rayo 3 by El Garza (cc) (from Flickr)

Although technically Project Lightening and Thunder represent some interesting offshoots of EMC software, hardware and system prowess,  I wonder why they would decide to go after this particular market space.

There are plenty of alternative offerings in the PCIe NAND memory card space.  Moreover, the PCIe card caching functionality, while interesting is not that hard to replicate and such software capability is not a serious barrier of entry for HP, IBM, NetApp and many, many others.  And the margins cannot be that great.

So why get into this low margin business?

I can see a couple of reasons why EMC might want to do this.

• Believing in the commoditization of storage performance.  I have had this debate with a number of analysts over the years but there remain many out there that firmly believe that storage performance will become a commodity sooner, rather than later.  By entering the PCIe NAND card IO buffer space, EMC can create a beachhead in this movement that helps them build market awareness, higher manufacturing volumes, and support expertise.  As such, when the inevitable happens and high margins for enterprise storage start to deteriorate, EMC will be able to capitalize on this hard won, operational effectiveness.
• Moving up the IO stack.  From an applications IO request to the disk device that actually services it is a long journey with multiple places to make money.  Currently, EMC has a significant share of everything that happens after the fabric switch whether it is FC,  iSCSI, NFS or CIFS.  What they don’t have is a significant share in the switch infrastructure or anywhere on the other (host side) of that interface stack.  Yes they have Avamar, Networker, Documentum, and other software that help manage, secure and protect IO activity together with other significant investments in RSA and VMware.   But these represent adjacent market spaces rather than primary IO stack endeavors.  Lightening represents a hybrid software/hardware solution that moves EMC up the IO stack to inside the server.  As such, it represents yet another opportunity to profit from all the IO going on in the data center.
• Making big data more effective.  The fact that Hadoop doesn’t really need or use high end storage has not been lost to most storage vendors.  With Lightening, EMC has a storage enhancement offering that can readily improve  Hadoop cluster processing.  Something like Lightening’s caching software could easily be tailored to enhance HDFS file access mode and thus, speed up cluster processing.  If Hadoop and big data are to be the next big consumer of storage, then speeding cluster processing will certainly help and profiting by doing this only makes sense.
• Believing that SSDs will transform storage. To many of us the age of disks is waning.  SSDs, in some form or another, will be the underlying technology for the next age of storage.  The densities, performance and energy efficiency of current NAND based SSD technology are commendable but they will only get better over time.  The capabilities brought about by such technology will certainly transform the storage industry as we know it, if they haven’t already.  But where SSD technology actually emerges is still being played out in the market place.  Many believe that when industry transitions like this happen it’s best to be engaged everywhere change is likely to happen, hoping that at least some of them will succeed. Perhaps PCIe SSD cards may not take over all server IO activity but if it does, not being there or being late will certainly hurt a company’s chances to profit from it.

There may be more reasons I missed here but these seem to be the main ones.  Of the above, I think the last one, SSD rules the next transition is most important to EMC.

They have been successful in the past during other industry transitions.  If anything they have shown similar indications with their acquisitions by buying into transitions if they don’t own them, witness Data Domain, RSA, and VMware.  So I suspect the view in EMC is that doubling down on SSDs will enable them to ride out the next storm and be in a profitable place for the next change, whatever that might be.

And following lightening, Project Thunder

Similarly, Project Thunder seems to represent EMC doubling their bet yet again on the SSDs.  Just about every month I talk to another storage startup coming out in the market providing another new take on storage using every form of SSD imaginable.

However, Project Thunder as envisioned today is not storage, but rather some form of external shared memory.  I have heard this before, in the IBM mainframe space about 15-20 years ago.  At that time shared external memory was going to handle all mainframe IO processing and the only storage left was going to be bulk archive or migration storage – a big threat to the non-IBM mainframe storage vendors at the time.

One problem then was that the shared DRAM memory of the time was way more expensive than sophisticated disk storage and the price wasn’t coming down fast enough to counteract increased demand.  The other problem was making shared memory work with all the existing mainframe applications was not easy.  IBM at least had control over the OS, HW and most of the larger applications at the time.  Yet they still struggled to make it usable and effective, probably some lesson here for EMC.

Fast forward 20 years and NAND based SSDs are the right hardware technology to make  inexpensive shared memory happen.  In addition, the road map for NAND and other SSD technologies looks poised to continue the capacity increase and price reductions necessary to compete effectively with disk in the long run.

