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000-740 IBM Storage Networking Solutions Version 1

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Test Code : 000-740
Test name : IBM Storage Networking Solutions Version 1
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IBM IBM Storage Networking Solutions

Microsoft Vs. IBM: One limpid Winner | existent Questions and Pass4sure dumps

No result discovered, are attempting original 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 labor together in IBM’s multicloud manner | existent 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 total cloud platforms. This “AI in every sole place” manner 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 well-known 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 position 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, total the pass 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 original product become designed to rapidly entrap 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 infraction you,” Herzog stated. “however when they infraction 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 Have 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 ample compass of compute ecosystems, as Herzog wrote in a fresh weblog submit.

“You may Have NTT Cloud in Japan, you may additionally Have Alibaba in China, you can also Have IBM Cloud Australia, after which you may Have Amazon in Latin the us,” celebrated 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 engage a peek at more of SiliconANGLE’s and theCUBE’s insurance of the IBM deem experience. (* Disclosure: IBM Corp. subsidized this section of theCUBE. Neither IBM nor different sponsors Have 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 Have a paywall or Run banner advertising, because they wish to hold their journalism open, devoid of affect 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 — engage loads of tough work, time and money. retaining the first-rate excessive requires the hearten 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 | existent Questions and Pass4sure dumps

February 25, 2019 Alex Woodie

IBM i professionals who hunger 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 original means.

Rocket application is in the procedure of certifying its Aldon Lifecyle supervisor for IBM i (LMi) application to Run on Skytap‘s public cloud providing for IBM i. Late closing yr, Skytap, which has Amazon’s Jeff Bezos as a ample investor and which is additionally based mostly in Seattle dote Amazon, unveiled plans for Skytap Cloud for IBM i, with the intention 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 undergo for IBM i gurus.

“the primary exhaust 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 pass 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 punch 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 sever environments up and down as a cohesive unit. once valued clientele Have configured an environment to their liking, they could establish it aside as a examine-handiest template that they can name every time they like.

“that you could instantiate these templates and then you Have got a total 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 total going to live operating in the era of time it takes for them to IPL.”

this will vastly diminish the friction that progress groups invariably puss when tasked with spinning up construction and QA methods for testing original 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 original environments to log on.

“That’s some thing that they are able to finish 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 finish that yet. they are able to’t entrap a fresh, manufacturer-new partition to finish 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 surreptitious sauce is the pass that they seize VM photographs, the style they entrap 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 Have a fuse 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 ample amounts of cash and ache on the DevOps front, Jones predicts.

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

Rocket is also 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 exhaust BRMS to shop backups to the cloud. Skytap gained’t assist tape connectivity for backups (it makes exhaust of a proprietary SSD-based storage layer), so the Cloud Connector could live captivating, Romo says.

Skytap is also working with two other IBM i towering availability utility providers, HelpSystems and Syncsort, to entrap their solutions licensed on its IBM i cloud before it goes GA. Its working with HelpSystems to entrap the community-based mostly (i.e. non storage-primarily based) PowerHA replication offerings operating on its cloud, whereas it’s working with Syncsort to entrap 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 also has an pastime in Skytap, for a yoke of reasons. First, Skytap is an IBM Cloud client, and total of its power programs offerings will Run 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 entrap 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 labor to motif out how will they try this translation between a licensing model that’s tied to the actual world, how finish they translate that to clients who are working within the digital world,” Jones tells IT Jungle. “We’re relatively immediate to finalizing that. so far, the comments has been excellent, and that i believe we’ve been able to entrap it transcribed into a cloud-pleasant model. They believe they now Have that mannequin in region. They requisite to Run a few more simulations just to live confident that they don’t wait up underwater each and every month with giant IBM i licensing bills.”

connected STORY

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

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HPC in Life Sciences fragment 1: CPU Choices, soar of Data Lakes, Networking Challenges, and More | existent questions and Pass4sure dumps

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

Without HPC writ large, modern life sciences research would quickly grind to a halt. It’s proper 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 Have long been de rigueur and recently speedily networking has become well-known (no dumbfound given lab instruments’ prodigious output). Lastly, striding into this shifting environment is AI – deep 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 universal 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. fragment One, presented here, examines core infrastructure issues around processor choices, heterogeneous architecture, network bottlenecks (and solutions), and storage technology. fragment Two, scheduled for next week, tackles the AI’s trajectory in life sciences and the increasing exhaust of cloud computing in life sciences. In terms of the latter, you may live confidential with NIH’s STRIDES (Science and Technology Research Infrastructure for Discovery, Experimentation, and Sustainability) program which seeks to carve costs and ease cloud access for biomedical researchers.


