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a huge focal point of the bulletins from IBM Corp.’s feel convention ultimate week worried synthetic intelligence and making it attainable throughout each and every cloud platforms. This “AI in every single place” routine 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 faultfinding 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 set 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, each and every the way 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 salvage well facts and applications following a cyberattack. “sure, each person is used to the ‘superb wall of China’ keeping you, and then of course chasing the wicked 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 eventual 12 months hold 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 large range of compute ecosystems, as Herzog wrote in a fresh weblog submit.
“You may hold NTT Cloud in Japan, you may additionally hold Alibaba in China, you can likewise hold IBM Cloud Australia, after which you may hold 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 produce sure to purchase a gape at more of SiliconANGLE’s and theCUBE’s insurance of the IBM consider experience. (* Disclosure: IBM Corp. subsidized this section of theCUBE. Neither IBM nor different sponsors hold editorial control over content on theCUBE or SiliconANGLE.)image: SiliconANGLE because you’re privilege here …
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February 25, 2019 Alex Woodie
IBM i professionals who yearn 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 original means.
Rocket application is in the procedure of certifying its Aldon Lifecyle supervisor for IBM i (LMi) application to elope on Skytap‘s public cloud providing for IBM i. Late closing yr, Skytap, which has Amazon’s Jeff Bezos as a large investor and which is additionally based mostly in Seattle fancy Amazon, unveiled plans for Skytap Cloud for IBM i, with the object to permit purchasers to spin IBM i environments up and down from the solace of a web interface.
David Romo, the director of software engineering for Rocket application, which is based on Waltham, Massachusetts, says the aggregate of Aldon LMi and Skytap’s bendy cloud environment has the talents to alternate the DevOps sustain for IBM i gurus.
“the primary utilize 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 way 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 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 discrete environments up and down as a cohesive unit. once valued clientele hold configured an environment to their liking, they could achieve it aside as a examine-handiest template that they can designation every time they like.
“that you could instantiate these templates and then you hold got a whole 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 each and every going to be operating in the era of time it takes for them to IPL.”
this will vastly diminish the friction that evolution groups invariably visage when tasked with spinning up construction and QA methods for testing 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 conclude 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 conclude that yet. they are able to’t salvage a fresh, manufacturer-new partition to conclude 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 secret sauce is the way that they seize VM photographs, the style they trap 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 hold a coalesce 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 large amounts of cash and ache on the DevOps front, Jones predicts.
“in case you suppose about how most valued clientele elope IBM i today, as a result of the capital outlay on the hardware, they’re no longer in reality in a position the set they can spin up and spin down non-production workloads at will,” he says. “they've their hardware purchase, the set they simply sort of depart everything operating. And if they’re at capability and exigency to beginning up yet another venture, well ware they going to shut down to startup this other task? Are they going to hold to fade spend tens of heaps of greenbacks on one more server and tens of heaps of bucks on licensing to salvage an entire different atmosphere up and working?”
Rocket is likewise 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 utilize BRMS to shop backups to the cloud. Skytap gained’t assist tape connectivity for backups (it makes utilize of a proprietary SSD-based storage layer), so the Cloud Connector could be captivating, Romo says.
Skytap is likewise working with two other IBM i tall availability utility providers, HelpSystems and Syncsort, to salvage their solutions licensed on its IBM i cloud before it goes GA. Its working with HelpSystems to salvage the community-based mostly (i.e. non storage-primarily based) PowerHA replication offerings operating on its cloud, whereas it’s working with Syncsort to salvage MIMIX running. There can be extra HelpSystems products licensed by the time Skytap Cloud for IBM i goes are living, which is slated to turn up before June 30.
IBM likewise has an pastime in Skytap, for a couple of reasons. First, Skytap is an IBM Cloud client, and each and every of its power programs offerings will elope in IBM Cloud datacenters. Secondly, IBM will resell the IBM i and AIX cloud choices as a solution referred to as IBM Cloud for Skytap options, or ICSS.
Thirdly, IBM has been working with Skytap to salvage a hold of a more robust licensing mannequin for running application in a public cloud environments. The particulars aren’t public yet, but Jones says the early feedback from consumers has been quite fantastic.
