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000-740 exam Dumps Source : IBM Storage Networking Solutions Version 1
Test Code : 000-740
Test title : IBM Storage Networking Solutions Version 1
Vendor title : IBM
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IBM IBM Storage Networking Solutions
No result discovered, are attempting novel 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 ...
a huge focal point of the bulletins from IBM Corp.’s feel convention ultimate week worried synthetic intelligence and making it attainable throughout everyone cloud platforms. This “AI in every separate 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 necessary 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 be anyplace there’s AI and any dwelling 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, everyone 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 novel product become designed to rapidly accumulate 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 foul man down after they infringement you,” Herzog stated. “however when they infringement you, it will bound be first-rate if every thing had facts at leisure encryption.”
Enhancements to IBM’s storage portfolio during the terminal 12 months fill 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 titanic ambit of compute ecosystems, as Herzog wrote in a fresh weblog submit.
“You may fill NTT Cloud in Japan, you may additionally fill Alibaba in China, you can too fill IBM Cloud Australia, after which you may fill 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 certain to retract a quest 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 fill editorial control over content on theCUBE or SiliconANGLE.)
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… 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 fill a paywall or rush banner advertising, because they wish to hold their journalism open, devoid of affect or the necessity 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 aid of sponsors who're aligned with their imaginative and prescient of advert-free journalism content.
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February 25, 2019 Alex Woodie
IBM i professionals who hunger for the administrative simplicity of Amazon web functions will quickly be 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 novel means.
Rocket application is in the procedure of certifying its Aldon Lifecyle supervisor for IBM i (LMi) application to rush on Skytap‘s public cloud providing for IBM i. Late closing yr, Skytap, which has Amazon’s Jeff Bezos as a titanic investor and which is additionally based mostly in Seattle dote Amazon, unveiled plans for Skytap Cloud for IBM i, with the end to permit purchasers to spin IBM i environments up and down from the console 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 suffer for IBM i gurus.
“the primary exhaust case could be 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 complex 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 vigor 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 part environments up and down as a cohesive unit. once valued clientele fill configured an environment to their liking, they could Put it aside as a examine-handiest template that they can title every time they like.
“that you could instantiate these templates and then you fill got a gross 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 everyone going to be operating in the period of time it takes for them to IPL.”
this will vastly diminish the friction that development groups invariably pan when tasked with spinning up construction and QA methods for testing novel 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 novel environments to log on.
“That’s some thing that they are able to Do 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 Do that yet. they are able to’t accumulate a fresh, manufacturer-new partition to Do 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 furtive sauce is the pass that they seize VM photographs, the style they snare 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 fill a blend 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 titanic amounts of cash and ache on the DevOps front, Jones predicts.
“in case you suppose about how most valued clientele rush IBM i today, as a result of the capital outlay on the hardware, they’re no longer in reality in a position the dwelling they can spin up and spin down non-production workloads at will,” he says. “they've their hardware purchase, the dwelling they simply sort of depart everything operating. And if they’re at capability and necessity to genesis up yet another venture, well ware they going to shut down to startup this other task? Are they going to fill to vanish expend tens of heaps of greenbacks on one more server and tens of heaps of bucks on licensing to accumulate an entire different atmosphere up and working?”
Rocket is too 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 be captivating, Romo says.
Skytap is too working with two other IBM i tall availability utility providers, HelpSystems and Syncsort, to accumulate their solutions licensed on its IBM i cloud before it goes GA. Its working with HelpSystems to accumulate the community-based mostly (i.e. non storage-primarily based) PowerHA replication offerings operating on its cloud, whereas it’s working with Syncsort to accumulate MIMIX running. There can be 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 too has an pastime in Skytap, for a yoke of reasons. First, Skytap is an IBM Cloud client, and everyone of its power programs offerings will rush 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 accumulate 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 pattern out how will they try this translation between a licensing model that’s tied to the actual world, how Do they translate that to clients who are working within the digital world,” Jones tells IT Jungle. “We’re relatively nearby to finalizing that. so far, the comments has been excellent, and that i believe we’ve been able to accumulate it transcribed into a cloud-pleasant model. They believe they now fill that mannequin in region. They necessity to rush a few more simulations just to be certain that they don’t End up underwater each and every month with giant IBM i licensing bills.”
