    (Source: IBM Red Hat Acquisition presentation)

    IBM says that Redhat will accelerate top-line growth 2% over the long-term, which would live a welcome relief for investors who gain sales descend or stagnate for seven straight years.

    (Source: IBM Red Hat Acquisition presentation)

    IBM claims that the deal will live accretive to cash current within one year which is notable since free cash current is what funds dividends and pays down debt. However, due to tall integration expenses, IBM is now guiding for a double-digit abate in FCF for 2019.

  • 2018 FCF: $13.3 billion
  • 2019 FCF guidance: $12 billion (-9.8%)
  • This continues a decade long trend of flat FCF/share, which explains why IBM's dividend growth has slowed over time. And given the requisite to deleverage ASAP to retain a stout credit rating and apt pecuniary flexibility in the future, income investors can likely await even slower payout growth through at least 2021 if not longer.

    IBM FCF/Share

    (Source: Simply Safe Dividends)

    In contrast, Microsoft's FCF/share growth, while far from the best in the industry, is at least trending higher over time.

    Microsoft FCF/Share

    (Source: Simply Safe Dividends)

    And maintain in intelligence that a Big intuition that Microsoft's FCF is up just 26% since Nadella took over is Microsoft's much higher spending on R&D and capex to accelerate its cloud growth.

    Chart Data by YChartsChart Data by YCharts

    What about IBM? Well, it too spends a lot on R&D, but far less than Microsoft, or its large cloud peers.

    Chart Data by YCharts

    And most importantly, IBM's investments over time gain failed to deliver stout returns on investment, which brings me to the most notable intuition that Microsoft is a far better investment.

    Business Quality: Winner Microsoft

    The attribute of a business, including management's capital allocation skills, is the most notable driver of long-term total returns. A apt proxy for business and management attribute is a company's profitability metrics.

    Company Operating Margin FCF Margin Return On Equity

    Return On Invested Capital

    Microsoft 33% 25% 39% 22% IBM 17% 9% 50% 21% Good Company Benchmark 12% 5% 10% 8%

    (Source: Simply Safe Dividends)

    Microsoft's margins are vastly superior to IBM's and the only intuition IBM has higher returns on equity is the much more leveraged equilibrium sheet. And while MSFT and IBM gain basically equal returns on invested capital today, the long-term trend of that management attribute proxy is what matters most.

    IBM ROIC Over Time

    (Source: Simply Safe Dividends)

    Since Rometty took over in 2012, IBM's ROIC has fallen by over 50%. In fairness, it has bounced back a bit from its 2017 lows, BUT the very expensive RHT acquisition is likely to send it plummetting to fresh 10+ year lows.

    In contrast, Nadella's tenure at MSFT has moreover turned around a long glide in ROIC that was due to Ballmer's complacency and horrific acquisition strategy. Nadella is the one who moved Microsoft from a perpetual license model focused on Windows to a subscription-based software as a service model deeply integrated into the cloud. He moreover quit the incredibly competitive and no margin wireless handset business that Ballmer failed to compete in. Morningstar's Dan Romanoff considers Nadella an "exemplary" CEO and I disagree wholeheartedly.

    Microsoft ROIC Over Time

    (Source: Simply Safe Dividends)

    It should live noted that the LinkedIn acquisition is a Big intuition that MSFT's ROIC dipped in 2017 but it's since bounced back nicely, due to the success that deal has proven to be.

    (Source: MSFT earnings presentation)

    Microsoft's 2016 $26.2 billion acquisition of LinkedIn was highly controversial at the time, with many fervor it harkened back to Steve Ballmer's illustrious penchant for lighting shareholder money on fire by vastly overpaying resulting in huge write-downs later.

    But as you can observe above, LinkedIn revenue is growing consistently at 30+% YOY thanks to similar growth rates in participation. Basically, Nadella bought LinkedIn to strengthen the cloud ecosystem by enhancing productivity-boosting features, which is helping to drive stout growth in commercial subscribers to Office 365. In fact, 89% of Microsoft's commercial software business is now subscriber based, creating annuity-like recurring monthly revenue.

    The most recent Big acquisition Microsoft made was the 2018 $7.5 billion stock-based purchase of Github. Github is the "Facebook of programmers" with 31 million accounts and 100 million codes stored in its cloud-based servers. Those programs serve over 1.5 million companies and organizations around the world and Microsoft hopes that those programmers will become addicted to the Azure-based platform that Github under MSFT ownership will provide.