“We’ve been doing lots of evaluation, modeling, and engineering work to pattern out how will they try this translation between a licensing model that’s tied to the actual world, how conclude they translate that to clients who are working within the digital world,” Jones tells IT Jungle. “We’re relatively near to finalizing that. so far, the comments has been excellent, and that i believe we’ve been able to salvage it transcribed into a cloud-pleasant model. They believe they now hold that mannequin in region. They exigency to elope a few more simulations just to be sure that they don’t stop up underwater each and every month with giant IBM i licensing bills.”connected STORY
Skytap Says It’s structure a ‘genuine Cloud’ offering for IBM i
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For the past few years HPCwire and leaders of BioTeam, a research computing consultancy specializing in life sciences, hold convened to examine the state of HPC (and now AI) utilize in life sciences.
Without HPC writ large, modern life sciences research would quickly grind to a halt. It’s virtuous most life sciences research computing is less focused on tightly-coupled, low-latency processing (traditional HPC) and more subject 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 hold long been de rigueur and recently speedy networking has become faultfinding (no surprise 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 general 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. share One, presented here, examines core infrastructure issues around processor choices, heterogeneous architecture, network bottlenecks (and solutions), and storage technology. share Two, scheduled for next week, tackles the AI’s trajectory in life sciences and the increasing utilize of cloud computing in life sciences. In terms of the latter, you may be intimate with NIH’s STRIDES (Science and Technology Research Infrastructure for Discovery, Experimentation, and Sustainability) program which seeks to slit costs and ease cloud access for biomedical researchers.
HPCwire: Let’s tackle the core compute. eventual year they touched potential tower of processor diversity (AMD, Intel, Arm, Power9) and certainly AMD seems to hold near on strong. What’s your purchase 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 fancy GPUs and specialized computing devices, there’s not a lot of movement away from the mainstream processor platforms. These are people poignant 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 purchase something of huge significance to produce them shift again. In commercial biopharmaceutical and biotech there’s not a lot of enchanting stuff going on in the CPU set.
The only other thing that’s enchanting 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 share of my community (biomedical researchers in enterprise) where the users don’t even know what CPU their code is running on. That’s particularly virtuous for things fancy AWS batch, and AWS Lambda (serverless computing services) and that sort of stuff running in the cloud. I mediate I’ll stop here are remark on the commercial side they are slack and conservative and it’s still an Intel world and the cloud is hiding a lot of the virtuous CPU stuff particularly as people fade serverless.
Aaron Gardner: That’s an enchanting point. As more clouds hold adopted the Epyc CPU, some people may not realize they are running on them when they start instances. I would remark likewise that the tower of informatics as a service and workflows as a service is going to abstract things even more. It’s relatively simple today to elope most code with some even 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 fancy that.
We talked eventual 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 poignant pieces and storage tiers, but the spokes are each and every the different types of heterogeneous compute services that span and support the workload elope on that system. They definitely hold seen movement towards that model. If you gape at each and every Cray’s announcements in the eventual few months, everything from what they are doing with Shasta and Slingshot, and work towards making the CS (cluster supercomputers) and XC (tightly coupled supercomputers) work seamlessly, interoperably, in the very infrastructure, we’re seeing companies fancy Cray and others gearing up for a heterogeneous future where they are going to support multiple processor architectures and optimize for multiple processor architectures as well as accelerators, CPUs and GPUs, and hold it each and every work together in a coherent whole. That’s actually very exciting, because it’s not about betting on one particular horse or another; it’s about how well you are going to integrate across architectures, both traditional and non-traditional.
Ari Berman: Circling back to what Chris said. Life sciences historically has been sort of slack to jump in and adopt original stuff just to try it or to espy if it will be three percent faster because the differences gained in knowledge generation at this point in life science for those three percent are not ground breaking – it’s fine to wait a shrimp 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 likewise 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 elope it on one of the main system processors and it can elope on a balanced 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 odds of on the Intel system platform, some of the data offloading for poignant 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 kind of research you are doing.