Skytap Says It’s structure a ‘genuine Cloud’ offering for IBM i
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No result found, try novel 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...
For the past few years HPCwire and leaders of BioTeam, a research computing consultancy specializing in life sciences, fill convened to examine the status 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 righteous most life sciences research computing is less focused on tightly-coupled, low-latency processing (traditional HPC) and more conditional 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 fill long been de rigueur and recently hasty networking has become necessary (no surprise 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 exhaust of cloud computing in life sciences. In terms of the latter, you may be confidential with NIH’s STRIDES (Science and Technology Research Infrastructure for Discovery, Experimentation, and Sustainability) program which seeks to slice costs and ease cloud access for biomedical researchers.
HPCwire: Let’s tackle the core compute. terminal year they touched potential surge of processor diversity (AMD, Intel, Arm, Power9) and certainly AMD seems to fill arrive on strong. What’s your retract on changes in core computing landscape?
Chris Dagdigian: I can be 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 pang 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 spicy stuff going on in the CPU set.
The only other thing that’s spicy 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 righteous for things dote AWS batch, and AWS Lambda (serverless computing services) and that sort of stuff running in the cloud. I mediate I’ll discontinue here are instruct on the commercial side they are slack and conservative and it’s noiseless an Intel world and the cloud is hiding a lot of the righteous CPU stuff particularly as people vanish serverless.
Aaron Gardner: That’s an spicy point. As more clouds fill adopted the Epyc CPU, some people may not realize they are running on them when they start instances. I would instruct too that the surge of informatics as a service and workflows as a service is going to abstract things even more. It’s relatively light today to rush most code with some plane 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 terminal 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 everyone the different types of heterogeneous compute services that span and back the workload rush on that system. They definitely fill seen movement towards that model. If you quest at everyone Cray’s announcements in the terminal 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 fill it everyone 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 slack to jump in and adopt novel stuff just to try it or to view if it will be three percent faster because the differences gained in lore generation at this point in life science for those three percent are not ground breaking – it’s fine to wait a minute while. Those days, however, are dwindling because of the amount of data being generated and the urgency with which it has to be processed and too the backlog of data that has to be 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 rush it on one of the main system processors and it can rush on a measure version of Linux, they are not optimizing for that; the exceptions to that are some of the built in math libraries that can be taken edge of on the Intel system platform, some of the data offloading for moving data to and from CPUs from remote or even internally, reminiscence bandwidth really matters a lot, and some of those things are differentiated based on what kindhearted of research you are doing.
HPCwire: It sounds a minute 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 reminiscence bandwidth to exploit things dote PCIe links, having novel interconnects between CPUs, and too the connection to the motherboard. One of the titanic bottlenecks Intel noiseless has to unravel is how Do you accumulate data to and from the machine from external sources. Internally they fill optimized the bandwidth a gross lot, but if you fill huge central sources of data from parallel file systems, you noiseless fill to accumulate 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 reminiscence access, moving away from NUMA (nonuniform memory) to a central reminiscence controller with uniform latency across dies. This is really necessary when you fill up to 64 cores per socket. moving back towards a more favorable reminiscence access model on a per node design plane I mediate is really going to aid 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 Do mediate 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 mediate people are exploring it but I don’t know that it will compose much of a play outside of just unadulterated HPC. The other thing I meant to bring up is a dwelling where I mediate 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 Do 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 mediate AMD has been extremely strategic over the terminal 18 months because when you quest 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 privilege away. But AMD is really geared towards the economies-of-scale ilk plays such as in the cloud where any edge in efficiency is going to be appreciated. So I mediate they fill been strategic [in choosing target markets] and we’ll view over the next yoke of years how it plays out. I mediate they are at the moment not in a dwelling where the client needs to specify a inevitable processor. They are going to view the integrators influence here, what they choose to Put together in their heterogeneous HPC systems portfolio, influence what CPUs people accumulate and that may really outcome the winners and losers over time.
