The thought to write about what “best” means in technology came to me after reading Joe Weinman’s book “Cloudonomics”. In the book he points out several times that having the best technology doesn’t guarantee that you’ll end up with the best solution or service. So how do you determine what’s best?

Some definitions of “best” in IT include:

• Most comprehensive solution
• Lowest priced solution
• Easiest solution to install and get up and running
• Best performing in high latency situations
• Doesn’t require capital
• Doesn’t lock me in
• Highest price

I’m guessing that after having read the seven bullets above, you’re already starting to get a sense of how we sometimes make assumptions about the appropriateness of an IT solution based on incomplete considerations. It seems self-evident what best should mean, but it’s often true that we don’t recognize how priorities can contradict or shift our definitions.

Buying the best

When you buy the best solution in any product category you assume that you are in fact getting the most appropriate solution for the money. That value might be any combination of things from a name (such as Hermes,) to performance or sex appeal (like Ferrari,) or maybe time per transaction (I won’t wait in line at Whole Foods markets).

The reality is that best could mean all of those things or none of them. While it’s almost certain that a bag you buy from Hermes is going to be well made, is it 30 times better than another brand? Is a $1,000 bottle of wine 20 times better than a $50 bottle? If money is no object to you, then the answer is more likely to be yes, a $1,000 bottle is better. On the other hand, if you value the ability to have different bags for different events, or simply prefer the ability to buy a new bag more often, then the $150 bag is probably “best” compared to the Hermes bag.

Buying IT is no different, except that it’s immensely more complex. In IT there are myriad variables that affect the ability to get the most from any solution. These variables include price, features, latency, maintenance, flexibility, open vs. proprietary, required training, user interface, APIs, and more. What about your team’s ability to sell the solution as the right choice to your customers? How about whether or not you’ve got the correct organizational and financial structure to support the solution appropriately?

How to determine what’s best

The decision process for every new technology or solution selection needs to cover a wide list of criteria. These criteria will mostly all be the same for each business but the priorities will change depending on your organization.

The majority of the standard selection assumptions (need, ROI, cost, etc) are well understood, but even among those “standards” there is room for better decision making and prioritization. I like to include the following non-standard criteria when my team is making a solution selection.

• How much value do we get out of the solution at 80 percent of total feature set?
• What other capabilities does this solution open the door to in the future?
• How many of my customers need to use the solution and to what extent before it adds new value?
• What organizational support (business and IT) do I have for the long term “ownership” needs (staff, training, champions, budget, lifecycle, etc.)?
• How does this solution position my team to execute against larger IT and business visions?
• Does this solution leverage other partners and technologies already in use?
• What’s the time to install vs. cost to purchase or time to benefit? (In other words, will I get 30 percent net new benefit value in year one vs. nothing in year one and two, but 80 percent in year three from another solution?)
• Ownership risk assumptions (what assumptions are you making at the front end of any solution selection and are those assumptions still accurate? With modern cloud/SaaS etc., you might not have the ownership risk you “enjoyed” with many legacy platforms)

While I could easily argue that all of the above bullet points are important to every organization, they must each be measured against the organization’s situation at the time. Are you low on cash, but growing fast, do you have a higher risk profile or regulatory concern? The process of prioritization can only be done by the business making the purchase.

Seems like an oxymoron

Sometimes the best purchase is the purchase you avoid, other times the best purchase is the one you didn’t make. IT is littered with examples of purchases that would have been better left undone. However, just as common are those purchases that were never made because they weren’t “perfect”. When you’re looking for perfect, keep in mind that there’s no such thing in software and many cases in hardware, but if you can solve a problem even at 70 or 80 percent, the purchase might still be better than waiting for the “perfect” option.

The test and fail option is much more real today than it ever has been and it’s a good thing. Now you can test, fail, and retry three or four times all for less effort and cost than making one selection in the past. So, step forward boldly, but don’t forget that when you are thinking “best” make sure you’ve really developed a case for what best means to your organization.

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There is ample evidence commoditization is occurring, and we could point to almost any area of IT to see it, from servers, PCs, virtualization, storage, networking, and so on. However, what is often lost in the obvious is that it’s not that simple.