HPCwire: It sounds a shrimp fancy the battle for mindshare and market share among processor vendors doesn’t matter as much in life sciences, at least at the user level. Is that fair?
Ari Berman: Well, they really fancy a lot of the future architectures. AMD is coming out with for better recollection bandwidth to maneuver things fancy PCIe links, having original interconnects between CPUs, and likewise the connection to the motherboard. One of the large bottlenecks Intel still has to solve is how conclude you salvage data to and from the machine from external sources. Internally they hold optimized the bandwidth a whole lot, but if you hold huge central sources of data from parallel file systems, you still hold to salvage it in and out of that system, and there are bottlenecks there.
Aaron Gardner: With the Rome architecture poignant forward, AMD has provided a much better approach to recollection access, poignant away from NUMA (nonuniform memory) to a central recollection controller with uniform latency across dies. This is really faultfinding when you hold up to 64 cores per socket. poignant back towards a more propitious recollection access model on a per node design even I mediate is really going to assist provide advantages to workloads in the life sciences and that is certainly something they are looking at testing and exploring over the next year.
Ari Berman: I conclude 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 produce much of a play outside of just simple HPC. The other thing I meant to bring up is a set 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 conclude 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 eventual 18 months because when you gape 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 type plays such as in the cloud where any odds in efficiency is going to be appreciated. So I mediate they hold been strategic [in choosing target markets] and we’ll espy over the next couple of years how it plays out. I mediate they are at the second not in a set where the client needs to specify a inevitable processor. They are going to espy the integrators influence here, what they choose to achieve together in their heterogeneous HPC systems portfolio, influence what CPUs people salvage and that may really effect the winners and losers over time.
ARM they espy continue to grow but not explosively and I’d remark Power is certainly interesting. Having the large Power systems at the top of the TOP500 has really validated Power9 for utilize in capability supercomputing. How those are used though versus the GPUs for target workloads is interesting. In general they may be headed to a future where the CPU is used to turn on the GPU for inevitable workloads. Nvidia would probably favor that model. It’s just very enchanting the interplay between CPU and GPU; it really does hold to conclude with whether you are accelerating a small number of codes to the nth degree or you are trying to hold more diverse application support which is where multiple CPU and GPU architectures are going to be needed.
Ari Berman: Using GPUs is still a huge thing for lots of different reasons. At the second GPUs are hyped for AI and ML, but they hold been used extensively for a lot of the simulation space, Schrodinger suite, molecular modeling, quantum chemistry, those sorts of things, and likewise down into phylogenetic inference, special inheritance, things fancy that. There are many worthy applications for realistic processors, but really I would disagree with others that it really boils down to system processors and GPUs at the second in life sciences. I did hear anecdotally from a couple of folks in the industry that were using the IBM Q cloud just to try quantum [computing], just to espy how it worked with really tall even genomic alignment and they kind of got it to work and I’ll leave it at that.
HPCwire: They probably don’t dedicate enough coverage to networking given its weight driven by huge datasets and the tower of edge computing. What’s the state of networking in life sciences?
Chris Dagdigian: In pharmaceuticals and biotech, Ethernet rules the world. The tall speed low latency interconnects are still in niche environments. When they conclude espy 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 remark networking speed is now the most faultfinding issue in my HPC world. I feel that compute and storage at petascale are largely tractable problems. poignant data at scale within an organization or outside the boundaries of your firewall to a collaborator or a cloud is the single biggest rate limiting bottleneck for HPC in pharma and biotech. Combine with that the cost tall speed Ethernet has not gone down as speedy as the cost of commoditization in storage and compute. So they are in this double whammy world where they desperately exigency speedy networks.
The corporate networking people are fairly smug about the 10 gig and 40 gig links they hold in the datacenter core whereas they exigency 100 gig networking going outside the datacenter, 100 gig going outside the building, sometimes they exigency 100 gig links to a particular lab. Honestly the way that I maneuver 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 hold 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 espy the insane data movement that they hold to conclude between the laboratory instrument and a storage system. The second thing, and I hold utterly failed at it, is articulating that there are products other than Cisco in the world. That controversy does not Fly in enterprise because there is a tremendous installed base. So I am in the trap 22 of I pay a lot of money for Cisco 40 gig and 100 gig and I just hold to live with it.