However, the challenges then and now seem as much to do with software that makes shared external memory universally effective as with the hardware technology to implement it.  Providing a new storage tier in Linux, Windows and/or VMware is easier said than done. Most recent successes have usually been offshoots of SCSI (iSCSI, FCoE, etc).  Nevertheless, if it was good for mainframes then, it certainly good for Linux, Windows and VMware today.

And that seems to be where Thunder is heading, I think.

Comments?

Comments?

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Post tags: commoditization of storage performance, Commodity hardware, EMC, EMC Project Lightening, EMC Project Thunder, external shared memory, Linux, NAND, SSD, VMware, Windows

IBM Neuromorphic Chip (from Wired story)

What does Watson, Neuromorphic chips and race track memory have in common. They have all emerged out of IBM research labs.

I have been wondering for some time now how it is that a company known for it’s cutting edge research but lack of product breakthrough has transformed itself into an innovation machine.

There has been a sea change in the research at IBM that is behind the recent productization of tecnology.

Talking the past couple of days with various IBMers at STGs Smarter Computing Forum, I have formulate a preliminary hypothesis.

At first I heard that there was a change in the way research is reviewed for product potential. Nowadays, it almost takes a business case for research projects to be approved and funded. And the business case needs to contain a plan as to how it will eventually reach profitability for any project.

In the past it was often said that IBM invented a lot of technology but productized only a little of it. Much of their technology would emerge in other peoples products and IBM would not recieve anything for their efforts (other than some belated recognition for their research contribution).

Nowadays, its more likely that research not productized by IBM is at least licensed from them after they have patented the crucial technologies that underpin the advance. But it’s just as likely if it has something to do with IT, the project will end up as a product.

One executive at STG sees three phases to IBM research spanning the last 50 years or so.

Phase I The ivory tower:

IBM research during the Ivory Tower Era looked a lot like research universities but without the tenure of true professorships. Much of the research of this era was in materials and pure mathematics.

I suppose one example of this period was Mandlebrot and fractals. It probably had a lot of applications but little of them ended up in IBM products and mostly it advanced the theory and practice of pure mathematics/systems science.

Such research had little to do with the problems of IT or IBM’s customers. The fact that it created pretty pictures and a way of seeing nature in a different light was an advance to mankind but it didn’t have much if any of an impact to IBM’s bottom line.

Phase II Joint project teams

In IBM research’s phase II, the decision process on which research to move forward on now had people from not just IBM research but also product division people. At least now there could be a discussion across IBM’s various divisions on how the technology could enhance customer outcomes. I am certain profitability wasn’t often discussed but at least it was no longer purposefully ignored.

I suppose over time these discussions became more grounded in fact and business cases rather than just the belief in the value of the research for research sake. Technological roadmaps and projects were now looked at from how well they could impact customer outcomes and how such technology enabled new products and solutions to come to market.

Phase III Researchers and product people intermingle

The final step in IBM transformation of research involved the human element. People started moving around.

Researchers were assigned to the field and to product groups and product people were brought into the research organization. By doing this, ideas could cross fertilize, applications could be envisioned and the last finishing touches needed by new technology could be envisioned, funded and implemented. This probably led to the most productive transition of researchers into product developers.

On the flip side when researchers returned back from their multi-year product/field assignments they brought a new found appreciation of problems encountered in the real world. That combined with their in depth understanding of where technology could go helped show the path that could take research projects into new more fruitful (at least to IBM customers) arenas. This movement of people provided the final piece in grounding research in areas that could solve customer problems.

In the end, many research projects at IBM may fail but if they succeed they have the potential to make change IT as we know it.

I heard today that there were 700 to 800 projects in IBM research today if any of them have the potential we see in the products shown today like Watson in Healthcare and Neuromorphic chips, exciting times are ahead.

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Post tags: IBM Research, IBM Smarter Computing Forum, Neuromorphic chips, Project management, racetrack memory, Research management, Watson

perfection, brasilia april 2006 by seier+seier (cc) (from Flickr)

Heard a story yesterday about Smart Windows on NPR .  They were talking about new smart glass technology which uses a nano-crystal film coating to window panes that can change heat transmission characteristics of the glass.