    And while IBM is making what's likely a desperate and overpriced and debt-funded acquisition to strengthen its cloud position, Microsoft is making far less risky moves such as partnering with VMWare (VMW), Accenture (ACN), and Mastercard (MA) to tender ever improved services to its customers. Which is why it keeps landing Big clients like Exxon (XOM) to host its cloud needs. In fact, Microsoft's cloud business, which at 48% is growing more than twice as speedily as IBM's, is now hosting over 420,000 global companies and organizations. That includes 89% of the Fortune 100.

    What about IBM's Big investments? Well, the incompatibility between IBM and Microsoft's overall investment approach can live summed up like this. IBM mints patents, while Microsoft mints money.

    Watson is a noteworthy specimen of this, with IBM having spent billions on the AI platform over the years and hyping it to the moon via illustrious appearances on Jeopardy, and Superbowl commercials touting it as "one of the most powerful tools their species has created."

    Virginia Rometty has moreover spent years proclaiming that Watson was a game-changing differentiator for IBM that is "touching a billion people... and live able to address, diagnose, and handle 80 percent of cancer in the world."

    In fact, Rometty is illustrious for overpromising and under delivering. When she took over in 2012 and began IBM's now seven-year turnaround exertion she guided for $20 per share in Adjusted EPS in 2015. IBM missed that target by 26% ($14.90) and adjusted EPS fell to $13.8 in 2017 and 2018 and now management is guiding for "at least $13.8" in 2019 (but with 10% less FCF).

    Essentially Watson has, like most of IBM's Big R&D efforts and Rometty's promises, failed to deliver top or bottom line growth over time. For example, IBM's Cognitive Solutions segment, home of Watson, saw very miniature growth in the past quarter, despite the suppositious world-changing power of that AI platform.

    (Source: IBM earnings presentation)

    What's more, margins actually fell, showing that Watson based SI and cloud offerings don't gain stout pricing power, unlike Microsoft, where cloud margins are soaring year after year.

    This highlights my biggest issue with IBM in general, which is that management likes to consume the hottest buzzwords, and file lots of patents for promising future tech, yet investors never seem to benefit.

    In 2018 IBM's army of 8,500 researchers, engineers, scientists, and designers in 47 different U.S. states and 48 countries were granted a record 9,100 patents, the 26th consecutive year in which IBM received the most corporate patents in America.

    (Source: IBM)

    Over 5,000 of those patents were in "hot" industries like AI, cloud, and cybersecurity. The company is moreover getting patents for quantum computing, healthcare, and blockchain. From 1993 to 2018 IBM obtained over 110,000 patents which should compose it a preponderant designation in every industry in which it operates and set it up for a glorious Star Trek-like future.

    Yet one of the largest collections of patents on earth hasn't stopped IBM investors from losing money during Rometty's tenure, even factoring in dividends.

    Chart Data by YCharts

    While the market can, and often is wrong about a company's value in the short-term, over the long-term total returns are always a duty of apt management delivering solid growth in fundamentals like sales, cash flow, and dividends.

    When it comes to the attribute of the business, and its management, Microsoft under Nadella is unquestionably far superior to IBM under Rometty.

    Total recur Potential: Winner Microsoft

    Ultimately I'm not just interested in dividend stocks for the income, but because they are a proven source of noteworthy total returns over time. Total returns are a duty of three things: bow + long-term earnings/cash current growth (which dividends track) + valuation change.

    Company Yield 5 Year Expected Earnings Growth (Analyst Consensus) Total recur Expected

    Valuation-Adjusted Total recur Potential

    Microsoft 1.6% 12.3% 13.9% 15.0% IBM 4.5% 2.3% 6.8% 8.0% S&P 500 1.9% 6.4% 8.3% 3% to 8.2%

    (Sources: Simply Safe Dividends, Multipl.com, Morningstar, analyst estimates, Gordon Dividend Growth Model, Moneychimp)

    IBM certainly offers the superior yield, nearly triple that of Microsoft. And despite overpaying for Redhat and blowing up its equilibrium sheet, the dividend is quiet relatively safe. However, while Microsoft's current bow may live paltry, it's expected to grow earnings and cash current nearly six times as speedily as Big Blue. Morningstar actually expects 15% EPS growth from MSFT compared to 6.1% from IBM and they are usually conservative in their growth assumptions.