Ari Berman: I would disagree networking is one of the major challenges. Depending on what granularity you are looking at, I mediate most of the HPCwire readers will supervision a lot about interconnects on clusters. Starting there, I would remark they are seeing a fairly even distribution of simple Ethernet on the back stop because of vendors fancy Arista for instance, which is producing more affordable 100 gig low latency Ethernet that can be achieve on the back stop so you don’t hold to conclude the whole RDMA versus TCP/IP dance necessarily. But most clusters are still using InfiniBand on their back end.
In life sciences I would remark that they still espy Mellanox predominantly as the back end. I hold not seen life-science-directed organizations [use] a whole lot of Omni-Path (OPA). I hold seen it at the NSF supercomputer centers, used to worthy effect, and they fancy it a lot, but not really so much in life sciences. I’d remark 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 hold wound them. I conclude mediate the original interconnects fancy Shasta/Slingshot from Cray are paving the way 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 purchase their security enough out of the way or optimize it enough so that people can effectively utilize the cloud for data-intensive applications, that getting the data there is impossible. You can utilize the cloud but only if the data is already there. That’s a huge problem.
Internally, a lot of organizations hold moved to irritated spots of 100 gig to be able to ride data effectively between datacenters and from external data sources but a lot of 10 gig still predominates. I’d remark 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 contour factors hold shrunk.
Going back to the cluster back end. In life sciences the judgement tall performance networking on the back stop of a cluster is really faultfinding 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 each and every of the data are coming from at one point or another. You hold to salvage 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 gape at storage performance to bring data to nodes and even to ride between nodes versus message passing for parallel applications. That’s starting to shift a shrimp bit but that’s traditionally been how it is. They usually hold looked at a single tall performance fabric talking to a parallel files system. Whereas HPC as a whole has for a long time dealt with having a speedy fabric for internode communications for large scale parallel jobs and then having a storage fabric that was either brought to each and every of the nodes or effectively shunted into the other fabric using IO router nodes.
“One of the things that is very enchanting with Cray announcing Slingshot is the capacity to speak both an internal low latency HPC optimized protocol as well as Ethernet, which in the case of HPC storage removes the exigency for IO router nodes, instead allowing the HCA (host channel adapters) and switching to maneuver the load and protocol translation and each and every of that. Depending on how transparent and simple it is to implement Slingshot at the small 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 achieve 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 conclude they understand what we’ve got on disk, how conclude they carefully curate and maintain that stuff. Overwhelmingly the predominant 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 still 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 still relatively difficult to either synchronize or replicate and maintain a consistent storage namespace unless you are a really solid organization with really speedy pipes to the outside world. They still espy the problems of lots of islands of storage. The only other thing I will remark is I am known for aphorism the future of scientific data at comfort belongs in an object store, but that it’s going to purchase a long time to salvage there because they hold so many dependencies on things that anticipate to espy files and folders. I hold customers that are buying petabytes of network attached storage but at the very time they are likewise 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 likewise incredibly concerned with admin affliction and value so almost universally it is going to be a mainstream election fancy GPFSsupported by DDN or IBM. There are lots of really enchanting alternatives fancy BeeGFS but the issue really is the enterprise is nervous about fancy original technologies, not because of the fancy original technologies but because they hold to bring original people in to conclude the supervision and feeding.
Aaron Gardner: Some of the challenges with how they espy storage deployed across life science organizations is how near to the bottom hold they been driven. With traditional supercomputing, you’re trying to salvage the fastest storage you can, and the most of it, for the least amount of money. The support needed is not the primary driver. In HPC as a whole, Lustre and GPFS/Spectrum Scale are still the predominate players in terms of parallel file system. The enchanting stuff over the eventual year or so has been Lustre trading hands (from Intel to DDN). With DDN leading the charge, the ecosystem is still being kept open and I mediate carefully crafted so other vendors can provide solutions independently from DDN. They conclude espy IBM stepping up Spectrum Scale performance and Spectrum Scale 5offering a lot of generous features proven out and demonstrated on the Summit and Sierra type systems, making Spectrum Scale every bit as material as it ever was.