Apparently the nano-crystal film can electronically change their orientation to reflect or transmit heat. Thus their heat transmissivity could be changed by supplying a low-voltage current to the window coating.

Problems with todays windows

The problem with todays Low-E glass windows today is that they reflect heat year round. In summer that’s great, but if it’s winter or cold and there is abundant sunlight, this stinks.  With smart windows that can change their heat transmission, one can have the best of Low-E glass and dumb windows.

Integrating current smart windows could be problematic

The story went on to discuss that ideally the smart windows would somehow be tied into a building’s heating/cooling systems used to trigger the changes to the nano-crystal coating.  Seems like a good idea for a new building construction but not so good for current housing and commercial buildings due to the retrofit requirements.

Also, the fact that a building/house is heating mode doesn’t necessarily indicate that windows should transmit heat.  The only time they should really do that is when sunlight is hitting the window pain and it’s cold out.

Ideally a building with smart glass on all four sides would have windows to the east transmit heat on winter mornings but reflect heat the rest of the day, windows to the south transmit heat most of a winter daylight times, those to the west transmit during the afternoon, and windows to the north reflect heat all the time.  But any heat transmission would only if it was a sunny day.

Smart-er window design

For the current 130.6M houses and 4.7M commercial buildings already constructed in the USA it would be better if the smart window systems were isolated and separate from a buildings other systems and somehow more self-contained/passively-managed.

This could be done by including solar photo-voltaics tied to a thermocouple/thermoelectric device in the window that would trigger heat transmission only during sunlight and its cold outside. That way we could use the solar voltaics to power the transition to heat-transmitting as well.  The smart window would even be better if it somehow could be designed to require the solar power to keep it transmitting heat.  That way as the sunlight stops shining on the window, it starts reflecting heat.

TCO of smart-er windows

While any self-contained/passively managed smart-er window might cost more up front than a dumber smart window just connected to the buildings thermostat, it would probably be cheaper when all costs are accounted for.

• With a non-self contained smart window, one needs an even smarter thermostat (driving a signal when in heating mode even though the furnace was not needed),  one has to run (low-voltage) wiring to plug into each and every smart window in a building and each window still requires some logic to transmit/transform the signal from the buildings thermostat to the window’s nano-crystal film.
• With a self-contained smart window, one would need include additional control logic, a solar photovoltaic strip/cell and a thermocouple but it wouldn’t need to plug into any other building system.

What do you think?

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Post tags: Energy efficiency, green energy, Low-e glass, Nano-crystal coatings, Smart windows

Functional Fusion? by Cain Novocaine (cc) (from Flickr)

One can only be perplexed by the seemingly overwelming adoption of server virtualization and contrast that with the ho-hum, almost underwelming adoption of storage virtualization.  Why is there this significant a difference?

I think the problem is partly due to the lack of an common understanding of storage performance utilization.

Why server virtualization succeeded

One significant driver of server virtualization is the precipitous drop in server utilization that occurred over the last decade when running single applications on a physical server.  It was nothing to see real processor utilization of less than 10% and consequently it was easy to envision that executing 5-10 applications on the single server. And what’s more each new generation of server kept getting more powerful, handling double the MIPs every 18 months or so driven by Moore’s law.

The other factor was that application workloads weren’t increasing that much. Yes new applications would come online but they seldom consumed an inordinate amount of MIPs and were often similar to what was already present. So application processing growth while not flatlining, was expanding at a relatively slow speed.

Why storage virtualization has failed

Data on the other hand continues its never ending exponential growth. Doubling every 3-5 years or less. And the fact that you have more data, almost always requires more storage hardware to support the IOPs being required to support it.

In the past the storage IOP rates was intrinsically tied to the number of disk heads available to service the load.  Although disk performance grew it wasn’t doubling every 18 months, and real per disk performance was actually going down over time, measured as the amount of IOPS per GB.

This drove proliferation of disk spindles and as such, storage subsystems in the data center. Storage virtualization couldn’t reduce the number of spindles required to support the workload.

Thus, if you look at storage performance from the perspective of % IOPS one could support per disk, most  sophisticated systems were running anywhere from 75% to 150% (based on DRAM caching).

Paradigm shift ahead

But SSDs can change this dynamic considerably.  A typical SSD can sustain 10-100K IOPs and there is some liklihood that this will increase with each generation that comes out but the application requirements will not increase as fast.  Hence, , there is a high liklihood that normal data center utilisation of SSD storage perfomance will start to drop below 50% or more, when that happens. -torage virtualization may start to make a lot more sense.