ARM they view continue to grow but not explosively and I’d instruct Power is certainly interesting. Having the big 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 generic they may be headed to a future where the CPU is used to circle on the GPU for inevitable workloads. Nvidia would probably favor that model. It’s just very spicy the interplay between CPU and GPU; it really does fill to Do with whether you are accelerating a petite number of codes to the nth degree or you are trying to fill more diverse application back which is where multiple CPU and GPU architectures are going to be needed.
Ari Berman: Using GPUs is noiseless a huge thing for lots of different reasons. At the moment GPUs are hyped for AI and ML, but they fill been used extensively for a lot of the simulation space, Schrodinger suite, molecular modeling, quantum chemistry, those sorts of things, and too down into phylogenetic inference, special inheritance, things dote that. There are many noteworthy applications for realistic processors, but really I would conform with others that it really boils down to system processors and GPUs at the moment 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 view how it worked with really tall plane genomic alignment and they kindhearted of got it to labor and I’ll leave it at that.
HPCwire: They probably don’t dedicate enough coverage to networking given its importance driven by huge datasets and the surge of edge computing. What’s the status of networking in life sciences?
Chris Dagdigian: In pharmaceuticals and biotech, Ethernet rules the world. The tall speed low latency interconnects are noiseless in niche environments. When they Do view 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 instruct networking speed is now the most faultfinding 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 separate biggest rate limiting bottleneck for HPC in pharma and biotech. Combine with that the cost tall speed Ethernet has not gone down as hasty as the cost of commoditization in storage and compute. So they are in this double whammy world where they desperately necessity hasty networks.
The corporate networking people are fairly smug about the 10 gig and 40 gig links they fill in the datacenter core whereas they necessity 100 gig networking going outside the datacenter, 100 gig going outside the building, sometimes they necessity 100 gig links to a particular lab. Honestly the pass that I exploit 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 fill 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 view the insane data movement that they fill to Do between the laboratory instrument and a storage system. The second thing, and I fill utterly failed at it, is articulating that there are products other than Cisco in the world. That dispute does not glide in enterprise because there is a tremendous installed base. So I am in the snare 22 of I pay a lot of money for Cisco 40 gig and 100 gig and I just fill to live with it.
Ari Berman: I would conform networking is one of the major challenges. Depending on what granularity you are looking at, I mediate most of the HPCwire readers will reliance a lot about interconnects on clusters. Starting there, I would instruct they are seeing a fairly even distribution of unadulterated Ethernet on the back End because of vendors dote Arista for instance, which is producing more affordable 100 gig low latency Ethernet that can be Put on the back End so you don’t fill to Do the gross RDMA versus TCP/IP dance necessarily. But most clusters are noiseless using InfiniBand on their back end.
In life sciences I would instruct that they noiseless view Mellanox predominantly as the back end. I fill not seen life-science-directed organizations [use] a gross lot of Omni-Path (OPA). I fill seen it at the NSF supercomputer centers, used to noteworthy effect, and they dote it a lot, but not really so much in life sciences. I’d instruct the speed and diversity and the abilities of the Mellanox implementation could really outclass what is available in OPA today. I mediate the delays in OPA2 fill wound them. I Do mediate the novel 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 retract 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 fill moved to fiery spots of 100 gig to be able to split data effectively between datacenters and from external data sources but a lot of 10 gig noiseless predominates. I’d instruct 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 splinter those out and so the form factors fill shrunk.
Going back to the cluster back end. In life sciences the intuition tall performance networking on the back End of a cluster is really necessary isn’t necessarily for inter-process communications, it’s for storage delivery to nodes. Almost every implementation has a big parallel distributed file system where everyone of the data are coming from at one point or another. You fill to accumulate them to the CPU and that backend network needs to be optimized for that traffic.