As far as performant parallel file systems there are enchanting alternatives. There is more presence and momentum behind BeeGFS than they hold seen in prior years. They espy some adoption and clients interested in trying and adopting it but the number deployments in production and at a large scale is still pretty limited.
These days object storage is seen more fancy a tap that you turn on and you are getting your object storage through AWS or Azure or GCP. If you are buying it for on-premise, there’s shrimp differentiation seen between object vendors. That’s the perception at least. They are seeing interest in what they summon next generation storage systems and file systems – things like WekaIO that provide NVMe over fabrics (NVMeOF) on the front stop and export their own NVMeOF indigenous file system as opposed to block storage. This removes the exigency to utilize something fancy Spectrum Scale or Lustre to provide the file system and can drain cool data to object storage either on premise or in the cloud. They conclude espy that as a viable model poignant forward.
I would add remark that speaking to NVME over fabrics in general; that it seems to be growing and becoming established as most of the original storage vendors coming on the scene are currently architecting that way. That’s generous in their book. They certainly espy performance advantages but it really matters how it’s done—it is faultfinding that the software stack driving the NVME media has been purpose built for NVME over fabrics or at least significantly redesigned. Something ground up fancy WekaIO or VAST will execute 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 espy much benefit.
Couple of other quick notes. It seems fancy 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 fancy the IO500 we’ve seen an uptick in participation, both from national labs as well as vendors and other organizations. The eventual 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 hold in the past. One of the simple ways to conclude 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 gape at what companies like Atavium is doing for primary storage or Igneous for secondary storage, providing the capacity to tag data on ingest and the capacity to ride data (policy-driven) according to tags. This is something that they hold talked about for a long time and hold helped a lot of clients tackle.”
Link to share Two (HPC in Life Sciences share 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 speedy 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 share in this large, tall margin and rapidly growing business. But unless you're Warren Buffett, you hold limited funds to invest, and most people want to maintain their portfolio to a manageable number of companies. This means income growth investors exigency to be selective with what cloud computing stocks they buy.
So let's purchase a gape at two favorite dividend cloud companies, Microsoft (MSFT) and IBM (IBM), who are some of the biggest players in cloud computing. Specifically, espy how they compare in the six most faultfinding categories dividend investors supervision 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 each and every 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 near to becoming a dividend aristocrat, while Microsoft won't achieve that status for another 16 years.
And in terms of dividend growth rates, IBM at first seems to measure up well to Microsoft, at least over the past 20 years. But note that IBM's dividend growth has been slowing down over time, while Microsoft's has remained stable (9.5% hike for 2019).
That speedy payout growth from MSFT is courtesy of a vastly superior business model and growth trajectory (more on this later). But dividend growth rates and track records are just two parts of the dividend profile, safety is by far the most important.Company Yield TTM FCF Payout Ratio
Simple Safe Dividends Safety Score (Out Of 100)Microsoft 1.6% 42% 98 (Very Safe) IBM 4.5% 49% 65 (Safe)
(Source: Simply Safe Dividends)
While IBM may 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 CostMicrosoft -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 active 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 purchase 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 share of IBM's latest efforts to turn 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 virtuous that Red Hat is a potentially smart and bold ride for IBM, according to the Harvard business Review about 80% of M&A fails to deliver long-term shareholder value. That's especially virtuous 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 expense to pay that means IBM has shrimp margin of mistake when it comes to executing on its integration and growth plans for its future hybrid cloud business (and its track record on overall execution is poor).
But the large amount of debt IBM is taking on is a certainty, and S&P has already downgraded its credit rating from A+ to A over the far more bloated balance sheet.
Moody's has achieve 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 limit 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 likewise carries its own risks. Bond yields, even for investment-grade debt, can be highly volatile, spiking during times of fiscal market scare (as occurs in corrections and stand 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 way to revert to about a 1.7 leverage ratio by the stop of 2021.Growth Profile: Winner Microsoft
Even more impressive than Microsoft's already large cloud revenue is the fact that it continues to grow that business at a breakneck pace and gain market share.