Maybe when (SSD) data storage starts moving more in line with Moore’s law, storage virtualization will become a more dominant paradigm for data center storage use.

—

Any bets on who the VMware of storage virtualization will be?

Comments?

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Post tags: performance utilization, processor utilization, storage virtualization adoption rate

Analysts walking to HCRL, notice the cleanliness of the street (c) 2011 Silverton Consulting, All Rights Reserved

We spent a couple of days last week in Tokyo and I was struck by the contrasts I saw there.

I was amazed at the extent of public transportation available from the bullet trains to the Tokyo Metro.  It’s hard to deny the advanced technology present in the Japanese rail system. I don’t think I have seen anything quite so well organized or as integrated outside of perhaps the densest cities in Europe.

For instance, in the Shinigawa station, where we were, they had multiple bullet trains, many different metro lines, and multiple express trains to nearby locations.  All located within walking distance within a single station.

I was also struck by the orderliness present within the chaos.  We weren’t necessarily taking transport at rush hour, but there was a mass of people moving throughout the station, whenever we were there.

River of people

It looked to me like a river of people going in all different directions, like currents or eddies in a stream – moving around obstacles, forking off to one track or another, with counter streams at least as busy, going in an opposite direction.  I guess I had a unique vantage point due to my height but all I could see was orderliness, constant movement and people moving with purpose and calm detachment.

No litter, anywhere

The other thing I found interesting is that there was absolutely no debris on the streets.  Masses of people moved through the streets and stations every day but the grounds and roads were spotless.  The streets were cleaner than most small cities I have ever seen.

Chicago, New York, San Francisco, and most other major American cities look like trash heaps in comparison.  I don’t know what it is about Japan, its people or culture but they obviously care about the way their city looks and try hard to keep it clean.

But office culture endures

On the other hand, Tokyo and perhaps all of Japan still remains stuck in the American office culture of the 50′s, 60′s and 70′s. As we rode the trains throughout our travels, one could see floors of cubicles, full of workers.

I suppose this is present in any major city throughout the world today, but it seems like telecommuting is not available in Japan.  Perhaps this has something to do with their compact dwellings, their culture and/or environment, which requires more face to face time between management and employee. But to my mind this seems counter productive and old world.  Note, I may be biased telecommuting from my home day after day.

Nonetheless, I was very impressed with what I saw of Tokyo and the people there.  They seem to understand how to co-exist peacefully with high population density and to efficiently move their population wherever they need to go.  America should aspire to do as well.

Comments?

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Post tags: Population density, Population dynamics, Tokyo

American War Cemetary - Remembering by tienvijftien (cc) (from Flickr)

Was talking with a friend of mine this week and he said that strategic planning has been deemphasized these last few years mainly due to the economic climate.  We have discussed this before (see Strategy, as we know it, is dead). Most companies are in a struggle to survive and had little time or resources to spend on thinking about their long term future, let alone next year.

Yes, the last few years have been tough on everyone but the lack of strategic planning is hard for me to accept.  As I look around, products are still being developed, functionality is being enhanced, technology continues to move forward.  All of these exemplify some strategic planning/thinking, albeit prior efforts from 24 to 30 months ago.

Nonetheless, development has not ceased in the interim. New features and products are still being planned for introduction over the next year or so.  Development pipelines seem as full as ever.

One could read the apparent dichotomy between deemphasizing strategic planning but continuing to roll out new products/enhancements as indicating that strategic planning has little impact on product development.  Another, more subtle interpretation is that strategic thinking goes beyond near term product improvements to something longer term, perhaps outside the 3 year window we see for current product enhancements.

In that case, then the evidence for reduced strategic planning will not show up until a couple more years have passed.  Thus, we should eventually see a slow down in new or revolutionary technology offerings.

Such a slowdown is hard to view.  Apple seems to introduce a revolutionary product every 4.5 yrs or so (iPod ’01, iPhone ’07, Ipad ’10).  Other companies probably have longer cycles.  But any evidence for a strategic planning reduction may ultimately show up as a slowdown in the rate of new/revolutionary product introductions.