    While complete long-term growth forecasts must live taken with a grain of salt (educated guesstimates) in this case Microsoft's stout execution on cloud makes me reflect that 12% to 15% long-term earnings growth is a reasonable expectation. In contrast even that 2.3% consensus on IBM might live arduous to achieve given the company's ongoing struggles with its legacy hardware businesses and slowing SI sales growth.

    That's not to stutter that I reckon IBM a "sell" necessarily. After all, that attractive dividend should allow IBM to deliver near to the market's forward total returns in the coming years, as long as management can deliver on those VERY conservative growth estimates.

    But compared to Microsoft's recur potential, which is about three times that of the market and about double that of IBM, the better long-term investment from a total recur perspective is obvious.

    Risk Profile: Winner Microsoft

    All companies visage risks to their growth plans, and IBM and Microsoft are no different. The biggest risks investors requisite to live awake of is the cutthroat and speedily pace of change in an industry that is at the heart of disrupting so many sectors of the global economy.

    Cloud is an enormous, speedily growing and tall margin industry with tech giants like Amazon, Alphabet, and Alibaba investing billions each year to better their offerings and trying to cop market share. And there are dozens of smaller players, who are trying to out-innovate and or compete on price, which potentially could disrupt Microsoft's preponderant industry position.

    Now it's apt that network effects are stout in cloud, which is why the industry's top names (other than IBM) gain been steadily gaining market share. However, rising margins in cloud are largely due to tremendous economies of scale and not rising prices. For example, Amazon has slit its AWS prices 67 times over the past 12 years (yet AWS margins maintain rising).

    Microsoft's stout R&D efforts might live able to maintain margins rising for several more years but eventually, they will likely peak and leisurely earnings and cash current growth from the cloud (at least from margin expansion).

    Still, that's far superior to IBM's position which is infirm and getting weaker, as seen by its declining margins in complete segments, including SI and cloud.

    The other Big risk to reckon is that in order to compete with several giant and well-funded rivals Microsoft is going to occasionally compose Big acquisitions, as seen under Nadella with LinkedIn and Github.

    While LinkedIn appears to gain been a success, it's quiet too early to stutter whether $7.5 billion for Gitbub will prove a sensible move. The strategic rationale for that deal is very ephemeral, while IBM's buying Redhat is much easier to understand (if not likely to actually restore it to stout growth).

    This is why it's notable for investors in tech dividend stocks to watch ROIC trends over time to compose confident that management is allocating capital wisely, and not merely empire building.

    Finally, they can't forget that tall R&D spending is the lifeblood of tech (you can't grow your artery to noteworthy success only on acquisitions). Microsoft's rapidly rising R&D budget and cloud-based capex gain thus far paid off, but with complicated and large corporations, there is no certitude that such investments will always foster out profitably.

    This is why FCF/share is another critical attribute metric to watch over time. While tech companies can live applauded for pouring billions into expanding their businesses, ultimately FCF/share is what funds dividends and if that doesn't grow over the long-term then I can't recommend even a speedily growing and industry-leading company.

    But again, these risks are shared by complete dividend-paying cloud companies, and at the sojourn of the day, Microsoft is far better positioned to navigate these fast-changing waters than floundering and soon to live hyper-leveraged IBM.

    Valuation: Tie

    Chart Data by YCharts

    A Big intuition so many income investors like IBM is due to its low valuation, which isn't surprising given how poorly shares gain done over the past year (or five). And with Microsoft having crushed the market over the past 12 months many understandably reckon MSFT richly priced.

    Company Forward PE 5 Year incurious PE Growth Rate Baked In

    Expected Growth Rate

    Microsoft 24.3 19.9 9.1% 12.3% IBM 10.0 10.5 1.3% 2.3% Average Tech Company 17.6 NA 5.4% NA

    (Sources: Simply Safe Dividends, F.A.S.T Graphs, Benjamin Graham)

    From a forward PE perspective that makes sense given that Microsoft is trading at a premium to both its historical forward PE and that of most tech companies. IBM is trading at a slight discount to its historical forward PE which bakes in even slower growth than analysts expect. But note that Microsoft's PE isn't actually that tall for a company that's expected to grow at low to mid-double-digits.