IT commoditization vs cars

It’s true that with a modern server and chip combination you could likely solve almost any specific workload demand of a modern application. The inherent risk though is that there’s always someone out there looking to make a better rat trap, and the market continues to show that there is real demand for differentiation – consider the viability of both ARM and Intel chips for use with different job types.

For instance, in the case of Intel you could easily brute force the same workload that an ARM chip could handle, but processor by processor you would likely be very inefficient from a utilization and power consumption perspective. The same is true for ARM chips being used where a larger Intel processor might be more effective. While the aforementioned example is a simple one, it applies across most layers of infrastructure: storage, network, I/O, virtualization, and so on.

To make an analogy: Cars have been around for over 100 years now, they must be commodity by now, right? They all (mostly) have four wheels, two or more doors, a combustion engine (mostly) and generally get you from point A to point B successfully.  Are cars a commodity compared to each hand-built car of the late 1800s and early 1900s? Maybe. But only in the sense that we can each buy a Ford Focus with the exact same feature set as another Ford Focus.

You can also buy a Ferrari, which is excellent for country highways and tight corners, or you can pick a Dodge minivan, which is better at hauling the soccer kids around. Each of these two cars have substantially different features and solve different problems, yet they are both cars. So, the simple answer is no, they are not commodity if by commodity you mean there is little or no profit or differentiation to be found.

Drivers that make unique IT solutions critical

CPU Performance – There are some tasks that will need the fastest possible processors. The benefit comes from the time reduction associated with running a workload. The time is so valuable that the cost of the infrastructure and power is immaterial. In many cases this type of environment is refreshed 18-month cycles, but sometimes as few as every six months.

Network Bandwidth – Critical if the data being manipulated or distributed is being moved outside the confines of where the compute resides, or needs to be moved fairly quickly in very large amounts.

Network Performance – In terms of not just bandwidth but also latency. In some cases customer demands are on the level of differences of nanoseconds.

Storage Scale vs. I/O – Similar to networking, the type of storage you need is dependent on the type of work being done. You don’t solve an I/O requirement by just buying bigger arrays with more and larger SATA disks. You also don’t put large cache or expensive memory on storage that is mainly used for archival or lower performance requirements, such as for photos.

These only scratch the surface of the variables associated with building an infrastructure environment, but clearly it would be difficult to create a small handful of solutions or solution providers to take care of every IT workload demand. To the contrary, in my work I regularly see a significant number of players enter the market that either fill an unmet need from an industry perspective or enable new types of performance and pricing models.

Why commodity IT is a bad idea

Not only do I think we’re many years away from having a small handful of service providers deliver us compute on demand, I propose that more importantly, we should all hope that the day never comes anyway. I am against the idea of a utility form of compute delivered to everyone much the same way for many reasons, but the two that I think are the most critical are monopolies and innovation.

Cloud monopolies would be bad

The arguments against service providers acting under the pretext of a public utility are legion: inefficiency, waste, corruption, etc.  (For more detail, refer to the eye-opening book “The Fine Print” by David Cay Johnston.) Considering the importance of compute to the global economy, the last thing we should ever want then is for it to become a monopoly. If we allow a few companies to push the technology to a true commodity business model, then we could count on real competition for service delivery to disappear, as there wouldn’t be an easy way for the little guy or regional player to participate in the market. And it’s the ability for little guys to introduce innovation that sparks competition and evolution.

If Cloud were to become a monopoly service, we would quickly find ourselves suffering the same issues with many other public utilities:  running on older equipment, getting charged for non-existant services or things we don’t understand, and having no one accountable to address complaints.

Innovation would be stifled

Beyond that, Innovation in any market only occurs through necessity. Without real competition, the commodity cloud services would begin to act like so many of the early infrastructure outsource providers did and only deliver to the lowest common denominator. They would make changes more slowly and as customers we would be forced to plan our businesses around what providers were willing to do. IT will be its most successful when the business customer doesn’t have to consider the “limitations” before advancing strategic opportunities.

While there’s little doubt that several big players would come to dominate the market as is already the case today, we cannot afford to be without all those spunky new companies looking to carve out a market for themselves. These little players will force the larger players to stay honest, to bill correctly, to offer new services, and to continually innovate.