Other potential indicators of decreased strategic planning include margin erosion, loss of core competencies, reduction in market value, etc.  Some of these are objective, some subjective but they all sound like a better topic for an MBA thesis than a blog post or at least my blog posts.

For example, Kodak over the last 15 years or so comes to mind as a strategic corporate catastrophe playing out.  They almost invented digital photography/imaging.  But for whatever reason they failed to react to this coming transition until it was too late.  The result is a much diminished company of today, e.g., over the last 15 years their stock price has been reduced by a factor of 12X or more.

There are probably many more examples of both business strategy failure and success but from my perspective the choices are obvious:  Ignore strategic planning for too long and your company struggles to survive or implement strategic planning today and your company may thrive.

What other examples of strategic failure and successes can you think of?

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Post tags: Apple, Kodak

Years back when I was working in corporate strategy we used to have this yearly dance called strategic planning.  Every year we would fan out to all the business units, look at what they were doing and try to figure out what they needed to be doing three to five years down the road.

This process typically lasted the better part of a quarter or so and culminated in a presentation to upper management on a direction to pursue for the business unit.  What would happen next was often the best part.  Some business groups would shelve the work and not look at it again.  Other business units would invest time and effort to incorporate the strategic plan recommendations into what they were doing that year to try to make it happen in 3 to 5 years time.  At the end of this process, annual budgets would be declared “done” and the world would go back to work.

But that was the old, dead strategy.

The “New Strategy”

The new strategy is defined by adaptability and flexibility to take advantage of any opportunity that presents itself.  This results in strategic plans and operating budgets that are updated monthly, just-in-time decision making, and wider ranging planning scenarios.  For example:

• Strategic plans and budgets updated  monthly – as the economy tanked over the last couple of years, baseline assumptions were rendered useless in no time at all.  Budgets updated yearly were no help.  Even budgets that were updated quarterly were subject to significant tracking error.  The only way to survive was to look at your budgets every month and adjust for cost of capital, inventory, and revenue mix.  This way a company could adjust their product mix immediately to best match what was selling and thus, maximize return.
• Just-in-time decision making – the WSJ used a factory closing example in their article but I prefer to look at the SSD vs HDD product mix.  When to get on the SSD bandwagon is a strategic decision.  One can examine this decision yearly quarterly or monthly to see if it makes sense today or  take the time to identify the trigger points that would make the decision for you.  For SSDs, one could decide what price SLC-NAND memory has to drop to,  say $X/GB,  when SSDs would make sense.  To make this decision, one must determine how long it would take to create and launch SSD product offerings, what SLC-NAND pricing trends look like today and back up the trigger point to take this all in account.  But, after that all one need do is monitor SSD pricing daily and when it hits your trigger point start the product changeover.
• Wider ranging scenarios – all old strategic planning used economic variables such as cost of capital, revenue growth, and cost of goods sold, many would use a range of +/- 5% on each of these factors to generate operating scenarios that were then fed into the strategic planning process.  The problem with such scenarios is that they didn’t take into account the extreme circumstances of the last couple of years.  By widening the scenarios to something like +/- 15%, they became much more useful and would have reflected actual experience.

F-15 F-16 F86 Sabre Jet Heritage Flight by TMWolf (cc) (from flickr)

But in the end most of this speaks to speed and taking advantage of opportunities that are present.

OODA

All this reminds me of Colonel John R. Boyd (USAF deceased) who came up with a new military and competitive strategic paradigm called OODA or Observation, Orientation, Decision, and Action.  Observe the competition (or market place), orient to (or appreciate what) the market is doing,  decide what the most appropriate action will be, and then do it.  John believed that the fastest OODA cycle always wins in the end.  Any OODA cycle takes time to perform, one that is fastest will change the marketplace such that by the time your (slower) adversary sees what’s happening and reacts, you have already changed the world out from under them.

There was a good book on Col. Boyd’s life by Robert Coram, Boyd: The Fighter Pilot Who Changed the Art of War. Also there was a bio, Genghis John, written by a close friend, Chuck Spinney.  If you are interested in understanding more on his views of conflict and strategy, I suggest starting at the bio but the book was an easy read.

How this all applies to the world with 6-18 month product development cycles, and 3 month marketing campaigns needs to be the subject of a future post…

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Post tags: Boyd, just-in-time decision making, monthly budget reviews, OODA, Scenario planning, Strategic plan, Strategy, wider ranging scenarios