That's at the expense of IBM, who has steadily been losing market share to larger, better funded, and nimbler giants fancy 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 hold seen it revert to solid revenue growth.
That includes impressive growth in its most recent quarter of
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) extreme 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 assist customers maximize efficiency and profits.
Microsoft's one-stop shop in terms of productivity software, which is deeply integrated into Azure (as is LinkedIn now), is the main judgement Microsoft is able to achieve some of the industry's fastest growth rates while continuing to fancy 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 tall single-digit earnings and free cash current growth.
(Source: IBM investor presentation)
However, while the street may hold liked IBM's most recent results (the capitalize of very low expectations) the company still reported a 3% decline in revenue (-1% in constant currency).
(Source: Motley Fool)
And no one at all of its business segment posted impressive growth, including cognitive solutions, which is home to IBM's much-hyped Watson AI platform. The huge decline in systems was caused by the launch of the Z-mainframe rolling off its comps and shows that IBM's brief 2018 revert to positive top-line growth was not a trend reversal, but a temporary occurrence.
In fairness to IBM, SI did produce 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.
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 supposed 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 share in cloud, that slowing growth could continue, causing IBM to deliver bottom-line growth that's far below what management is guiding for over the long-term.
In fact, according to FactSet Research analysts don't mediate current management can deliver anywhere near to tall single-digit EPS growth, but just 2.3% CAGR over the next five years (with sub 2% growth through 2020). Morningstar's 6.1% earnings growth forecast is the most bullish I've seen for the company, yet likewise has the company falling far short of its guidance.
And those growth estimates now comprise Redhat, which is a very speedy 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 hold sales descend or stagnate for seven straight years.
(Source: IBM Red Hat Acquisition presentation)
IBM claims that the deal will be accretive to cash current within one year which is faultfinding since free cash current is what funds dividends and pays down debt. However, due to tall integration expenses, IBM is now guiding for a double-digit subside in FCF for 2019.
This continues a decade long trend of flat FCF/share, which explains why IBM's dividend growth has slowed over time. And given the exigency to deleverage ASAP to retain a strong credit rating and generous 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 maintain in wit that a large judgement 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 large cloud peers.
Data by YCharts
And most importantly, IBM's investments over time hold failed to deliver strong returns on investment, which brings me to the most faultfinding judgement that Microsoft is a far better investment.Business Quality: Winner Microsoft
The property of a business, including management's capital allocation skills, is the most faultfinding driver of long-term total returns. A generous proxy for business and management property is a company's profitability metrics.Company Operating Margin FCF Margin Return On Equity
Return On Invested CapitalMicrosoft 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 judgement IBM has higher returns on equity is the much more leveraged balance sheet. And while MSFT and IBM hold basically equal returns on invested capital today, the long-term trend of that management property proxy is what matters most.
IBM ROIC Over Time
(Source: Simply Safe Dividends)
Since Rometty took over in 2012, IBM's ROIC has fallen by over 50%. In fairness, it has bounced back a bit from its 2017 lows, BUT the very expensive RHT acquisition is likely to send it plummetting to fresh 10+ year lows.
In contrast, Nadella's tenure at MSFT has likewise 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 likewise quit the incredibly competitive and no margin wireless handset business that Ballmer failed to compete in. Morningstar's Dan Romanoff considers Nadella an "exemplary" CEO and I disagree wholeheartedly.
Microsoft ROIC Over Time
(Source: Simply Safe Dividends)
It should be celebrated that the LinkedIn acquisition is a large judgement 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 sentiment it harkened back to Steve Ballmer's eminent penchant for lighting shareholder money on fire by vastly overpaying resulting in huge write-downs later.
But as you can espy 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 business is now subscriber based, creating annuity-like recurring monthly revenue.
The most recent large 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 large clients fancy Exxon (XOM) to host its cloud needs. In fact, Microsoft's cloud business, which at 48% is growing more than twice as speedy as IBM's, is now hosting over 420,000 global companies and organizations. That includes 89% of the Fortune 100.
What about IBM's large investments? Well, the inequity between IBM and Microsoft's overall investment approach can be summed up fancy this. IBM mints patents, while Microsoft mints money.