Aaron Gardner: That’s a common case in the life sciences. They primarily quest at storage performance to bring data to nodes and even to split between nodes versus message passing for parallel applications. That’s starting to shift a minute bit but that’s traditionally been how it is. They usually fill looked at a separate tall performance fabric talking to a parallel files system. Whereas HPC as a gross has for a long time dealt with having a hasty fabric for internode communications for big scale parallel jobs and then having a storage fabric that was either brought to everyone of the nodes or virtually shunted into the other fabric using IO router nodes.
“One of the things that is very spicy with Cray announcing Slingshot is the competence to talk both an internal low latency HPC optimized protocol as well as Ethernet, which in the case of HPC storage removes the necessity for IO router nodes, instead allowing the HCA (host channel adapters) and switching to exploit the load and protocol translation and everyone of that. Depending on how transparent and light it is to implement Slingshot at the petite and mid-scale I mediate 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 Put 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 Do they understand what we’ve got on disk, how Do 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 speed 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 be seen as dinosaurs or being placed on a 3-year or 4-year upgrade cycle.
The other thing is there’s noiseless a lot of interest in hybrid storage, storage that spans the cloud and can be replicated into the cloud. The technology is there but in many cases the pipes are not. So it is noiseless relatively difficult to either synchronize or replicate and maintain a consistent storage namespace unless you are a really solid organization with really hasty pipes to the outside world. They noiseless view the problems of lots of islands of storage. The only other thing I will instruct is I am known for aphorism the future of scientific data at repose belongs in an object store, but that it’s going to retract a long time to accumulate there because they fill so many dependencies on things that anticipate to view files and folders. I fill customers that are buying petabytes of network attached storage but at the identical time they are too buying petabytes of object storage. In some cases they are using the object storage natively; in other cases the object storage is their data continuity or backup target.
In terms of file system preference, the commercial world is not only conservative but too incredibly concerned with admin tribulation and value so almost universally it is going to be a mainstream preference dote GPFSsupported by DDN or IBM. There are lots of really spicy alternatives dote BeeGFS but the issue really is the enterprise is nervous about fancy novel technologies, not because of the fancy novel technologies but because they fill to bring novel people in to Do the reliance and feeding.
Aaron Gardner: Some of the challenges with how they view storage deployed across life science organizations is how nearby to the bottom fill they been driven. With traditional supercomputing, you’re trying to accumulate 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 noiseless the predominate players in terms of parallel file system. The spicy stuff over the terminal year or so has been Lustre trading hands (from Intel to DDN). With DDN leading the charge, the ecosystem is noiseless being kept open and I mediate carefully crafted so other vendors can provide solutions independently from DDN. They Do view IBM stepping up Spectrum Scale performance and Spectrum Scale 5offering a lot of Good features proven out and demonstrated on the summit and Sierra ilk systems, making Spectrum Scale every bit as apropos as it ever was.
As far as performant parallel file systems there are spicy alternatives. There is more presence and momentum behind BeeGFS than they fill seen in prior years. They view some adoption and clients interested in trying and adopting it but the number deployments in production and at a big scale is noiseless pretty limited.
These days object storage is seen more dote a tap that you circle on and you are getting your object storage through AWS or Azure or GCP. If you are buying it for on-premise, there’s minute differentiation seen between object vendors. That’s the perception at least. They are seeing interest in what they convene next generation storage systems and file systems – things like WekaIO that provide NVMe over fabrics (NVMeOF) on the front End and export their own NVMeOF endemic file system as opposed to block storage. This removes the necessity to exhaust something dote Spectrum Scale or Lustre to provide the file system and can drain glacial data to object storage either on premise or in the cloud. They Do view that as a viable model moving forward.