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 Have near on strong. What’s your engage 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 dote GPUs and specialized computing devices, there’s not a lot of movement away from the mainstream processor platforms. These are people moving 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 engage something of huge significance to compose them shift again. In commercial biopharmaceutical and biotech there’s not a lot of consuming stuff going on in the CPU set.

The only other thing that’s consuming 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 fragment of my community (biomedical researchers in enterprise) where the users don’t even know what CPU their code is running on. That’s particularly proper for things dote AWS batch, and AWS Lambda (serverless computing services) and that sort of stuff running in the cloud. I believe I’ll halt here are grunt on the commercial side they are gradual and conservative and it’s soundless an Intel world and the cloud is hiding a lot of the proper CPU stuff particularly as people Go serverless.

Aaron Gardner: That’s an consuming point. As more clouds Have adopted the Epyc CPU, some people may not realize they are running on them when they start instances. I would grunt also 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 Run 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 dote 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 moving pieces and storage tiers, but the spokes are total the different types of heterogeneous compute services that span and back the workload Run on that system. They definitely Have seen movement towards that model. If you peek at total Cray’s announcements in the last few months, everything from what they are doing with Shasta and Slingshot, and labor towards making the CS (cluster supercomputers) and XC (tightly coupled supercomputers) labor seamlessly, interoperably, in the identical infrastructure, we’re seeing companies dote 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 Have it total labor 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 gradual to jump in and adopt original stuff just to try it or to note 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 dinky 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 also 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 Run it on one of the main system processors and it can Run on a traditional 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 odds of on the Intel system platform, some of the data offloading for moving data to and from CPUs from remote or even internally, recollection bandwidth really matters a lot, and some of those things are differentiated based on what benevolent of research you are doing.

HPCwire: It sounds a dinky dote the battle for mindshare and market participate 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 dote a lot of the future architectures. AMD is coming out with for better recollection bandwidth to wield things dote PCIe links, having original interconnects between CPUs, and also the connection to the motherboard. One of the ample bottlenecks Intel soundless has to solve is how finish you entrap data to and from the machine from external sources. Internally they Have optimized the bandwidth a total lot, but if you Have huge central sources of data from parallel file systems, you soundless Have to entrap it in and out of that system, and there are bottlenecks there.

Aaron Gardner: With the Rome architecture moving forward, AMD has provided a much better approach to recollection access, moving away from NUMA (nonuniform memory) to a central recollection controller with uniform latency across dies. This is really well-known when you Have up to 64 cores per socket. moving back towards a more favorable recollection access model on a per node design flush I believe is really going to hearten 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 finish believe 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 believe people are exploring it but I don’t know that it will compose much of a play outside of just absolute HPC. The other thing I meant to bring up is a position where I believe 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 finish 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 believe AMD has been extremely strategic over the last 18 months because when you peek 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 kind plays such as in the cloud where any odds in efficiency is going to live appreciated. So I believe they Have been strategic [in choosing target markets] and we’ll note over the next yoke of years how it plays out. I believe they are at the instant not in a position where the client needs to specify a confident processor. They are going to note the integrators influence here, what they choose to establish together in their heterogeneous HPC systems portfolio, influence what CPUs people entrap and that may really outcome the winners and losers over time.

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

Ari Berman: Using GPUs is soundless a huge thing for lots of different reasons. At the instant GPUs are hyped for AI and ML, but they Have been used extensively for a lot of the simulation space, Schrodinger suite, molecular modeling, quantum chemistry, those sorts of things, and also down into phylogenetic inference, special inheritance, things dote that. There are many powerful applications for vivid processors, but really I would coincide 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 note how it worked with really towering flush genomic alignment and they benevolent of got it to labor and I’ll leave it at that.

HPCwire: They probably don’t devote 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 towering accelerate low latency interconnects are soundless in niche environments. When they finish note 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 grunt networking accelerate is now the most captious issue in my HPC world. I feel that compute and storage at petascale are largely tractable problems. moving data at scale within an organization or outside the boundaries of your firewall to a collaborator or a cloud is the sole biggest rate limiting bottleneck for HPC in pharma and biotech. Combine with that the cost towering accelerate 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 Have 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 pass that I wield 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 Have 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 note the insane data movement that they Have to finish between the laboratory instrument and a storage system. The second thing, and I Have utterly failed at it, is articulating that there are products other than Cisco in the world. That argument does not sail in enterprise because there is a tremendous installed base. So I am in the entrap 22 of I pay a lot of money for Cisco 40 gig and 100 gig and I just Have to live with it.