    And when I study at both companies via my favorite valuation tool for income stocks, dividend bow theory, then IBM too seems like the obvious valuation winner.

    (Source: Investment attribute Trends)

    DYT is what asset manager/newsletter publisher Investment attribute Trends has been exclusively using since 1966 to deliver decades of market-beating returns from blue-chip income stocks. This valuation method compares a company's bow to its historical bow because, assuming fundamental conditions (like growth rates) are similar, yields are imply reverting over time and historical yields approximate objective value.

    Company Yield 5 Year incurious Yield

    Potential Discount To objective Value

    Microsoft 1.6% 2.5% -27% IBM 4.5% 3.6% 19%

    (Sources: Simply Safe Dividends, Dividend bow Theory)

    DYT (which is what I officially consume to buy companies for my portfolios) says Microsoft is about 27% overvalued while IBM is 19% undervalued. However, I don't actually reckon Big Blue's margin of safety that tall because its impoverished attribute management team continues to underdeliver on ever weakening growth guidance.

    In other words, if IBM can't recur to consistent earnings and cash current growth then I don't await its bow to actually recur to that 3.6% incurious yield, but rather the incurious bow to soar over time to match the current bow (IBM could live a value trap).

    But how can I claim that MSFT is tied with IBM in terms of valuation when two common valuation methods warrant IBM as the divide winner? That would live using the final valuation approach I consider, Morningstar's three-stage discounted cash current model.

    Company Morningstar objective Value Estimate Discount To objective Value Upside To objective Value Long-Term Valuation Boost

    Valuation-Adjusted Total recur Potential

    Microsoft $125 10% 11% 1.1% 15.0% IBM $158 12% 13% 1.2% 8.0%

    (Source: Morningstar)

    While no DCF model can live taken as gospel (all embrace numerous growth assumptions and discount rates that are actually different for complete investors) I reckon Morningstar's objective value estimates to live the gold yardstick as far as Wall Street analysts go.

    Morningstar is slightly more bullish on both companies compared to the analyst consensus but considers both cloud companies to live roughly equally undervalued. While I'm not necessarily as bullish on IBM as Morningstar is, in this case, I'm willing to give IBM the capitalize of the doubt despite its long-term growth prospects being far less unavoidable than Microsoft's.

    But the point is that given Microsoft's vast superiority in complete other notable categories, I reckon it a decent buy at today's prices for most income investors. Personally, I reckon IBM a "hold" until I observe them actually post uniform bottom line growth and prove that Redhat isn't a costly mistake.

    If you gain more aplomb in Rometty than I do, then IBM is a decent buy BUT just compose confident to size your position appropriately in case management continues its well-established track record of overpromising and under delivering.

    Bottom Line: Microsoft Is A Far Better Cloud Computing Dividend Growth Investment right Now

    Don't salvage me wrong, I understand why high-yield income investors might pick IBM over Microsoft. After all, the relatively safe 4.5% bow is triple what Microsoft offers, and if you're retired and requisite dividend to pay the bills, stronger long-term growth is less of a concern.

    But from a fundamental and valuation perspective, I gain to quiet recommend Microsoft over IBM for most long-term investors. That's because on every notable metric that matters, including management quality, profitability, growth outlook, and even valuation, Microsoft matches or beats IBM by a wide margin.

    IBM's bullish thesis is entirely based on a low valuation and long-promised turnaround that management keeps failing to deliver, and that analysts (and I) gain basically lost aplomb in. On the other hand, Microsoft's vast cloud empire continues to grow like a weed under the expert guidance of Satya Nadella.

    When it comes to choosing lower attribute profound value over high-quality growth, I'm with Buffett on this one "it's far better to buy a wonderful company at a objective expense than a objective company at a wonderful price."

    Well, today I've shown that Microsoft is not just a wonderful company, but arguably by far undervalued. Meanwhile, IBM, a objective company at best, may not live as undervalued as the PE ratio and high-yield might initially indicate.

    The bottom line is that when it comes to cloud computing dividend growth stocks, Microsoft is a far better buy than IBM.

    Disclosure: I/we gain no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I gain no business relationship with any company whose stock is mentioned in this article.



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