I would add instruct that speaking to NVME over fabrics in general; that it seems to be growing and becoming established as most of the novel storage vendors coming on the scene are currently architecting that way. That’s Good in their book. They certainly view performance advantages but it really matters how it’s done—it is necessary 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 perform 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 view 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 terminal 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 fill in the past. One of the simple ways to Do 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 arrive at the problem from different angles you could quest at what companies like Atavium is doing for primary storage or Igneous for secondary storage, providing the competence to tag data on ingest and the competence to split data (policy-driven) according to tags. This is something that they fill talked about for a long time and fill 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)
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 slack growing companies and industry.
Cloud computing is one of the hottest growth industries privilege now and expected to remain so for the foreseeable future.
Analyst firm Gartner forecasts that from 2017 to 2021 the global cloud computing market will grow nearly 18% CAGR, or more than four times as hasty 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 surprise that tech giants are racing to lock in market participate in this large, tall margin and rapidly growing business. But unless you're Warren Buffett, you fill limited funds to invest, and most people want to withhold their portfolio to a manageable number of companies. This means income growth investors necessity to be selective with what cloud computing stocks they buy.
So let's retract a quest at two well-liked dividend cloud companies, Microsoft (MSFT) and IBM (IBM), who are some of the biggest players in cloud computing. Specifically, view how they compare in the six most necessary categories dividend investors reliance 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 everyone 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 mediate it has the edge. After all, it's very nearby 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 hasty payout growth from MSFT is courtesy of a vastly superior trade 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.
TTM FCF Payout Ratio
Simple Safe Dividends Safety Score (Out Of 100)
98 (Very 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 poise sheet.
Interest Coverage Ratio
S&P Credit Rating
Average Interest Cost
3 Or Less
8 Or More
BBB- Or Better
(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 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 righteous that Red Hat is a potentially smart and bold split for IBM, according to the Harvard trade Review about 80% of M&A fails to deliver long-term shareholder value. That's especially righteous if a company overpays and IBM is paying a 63% premium for RHT. 10 and 30 times sales and free cash stream is a rich cost to pay that means IBM has minute margin of mistake when it comes to executing on its integration and growth plans for its future hybrid cloud trade (and its track record on overall execution is poor).
But the big 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 poise sheet.
Moody's has Put IBM's credit rating on watch for a downgrade citing:
"a substantial increase in leverage... and a departure from IBM's historical acquisition philosophy of making small, tuck-in acquisitions that restrict integration risk." - Moody's (emphasis added)
IBM will effectively be 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 denote even slower dividend growth in the years ahead.
And they can't forget that doubling leverage this late in the economic cycle too carries its own risks. Bond yields, even for investment-grade debt, can be highly volatile, spiking during times of fiscal market dread (as occurs in corrections and tolerate markets).
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 blueprint to recur to about a 1.7 leverage ratio by the End of 2021.
Growth Profile: Winner Microsoft
Even more impressive than Microsoft's already big cloud revenue is the fact that it continues to grow that trade 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 fill 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 be companies that can combine data storage with advanced AI-based software and data analytics offerings that aid 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 luxuriate in sturdy 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 stream growth.
(Source: IBM investor presentation)
However, while the street may fill liked IBM's most recent results (the benefit of very low expectations) the company noiseless reported a 3% decline in revenue (-1% in constant currency).
(Source: Motley Fool)
And no one of its trade 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 be 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 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 mediate current management can deliver anywhere nearby 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 too has the company falling far short of its guidance.
And those growth estimates now comprise Redhat, which is a very hasty 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 be a welcome relief for investors who fill sales plunge or stagnate for seven straight years.
(Source: IBM Red Hat Acquisition presentation)
IBM claims that the deal will be accretive to cash stream within one year which is necessary since free cash stream is what funds dividends and pays down debt. However, due to tall integration expenses, IBM is now guiding for a double-digit lessen 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 necessity to deleverage ASAP to retain a sturdy credit rating and Good fiscal flexibility in the future, income investors can likely anticipate even slower payout growth through at least 2021 if not longer.
(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.
(Source: Simply Safe Dividends)
And withhold in mind that a titanic 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.
Data by YCharts Data by YCharts
What about IBM? Well, it too spends a lot on R&D, but far less than Microsoft, or its big cloud peers.