Watson is a worthy sample of this, with IBM having spent billions on the AI platform over the years and hyping it to the moon via eminent appearances on Jeopardy, and Superbowl commercials touting it as "one of the most powerful tools their species has created."
Virginia Rometty has likewise 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 treat 80 percent of cancer in the world."
In fact, Rometty is eminent 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 share in Adjusted EPS in 2015. IBM missed that target by 26% ($14.90) and adjusted EPS fell to $13.8 in 2017 and 2018 and now management is guiding for "at least $13.8" in 2019 (but with 10% less FCF).
Essentially Watson has, fancy most of IBM's large 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 shrimp growth in the past quarter, despite the supposed 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 hold 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 utilize the hottest buzzwords, and file lots of patents for promising future tech, yet investors never seem to benefit.
In 2018 IBM's army of 8,500 researchers, engineers, scientists, and designers in 47 different U.S. states and 48 countries were granted a record 9,100 patents, the 26th consecutive year in which IBM received the most corporate patents in America.
Over 5,000 of those patents were in "hot" industries fancy AI, cloud, and cybersecurity. The company is likewise getting patents for quantum computing, healthcare, and blockchain. From 1993 to 2018 IBM obtained over 110,000 patents which should produce it a predominant designation in every industry in which it operates and set it up for a glorious Star Trek-like future.
Yet one of the largest collections of patents on earth hasn't stopped IBM investors from losing money during Rometty's tenure, even factoring in dividends.
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 office of generous management delivering solid growth in fundamentals fancy sales, cash flow, and dividends.
When it comes to the property 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 worthy total returns over time. Total returns are a office of three things: yield + 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 PotentialMicrosoft 1.6% 12.3% 13.9% 15.0% IBM 4.5% 2.3% 6.8% 8.0% S&P 500 1.9% 6.4% 8.3% 3% to 8.2%
(Sources: Simply Safe Dividends, Multipl.com, Morningstar, analyst estimates, Gordon Dividend Growth Model, Moneychimp)
IBM certainly offers the superior yield, nearly triple that of Microsoft. And despite overpaying for Redhat and blowing up its balance sheet, the dividend is still relatively safe. However, while Microsoft's current yield may be paltry, it's expected to grow earnings and cash current nearly six times as speedy as large 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 each and every long-term growth forecasts must be taken with a grain of salt (educated guesstimates) in this case Microsoft's strong 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 difficult to achieve given the company's ongoing struggles with its legacy hardware businesses and slowing SI sales growth.
That's not to remark that I consider IBM a "sell" necessarily. After all, that attractive dividend should allow IBM to deliver near to the market's forward total returns in the coming years, as long as management can deliver on those VERY conservative growth estimates.
But compared to Microsoft's 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 visage risks to their growth plans, and IBM and Microsoft are no different. The biggest risks investors exigency to be awake of is the cutthroat and speedy pace of change in an industry that is at the heart of disrupting so many sectors of the global economy.
Cloud is an enormous, speedy growing and tall margin industry with tech giants fancy 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 predominant industry position.
Now it's virtuous that network effects are strong in cloud, which is why the industry's top names (other than IBM) hold been steadily gaining market share. However, rising margins in cloud are largely due to stupendous economies of scale and not rising prices. For example, Amazon has slit its AWS prices 67 times over the past 12 years (yet AWS margins maintain rising).
Microsoft's strong R&D efforts might be able to maintain margins rising for several more years but eventually, they will likely peak and slack earnings and cash current growth from the cloud (at least from margin expansion).
Still, that's far superior to IBM's position which is weak and getting weaker, as seen by its declining margins in each and every segments, including SI and cloud.
The other large risk to consider is that in order to compete with several giant and well-funded rivals Microsoft is going to occasionally produce large acquisitions, as seen under Nadella with LinkedIn and Github.
While LinkedIn appears to hold been a success, it's still too early to remark whether $7.5 billion for Gitbub will prove a wise 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 faultfinding for investors in tech dividend stocks to watch ROIC trends over time to produce sure 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 way to worthy success only on acquisitions). Microsoft's rapidly rising R&D budget and cloud-based capex hold thus far paid off, but with complicated and large corporations, there is no conviction that such investments will always near out profitably.
