Iceberg of De-materialization, Horizon of Commoditization, and Theories of Cloud Universe

Earlier this month, I had the pleasure of attending to an MIT Enterprise Forum Fireside Chat by Bill Joy of Kleiner Perkins (Jason Pontin was the moderator). Among many other things, Joy spoke of a concept that he calls the "Iceberg of De-materialization." He defined this as changes in technology that undermine entire products and industries. He cited the recent example of Cisco's decision to shelve the Flip camera and postulated that the video capabilities of iPads, iPhones, and similar devices are eliminating the need for a stand alone camera.

This reminded me of a term that I have used at various points over the last decade - "Horizon of Commodization." It is perhaps a little different twist on the concept as it applies to providing services.

My Horizon of Commoditization assertion is that there is a moving line between what buyers spend time thinking about versus buying as a commodity like milk or eggs. Such commodity purchases are often decided by cost alone, with relatively little weight given to differentiating features.

In the data center business, the march to cloud services is very much like this. People want to buy compute or storage without knowing the details of how it is built and operated. This approach has a number of implications:

• public cloud is dominated by companies with tremendous economies of scale
• decisions are made on price alone with much less attention to "details" like quality of service
• customers also focus little thought on where the computing and storage actually happen and the quality of network access to those points

Some people believe that this could ultimately lead to dismantling of some aspects of the hardware and data center industries. This is, however, counterbalanced by the fact that the cloud still requires equipment, it must be housed somewhere, and data and applications are growing consistently.

The concepts of De-materialization and Commoditization have an even darker side. Does the person who uses their iphone rather than a traditional camera produce a better quality photo or video....probably not. Does the person that buys cloud without understanding design, performance, and reliability aspects serve their company well... probably not. There are still basic concepts that sit "behind the horizon" that need to be considered. As consumers we need to resist the temptation of these screens of opacity and make certain that what we are buying meets (all of) our needs.

So does this create a business opportunity for the companies providing these products and services? It has certainly worked for Apple on the product side, but how do we unlock the same treasure for a services business?

Icelandic Data Centers - from my Iceland 101 Blog

DataCenterGuru Gabe Cole

101Iceland: Rethinking Icelandic Data Center Opportunities#iceland #datacenter #cloud http://t.co/d0W1xCk

Latency and Data Center Siting

Today, there is much emphasis on the ability of cloud services to be located in mammoth data centers ideally suited to maximize low cost power and climatic or environmentally favorable cooling methodologies.

So, why don't we move everything to such facilities? There are a number of reasons:

• Companies whose system require care and feeding by a staff in a specific geographic location.
• Privacy laws that require the data be kept within certain boundaries.
• Disaster recovery and accessibility concerns.
• Physical latency which is the time that it takes to communicate with the facilities.

Today, I am going to address the issue of latency, which at its core is limited by physical laws of nature.

Latency is the amount of time, generally measured in milliseconds (ms) which represent 1/1000 of a second. It is generally expressed as "round trip latency", or the time it takes the information to make it from point a to point b and back to point a. This is in part because of the traditional tools (i.e., "ping") used to measure latency and also to simulate the effective time to make and confirm a transaction.

Round trip latency between New York and London is about 100 ms, and New York to Los Angeles is about 70 ms.

This delay is important in that it impacts the performance and business aspects of many transactions. Program trading operations, for example, want to minimize latency as much as possible and, as such, want to locate within 20 miles of the "trading" center and have latency that is below 2 ms. Many other applications perform best with latencies that are less than 20 ms, implying a distance that is less than 700 miles.

The tolerance of applications is increasing and many have become virtually latency insensitive. It is this class of applications that can easily be moved to a data center optimally located for power and cooling.

The more sophisticated IT departments now segregate their applications by latency, as well as other issues. This allows them to group what must be done at local vs remote data centers, and may include several different gradations along the way - such as one data center within 20 miles, one within 250 miles, one within 500 miles, etc.

Does the Equinix "miss" Signal the Beginning of the End?

On October 5, Equinix announced that both their third quarter and full year revenues for 2010 would be 1 to 2 percent lower than previously forecast, although their EBITDA would be higher than previously forecast. The stated reasons include (i)"underestimated churn assumptions in Equinix's forecast models in North America", (ii) "greater than expected discounting to secure longer term contract renewals," and (iii)"lower than expected revenues attributable to the Switch and Data business acquired in April 2010."

So, what does this mean for the industry?