Data by YCharts
And most importantly, IBM's investments over time fill failed to deliver sturdy returns on investment, which brings me to the most necessary intuition 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 necessary driver of long-term total returns. A Good proxy for trade and management character is a company's profitability metrics.
Return On Equity
Return On Invested Capital
Good Company Benchmark
(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 poise sheet. And while MSFT and IBM fill 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 transmit it plummetting to fresh 10+ year lows.
In contrast, Nadella's tenure at MSFT has too turned around a long slide 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 too quit the incredibly competitive and no margin wireless handset trade that Ballmer failed to compete in. Morningstar's Dan Romanoff considers Nadella an "exemplary" CEO and I conform wholeheartedly.
Microsoft ROIC Over Time
(Source: Simply Safe Dividends)
It should be celebrated that the LinkedIn acquisition is a titanic 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 feeling it harkened back to Steve Ballmer's well-known penchant for lighting shareholder money on fire by vastly overpaying resulting in huge write-downs later.
But as you can view 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 sturdy growth in commercial subscribers to Office 365. In fact, 89% of Microsoft's commercial software trade is now subscriber based, creating annuity-like recurring monthly revenue.
The most recent titanic 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 titanic clients dote Exxon (XOM) to host its cloud needs. In fact, Microsoft's cloud business, which at 48% is growing more than twice as hasty as IBM's, is now hosting over 420,000 global companies and organizations. That includes 89% of the Fortune 100.
What about IBM's titanic investments? Well, the unlikeness between IBM and Microsoft's overall investment approach can be summed up dote 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 well-known appearances on Jeopardy, and Superbowl commercials touting it as "one of the most powerful tools their species has created."
Virginia Rometty has too spent years proclaiming that Watson was a game-changing differentiator for IBM that is "touching a billion people... and be able to address, diagnose, and deal 80 percent of cancer in the world."
In fact, Rometty is well-known for overpromising and under delivering. When she took over in 2012 and began IBM's now seven-year turnaround application 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 titanic 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 minute 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 fill sturdy 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 look 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.
Over 5,000 of those patents were in "hot" industries dote AI, cloud, and cybersecurity. The company is too getting patents for quantum computing, healthcare, and blockchain. From 1993 to 2018 IBM obtained over 110,000 patents which should compose it a preponderant title 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.
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 role of Good 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 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 role of three things: bow + long-term earnings/cash stream growth (which dividends track) + valuation change.
5 Year Expected Earnings Growth (Analyst Consensus)
Total recur Expected
Valuation-Adjusted Total recur Potential
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 poise sheet, the dividend is noiseless relatively safe. However, while Microsoft's current bow may be paltry, it's expected to grow earnings and cash stream nearly six times as hasty as titanic 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 everyone long-term growth forecasts must be taken with a grain of salt (educated guesstimates) in this case Microsoft's sturdy execution on cloud makes me mediate that 12% to 15% long-term earnings growth is a reasonable expectation. In contrast even that 2.3% consensus on IBM might be arduous to achieve given the company's ongoing struggles with its legacy hardware businesses and slowing SI sales growth.
That's not to instruct that I reckon IBM a "sell" necessarily. After all, that attractive dividend should allow IBM to deliver nearby 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 pan risks to their growth plans, and IBM and Microsoft are no different. The biggest risks investors necessity to be conscious of is the cutthroat and hasty pace of change in an industry that is at the heart of disrupting so many sectors of the global economy.
Cloud is an enormous, hasty growing and tall margin industry with tech giants dote Amazon, Alphabet, and Alibaba investing billions each year to improve their offerings and trying to steal 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 righteous that network effects are sturdy in cloud, which is why the industry's top names (other than IBM) fill been steadily gaining market share. However, rising margins in cloud are largely due to huge economies of scale and not rising prices. For example, Amazon has slice its AWS prices 67 times over the past 12 years (yet AWS margins withhold rising).