Ari Berman: I would coincide networking is one of the major challenges. Depending on what granularity you are looking at, I believe most of the HPCwire readers will custody a lot about interconnects on clusters. Starting there, I would grunt they are seeing a fairly even distribution of absolute Ethernet on the back wait because of vendors dote Arista for instance, which is producing more affordable 100 gig low latency Ethernet that can live establish on the back wait so you don’t Have to finish the total RDMA versus TCP/IP dance necessarily. But most clusters are soundless using InfiniBand on their back end.

In life sciences I would grunt that they soundless note Mellanox predominantly as the back end. I Have not seen life-science-directed organizations [use] a total lot of Omni-Path (OPA). I Have seen it at the NSF supercomputer centers, used to powerful effect, and they dote it a lot, but not really so much in life sciences. I’d grunt the accelerate and diversity and the abilities of the Mellanox implementation could really outclass what is available in OPA today. I believe the delays in OPA2 Have pain them. I finish believe the original interconnects dote Shasta/Slingshot from Cray are paving the pass 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 engage their security enough out of the pass or optimize it enough so that people can effectively exhaust the cloud for data-intensive applications, that getting the data there is impossible. You can exhaust the cloud but only if the data is already there. That’s a huge problem.

Internally, a lot of organizations Have moved to irritated spots of 100 gig to live able to dash data effectively between datacenters and from external data sources but a lot of 10 gig soundless predominates. I’d grunt 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 shatter those out and so the profile factors Have shrunk.

Going back to the cluster back end. In life sciences the understanding towering performance networking on the back wait of a cluster is really well-known 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 total of the data are coming from at one point or another. You Have to entrap 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 peek at storage performance to bring data to nodes and even to dash between nodes versus message passing for parallel applications. That’s starting to shift a dinky bit but that’s traditionally been how it is. They usually Have looked at a sole towering performance fabric talking to a parallel files system. Whereas HPC as a total 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 total of the nodes or virtually shunted into the other fabric using IO router nodes.

“One of the things that is very consuming 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 wield the load and protocol translation and total of that. Depending on how transparent and light it is to implement Slingshot at the diminutive and mid-scale I believe 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 establish 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 choose from, and the actual act of storing the data is relatively straightforward. However, no one has centrally cracked the how they manage it, how finish they understand what we’ve got on disk, how finish they carefully curate and maintain that stuff. Overwhelmingly the paramount storage pattern in my world is if they are not using a parallel files system for accelerate 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 soundless 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 soundless 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 soundless note the problems of lots of islands of storage. The only other thing I will grunt is I am known for maxim the future of scientific data at repose belongs in an protest store, but that it’s going to engage a long time to entrap there because they Have so many dependencies on things that anticipate to note files and folders. I Have customers that are buying petabytes of network attached storage but at the identical time they are also buying petabytes of protest storage. In some cases they are using the protest storage natively; in other cases the protest storage is their data continuity or backup target.

In terms of file system preference, the commercial world is not only conservative but also incredibly concerned with admin tribulation and value so almost universally it is going to live a mainstream preference dote GPFSsupported by DDN or IBM. There are lots of really consuming alternatives dote BeeGFS but the issue really is the enterprise is nervous about fancy original technologies, not because of the fancy original technologies but because they Have to bring original people in to finish the custody and feeding.

Aaron Gardner: Some of the challenges with how they note storage deployed across life science organizations is how immediate to the bottom Have they been driven. With traditional supercomputing, you’re trying to entrap 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 soundless the predominate players in terms of parallel file system. The consuming stuff over the last year or so has been Lustre trading hands (from Intel to DDN). With DDN leading the charge, the ecosystem is soundless being kept open and I believe carefully crafted so other vendors can provide solutions independently from DDN. They finish note IBM stepping up Spectrum Scale performance and Spectrum Scale 5offering a lot of genuine features proven out and demonstrated on the zenith and Sierra kind systems, making Spectrum Scale every bit as material as it ever was.