This is why FCF/share is another faultfinding property 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 speedy growing and industry-leading company.
But again, these risks are shared by each and every dividend-paying cloud companies, and at the stop of the day, Microsoft is far better positioned to navigate these fast-changing waters than floundering and soon to be hyper-leveraged IBM.Valuation: Tie
Data by YCharts
A large judgement so many income investors fancy IBM is due to its low valuation, which isn't surprising given how poorly shares hold done over the past year (or five). And with Microsoft having crushed the market over the past 12 months many understandably consider MSFT richly priced.Company Forward PE 5 Year average PE Growth Rate Baked In
Expected Growth RateMicrosoft 24.3 19.9 9.1% 12.3% IBM 10.0 10.5 1.3% 2.3% Average Tech Company 17.6 NA 5.4% NA
(Sources: Simply Safe Dividends, F.A.S.T Graphs, Benjamin Graham)
From a forward PE perspective that makes sense given that Microsoft is trading at a premium to both its historical forward PE and that of most tech companies. IBM is trading at a slight discount to its historical forward PE which bakes in even slower growth than analysts expect. But note that Microsoft's PE isn't actually that tall for a company that's expected to grow at low to mid-double-digits.
And when I gape at both companies via my favorite valuation tool for income stocks, dividend yield theory, then IBM too seems fancy the obvious valuation winner.
(Source: Investment property Trends)
DYT is what asset manager/newsletter publisher Investment property Trends has been exclusively using since 1966 to deliver decades of market-beating returns from blue-chip income stocks. This valuation routine compares a company's yield to its historical yield because, assuming fundamental conditions (like growth rates) are similar, yields are denote reverting over time and historical yields approximate honest value.Company Yield 5 Year average Yield
Potential Discount To honest ValueMicrosoft 1.6% 2.5% -27% IBM 4.5% 3.6% 19%
(Sources: Simply Safe Dividends, Dividend Yield Theory)
DYT (which is what I officially utilize to buy companies for my portfolios) says Microsoft is about 27% overvalued while IBM is 19% undervalued. However, I don't actually consider large Blue's margin of safety that tall because its needy property 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 yield to actually revert to that 3.6% average yield, but rather the average yield to tower over time to match the current yield (IBM could be a value trap).
But how can I pretension that MSFT is tied with IBM in terms of valuation when two favorite valuation methods betray IBM as the discrete winner? That would be using the final valuation approach I consider, Morningstar's three-stage discounted cash current model.Company Morningstar honest Value Estimate Discount To honest Value Upside To honest Value Long-Term Valuation Boost
Valuation-Adjusted Total revert PotentialMicrosoft $125 10% 11% 1.1% 15.0% IBM $158 12% 13% 1.2% 8.0%
While no DCF model can be taken as gospel (all comprise numerous growth assumptions and discount rates that are actually different for each and every investors) I consider Morningstar's honest value estimates to be 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 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 capitalize 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 each and every other faultfinding categories, I consider it a decent buy at today's prices for most income investors. Personally, I consider IBM a "hold" until I espy them actually post steady bottom line growth and prove that Redhat isn't a costly mistake.
If you hold more self-confidence in Rometty than I do, then IBM is a decent buy BUT just produce sure 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 salvage me wrong, I understand why high-yield income investors might choose IBM over Microsoft. After all, the relatively safe 4.5% yield is triple what Microsoft offers, and if you're retired and exigency dividend to pay the bills, stronger long-term growth is less of a concern.
But from a fundamental and valuation perspective, I hold to still recommend Microsoft over IBM for most long-term investors. That's because on every faultfinding 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) hold basically lost self-confidence in. On the other hand, Microsoft's vast cloud empire continues to grow fancy a weed under the expert guidance of Satya Nadella.
When it comes to choosing lower property deep value over high-quality growth, I'm with Buffett on this one "it's far better to buy a wonderful company at a honest expense than a honest 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 honest 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 hold 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 hold no business relationship with any company whose stock is mentioned in this article.
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