Microsoft's sturdy R&D efforts might be able to withhold margins rising for several more years but eventually, they will likely peak and slack earnings and cash stream growth from the cloud (at least from margin expansion).
Still, that's far superior to IBM's position which is fragile and getting weaker, as seen by its declining margins in everyone segments, including SI and cloud.
The other titanic risk to reckon is that in order to compete with several giant and well-funded rivals Microsoft is going to occasionally compose titanic acquisitions, as seen under Nadella with LinkedIn and Github.
While LinkedIn appears to fill been a success, it's noiseless too early to instruct 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 sturdy growth).
This is why it's necessary for investors in tech dividend stocks to watch ROIC trends over time to compose certain 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 pass to noteworthy success only on acquisitions). Microsoft's rapidly rising R&D budget and cloud-based capex fill thus far paid off, but with complex and big corporations, there is no certainty that such investments will always arrive out profitably.
This is why FCF/share is another faultfinding character metric to watch over time. While tech companies can be 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 hasty growing and industry-leading company.
But again, these risks are shared by everyone dividend-paying cloud companies, and at the End of the day, Microsoft is far better positioned to navigate these fast-changing waters than floundering and soon to be hyper-leveraged IBM.
Data by YCharts
A titanic intuition so many income investors dote IBM is due to its low valuation, which isn't surprising given how poorly shares fill 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.
5 Year average PE
Growth Rate Baked In
Expected Growth Rate
Average Tech Company
(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 quest at both companies via my favorite valuation tool for income stocks, dividend bow 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 method compares a company's bow to its historical bow because, assuming fundamental conditions (like growth rates) are similar, yields are denote reverting over time and historical yields approximate unprejudiced value.
5 Year average Yield
Potential Discount To unprejudiced Value
(Sources: Simply Safe Dividends, Dividend bow 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 reckon titanic Blue's margin of safety that tall because its impecunious character management team continues to underdeliver on ever weakening growth guidance.
In other words, if IBM can't recur to consistent earnings and cash stream growth then I don't anticipate its bow to actually recur to that 3.6% average yield, but rather the average bow to surge over time to match the current bow (IBM could be a value trap).
But how can I title that MSFT is tied with IBM in terms of valuation when two well-liked valuation methods expose IBM as the manifest winner? That would be using the final valuation approach I consider, Morningstar's three-stage discounted cash stream model.
Morningstar unprejudiced Value Estimate
Discount To unprejudiced Value
Upside To unprejudiced Value
Long-Term Valuation Boost
Valuation-Adjusted Total recur Potential
While no DCF model can be taken as gospel (all comprise numerous growth assumptions and discount rates that are actually different for everyone investors) I reckon Morningstar's unprejudiced value estimates to be the gold measure 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 be 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 benefit of the doubt despite its long-term growth prospects being far less inevitable than Microsoft's.
But the point is that given Microsoft's vast superiority in everyone other necessary categories, I reckon it a decent buy at today's prices for most income investors. Personally, I reckon IBM a "hold" until I view them actually post uniform bottom line growth and prove that Redhat isn't a costly mistake.
If you fill more self-confidence in Rometty than I do, then IBM is a decent buy BUT just compose certain 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 privilege Now
Don't accumulate me wrong, I understand why high-yield income investors might choose IBM over Microsoft. After all, the relatively safe 4.5% bow is triple what Microsoft offers, and if you're retired and necessity dividend to pay the bills, stronger long-term growth is less of a concern.
But from a fundamental and valuation perspective, I fill to noiseless recommend Microsoft over IBM for most long-term investors. That's because on every necessary 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) fill basically lost self-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 profound value over high-quality growth, I'm with Buffett on this one "it's far better to buy a wonderful company at a unprejudiced cost than a unprejudiced company at a wonderful price."
Well, today I've shown that Microsoft is not just a wonderful company, but arguably fairly undervalued. Meanwhile, IBM, a unprejudiced company at best, may not be 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 fill 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 fill no trade relationship with any company whose stock is mentioned in this article.