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

These days protest storage is seen more dote a tap that you circle on and you are getting your protest storage through AWS or Azure or GCP. If you are buying it for on-premise, there’s dinky differentiation seen between protest vendors. That’s the perception at least. They are seeing interest in what they call next generation storage systems and file systems – things like WekaIO that provide NVMe over fabrics (NVMeOF) on the front wait and export their own NVMeOF autochthonous file system as opposed to obstruct storage. This removes the requisite to exhaust something dote Spectrum Scale or Lustre to provide the file system and can drain glacial data to protest storage either on premise or in the cloud. They finish note that as a viable model moving forward.

I would add grunt that speaking to NVME over fabrics in general; that it seems to live growing and becoming established as most of the original storage vendors coming on the scene are currently architecting that way. That’s genuine in their book. They certainly note performance advantages but it really matters how it’s done—it is well-known that the software stack driving the NVME media has been purpose built for NVME over fabrics or at least significantly redesigned. Something ground up dote WekaIO or VAST will achieve very well. On the other hand you could choose 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 note much benefit.

Couple of other quick notes. It seems dote 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 dote 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 Have in the past. One of the simple ways to finish 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 near at the problem from different angles you could peek 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 dash data (policy-driven) according to tags. This is something that they Have talked about for a long time and Have helped a lot of clients tackle.”

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

Microsoft Vs. IBM: One limpid Winner | existent 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 gradual 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 arduous 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 dumbfound that tech giants are racing to lock in market participate in this large, towering margin and rapidly growing business. But unless you're Warren Buffett, you Have limited funds to invest, and most people want to back 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 engage a peek at two Popular dividend cloud companies, Microsoft (MSFT) and IBM (IBM), who are some of the biggest players in cloud computing. Specifically, note how they compare in the six most well-known categories dividend investors custody 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 anticipate Microsoft to deliver about double IBM's total returns over the coming five years.

Dividend Profile: Winner Microsoft

Since dividend growth investing is total 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 believe it has the edge. After all, it's very immediate 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 commerce 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 proffer 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 balance 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 vigorous 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 engage 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 fragment 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 proper that Red Hat is a potentially smart and bold dash for IBM, according to the Harvard commerce Review about 80% of M&A fails to deliver long-term shareholder value. That's especially proper if a company overpays and IBM is paying a 63% premium for RHT. 10 and 30 times sales and free cash current is a flush price to pay that means IBM has dinky margin of error when it comes to executing on its integration and growth plans for its future hybrid cloud commerce (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 balance sheet.

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

    "a substantial multiply in leverage... and a departure from IBM's historical acquisition philosophy of making small, tuck-in acquisitions that circumscribe 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 live well-known even slower dividend growth in the years ahead.

    And they can't forget that doubling leverage this late in the economic cycle also carries its own risks. Bond yields, even for investment-grade debt, can live highly volatile, spiking during times of pecuniary market foreboding (as occurs in corrections and abide 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 intention to revert to about a 1.7 leverage ratio by the wait 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 commerce at a breakneck pace and gain market share.

    That's at the expense of IBM, who has steadily been losing market participate to larger, better funded, and nimbler giants dote 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 Have seen it revert 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) flagrant 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 hearten 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 understanding Microsoft is able to achieve some of the industry's fastest growth rates while continuing to luxuriate in strong 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 revert to towering single-digit earnings and free cash current growth.

    (Source: IBM investor presentation)

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

    (Source: Motley Fool)

    And nonexistent of its commerce 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 revert 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 revert it to modest top-line growth in the future. Thus far they've been unable to accomplish that and with IBM losing market participate 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 believe current management can deliver anywhere immediate to towering 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 also has the company falling far short of its guidance.

    And those growth estimates now include 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 Have sales plunge 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 well-known since free cash current is what funds dividends and pays down debt. However, due to towering integration expenses, IBM is now guiding for a double-digit dwindle 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 strong credit rating and genuine pecuniary flexibility in the future, income investors can likely anticipate 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 back in sarcasm that a ample understanding 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 Have failed to deliver strong returns on investment, which brings me to the most well-known understanding that Microsoft is a far better investment.

    Business Quality: Winner Microsoft

    The character of a business, including management's capital allocation skills, is the most well-known driver of long-term total returns. A genuine proxy for commerce and management character 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 understanding IBM has higher returns on equity is the much more leveraged balance sheet. And while MSFT and IBM Have basically equal returns on invested capital today, the long-term trend of that management character 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 dispatch it plummetting to fresh 10+ year lows.