At first cut, it appears to be primarily the result of the shortcomings of Equinix's integration of Switch and Data, but I do think that this highlights some core trends that the industry needs to be aware of:

1. Customers today consider moving a viable option - the move to virtualized environments and converged architecture make it easier for data center users to migrate to a new facility. This is amplified by the fact that many customers are currently implementing these solutions and require some type of migration - either in place or to a new facility.
2. There is an efficient marketplace - the emergence of national/international databases, reporting, and competitive placement have made it very easy for customers to understand what market rates are and to obtain competing proposals.
3. Capacity is not constrained in most markets - the facility expansions of recent years combined with improvements to many facilities mean that there is available capacity in most markets.

My takeaway is that it is finally time that the pure infrastructure companies need to start climbing the services stack. This will be the only way to maintain revenue and profit growth in the current developed markets in the US and Western Europe.

kW vs kVA in the Data Center – It really matters!

Understanding the difference between kVA and kW is critical to proper operation of a data center. The equation is simple – kW equals kVA multiplied by the power factor, but the implications can be a little more complex.

Power factor is the ratio of resistive to reactive power. In layman’s terms resistive power is burned on the spot whereas reactive power does not burn all of the power and “bounces” some back into the system. A lightbulb is an example of resistive power while an electric motor produces reactive power. Most electric systems and utility grade equipment are designed around a power factor of 80%. Most data centers, on the other hand, are almost completely resistive load and have power factors approaching unity (100%).

Since the data center power factor is high and, as such, kW is very close to kVA, some people discount the difference and use the two interchangeably. This is very dangerous and can lead to the creation of “phantom” capacity.

The fundamental limitation crops up in how much capacity critical equipment such as the generator and UPS have. Most of these systems are designed for a power factor of 80%, which means that they can only produce kW equivalent to 80% of kVA.

What does this mean. Let’s walk through a sample calculation. A data center is filled full of 120 V circuits where the customers are allowed to draw up to 16 Amps, which is equivalent to a kVA of 1.92. If we assume that this equipment has a power factor of 95%, this is equal to 1.82 kW. If we look at the other side, the 600 kVA UPS has a power factor of .8, so it produces 480 kW. So the capacity of the UPS is 480/1.82=263 circuits. If we had done “simple” division on the kVA side, we would have had a capacity of 600/1.92=312 circuits. So we actually have 49 fewer circuits than the “simple” math would have indicated, hence the reason that it is critical to convert all loads and capacities to kW!

Recently, manufacturers have begun to address this by designing systems with higher power factor ratings. A few companies are also marketing retrofit kits for existing UPS systems to increase the power factor rating.

Check back in a few weeks for the next installment – “Implications of Data Center Power Factor for the Utility Grid”.

The Significance and Challenge of Tier Ratings

The Tier Rating System, developed and implemented by The Uptime Institute (which itself is now part of The 451 Group) has been the standard measure bantered about by clients seeking data center space.

Over time it has been supplemented by broad interpretations, no doubt to the at least ocassional dismay of its developers. These interpretations have been somewhat of a necessity given the lack of flexibility written into the standard.

For example, each tier specifies a minimum height for raised floor. This leads some people to the erroneous conclusion that data centers without raised floor are somehow less reliable. This interpretation is incorrect . Raised floor allows for different design and operational implementations but neither those implementations or the raised floor itself impart more reliability. In fact, in high seismic zones just the opposite IS TRUE - slab has a higher calculated reliability than raised floor.

Calculated reliability is where we need to go as an industry. We need to thoroughly analyze design and operating standards to identify single points of failure, sources of cascading failures, maintenance considerations and a range of other concerns that determine reliability. Where appropriate, we need to back these up with detailed and vallidated calculations.

Equinix Purchase of Switch - Decline of the Massive Data Center

Three years ago, Equinix would have never seriously considered buying Switch and Data. Switch facilities were of a smaller scale, lower power density and more broadly distributed. All of these points were the converse of Equinix' stated strategic tenets at the time.

So did Switch reinvent itself or Equinix radically alter its strategy? In truth a little of both happened, but even more this is an indicator in a significant shift in market direction influenced by a number of factors.

What seemed like an insatiable drive for higher power density and ever bigger and more reliable data centers has slowed if not all together abated. Although motivated by the drive to reduce energy costs. the shift to virtual environments is also starting to significantly impact data center procurement.

The trend in developing a hardware platform for a virtual or cloud implementation is to seek the optimum price point for hardware, which often means stopping well short of top of the line high density blades. Architecture is also advancing such that many clients are achieving distributed and self healing computing environments. Even though we have seen some celebrated "cloud failures" there is an increasing number of customers seeking lower physical infrastructure reliability, and price points.

I haven't even touched on potential shrinking footprints with full-scale virtualization, but let's just suffice to say that Equinix apparently views it wiser to invest more in broadening their foot print and product line and (perhaps) less in building new mega data centers.