    In contrast, Nadella's tenure at MSFT has also 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 also quit the incredibly competitive and no margin wireless handset commerce that Ballmer failed to compete in. Morningstar's Dan Romanoff considers Nadella an "exemplary" CEO and I coincide wholeheartedly.

    Microsoft ROIC Over Time

    (Source: Simply Safe Dividends)

    It should live celebrated that the LinkedIn acquisition is a ample understanding 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 feeling 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 note 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 strong growth in commercial subscribers to Office 365. In fact, 89% of Microsoft's commercial software commerce is now subscriber based, creating annuity-like recurring monthly revenue.

    The most recent ample 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 proffer ever improved services to its customers. Which is why it keeps landing ample clients dote 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 ample investments? Well, the dissimilarity between IBM and Microsoft's overall investment approach can live summed up dote this. IBM mints patents, while Microsoft mints money.

    Watson is a powerful 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 also 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 treat 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 pains she guided for $20 per participate 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, dote most of IBM's ample 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 dinky 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 Have strong 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 exhaust the hottest buzzwords, and file lots of patents for promising future tech, yet investors never appear 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 dote AI, cloud, and cybersecurity. The company is also getting patents for quantum computing, healthcare, and blockchain. From 1993 to 2018 IBM obtained over 110,000 patents which should compose it a paramount name 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 function of genuine management delivering solid growth in fundamentals dote sales, cash flow, and dividends.

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

    Total revert Potential: Winner Microsoft

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

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

    Valuation-Adjusted Total revert 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,, 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 balance sheet, the dividend is soundless relatively safe. However, while Microsoft's current relent may live paltry, it's expected to grow earnings and cash current nearly six times as speedily as ample 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 total long-term growth forecasts must live taken with a grain of salt (educated guesstimates) in this case Microsoft's strong execution on cloud makes me believe 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 grunt that I deem IBM a "sell" necessarily. After all, that attractive dividend should allow IBM to deliver immediate 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 revert potential, which is about three times that of the market and about double that of IBM, the better long-term investment from a total revert perspective is obvious.

    Risk Profile: Winner Microsoft

    All companies puss risks to their growth plans, and IBM and Microsoft are no different. The biggest risks investors requisite to live aware 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 towering margin industry with tech giants dote Amazon, Alphabet, and Alibaba investing billions each year to ameliorate their offerings and trying to hook 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 paramount industry position.

    Now it's proper that network effects are strong in cloud, which is why the industry's top names (other than IBM) Have 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 carve its AWS prices 67 times over the past 12 years (yet AWS margins back rising).

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

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

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

    While LinkedIn appears to Have been a success, it's soundless too early to grunt whether $7.5 billion for Gitbub will prove a sapient 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 strong growth).

    This is why it's well-known 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 towering R&D spending is the lifeblood of tech (you can't grow your pass to powerful success only on acquisitions). Microsoft's rapidly rising R&D budget and cloud-based capex Have thus far paid off, but with complicated and large corporations, there is no certitude that such investments will always near out profitably.

    This is why FCF/share is another captious character 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 total dividend-paying cloud companies, and at the wait 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 ample understanding so many income investors dote IBM is due to its low valuation, which isn't surprising given how poorly shares Have done over the past year (or five). And with Microsoft having crushed the market over the past 12 months many understandably deem MSFT richly priced.

    Company Forward PE 5 Year detached 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 towering for a company that's expected to grow at low to mid-double-digits.

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

    (Source: Investment character Trends)

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

    Company Yield 5 Year detached Yield

    Potential Discount To impartial Value

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

    (Sources: Simply Safe Dividends, Dividend relent Theory)

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

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

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

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

    Valuation-Adjusted Total revert 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 include numerous growth assumptions and discount rates that are actually different for total investors) I deem Morningstar's impartial value estimates to live the gold standard 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 profit of the doubt despite its long-term growth prospects being far less confident than Microsoft's.

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

    If you Have more confidence 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 entrap me wrong, I understand why high-yield income investors might choose IBM over Microsoft. After all, the relatively safe 4.5% relent 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 Have to soundless recommend Microsoft over IBM for most long-term investors. That's because on every well-known 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) Have basically lost confidence in. On the other hand, Microsoft's vast cloud empire continues to grow dote a weed under the expert guidance of Satya Nadella.

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

    Well, today I've shown that Microsoft is not just a wonderful company, but arguably by a long shot undervalued. Meanwhile, IBM, a impartial 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 Have 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 Have no commerce relationship with any company whose stock is mentioned in this article.

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