The Good News

I don’t really think we have anything to worry about, because as I’ve already indicated I don’t believe we are at any near-term risk of getting to a utility-type delivery of compute resources market. There are just too many ways to (in this case) build that car. So rest easy: We’re going to continue to see lots of great innovation in the infrastructure and application services and delivery space for some time to come, but keep your eyes and ears open all the same.

Mark Thiele is executive VP of Data Center Tech at Switch, the operator of the SuperNAP data center in Las Vegas. Thiele blogs at SwitchScribe and at Data Center Pulse, where he is also president and founder. He can be found on Twitter at @mthiele10.

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You may not get the budget or buy-in to create a real business continuity plan, but if you can’t get one, then a communication plan might just be the best return on investment for the time and cost.

It seems simple, but communications is the single most critical capability post disaster. If your customers don’t hear from you, they assume you’re either out of business, or at a minimum unlikely to keep near term commitments. As anyone calling a customer support center will tell you, the black hole of “not knowing” is worse than being told, “it might be another day.” With a timeline the customer can react and plan, without it, she is at the whim of her vendor, which is now making her look bad with her customers.

Setting up the plan

Lobby at Verizon office at 140 West Street, New York post-Sandy

• Have a phone line with regularly updated information for all employees, with a tree for updates, or information that might be critical to sub groups.
• Create a website that is used only for updates.Be sure to host your recovery site with a hoster who is out of your area.
• Get a conference line(s) that are available for teams to jump on whenever they need to discuss specific activities with other members of the recovery team.
• Provide a location for meetings with at least two backup alternatives in case the primary isn’t an option. This could be someone’s home, some rental space or a conference room at a local hotel.
• Distribute pagers and or satellite phones for a few key staff. This can be especially important if the cell systems have been impacted by the disaster.

The tools of the plan

Email: Create a mirror of your email environment with a third party (if you haven’t already outsourced it to Google or Microsoft, etc.). This mirror doesn’t have to have all the data, it just has to have key names, addresses, and distribution lists. Your email should appear to be coming from the same domain as your primary email, and it should have the following:

• Mirror email accounts for a team of leaders and functional team members that are tasked with responding after a disaster;
• Addresses for all your customer contacts;
• Addresses for your key suppliers; and
• Distribution lists for customers and employees.

It really isn’t hard to make the above happen. Your email admin can find a third-party provider and setup a mirror but inactive environment with regular synchronization of the required information. This mirror environment allows you at low cost to have a “known and trusted” communications tool up and active the minute your primary systems are down.

Phones: Like the email solution, you should have a backup voice service such as Centrex. This voice service will have all the same contact information that your email solution should have, plus more depending on special contact details for recovery teams and key suppliers, etc.

Social media: If you’ve been reading the news lately, you‘ve seen or heard information on the importance of your CEO participating in social media (Twitter, Google+, Facebook, Quora, etc). A website with blogs and or a dashboard with updates can also be very useful. After a disaster your ability to communicate updates and answer questions in real time from customers, analysts, partners etc. is a huge benefit. The more information you make available the more comfortable your community will be and the more patience they will show you during the recovery period.

Justifying the communications efforts

During the disaster and the recovery these efforts will let you tell the customer know what’s going on. You can provide comfort to concerned families, partners and employees. Simple messages indicating what you’re doing, what your update schedule will be and how company representatives can be reached are all key objectives of the communications effort.

Of course, each communication tool has its advantages and disadvantages. I don’t recommend social media as the primary communication solution in lieu of email and phones. You still need the ability to provide targeted information to your customers and partners that would go way beyond the hit and miss capabilities of social media. Each of the tools listed above have capabilities that make them more suited for certain types of communication requirements.

In the case of social media the updates are really general and meant to satisfy the casual observer, while also updating those who do follow your tweets, LinkedIn updates, and Facebook posts closely. However, you shouldn’t consider it a substitute for direct communication with customers/partners via phone or email.

While these efforts aren’t an alternative to a real business continuity effort, like a weight loss plan or cleaning out the garage, taking small but measurable steps is often the key to making “something” happen. Each of the objectives listed above are relatively inexpensive and very easy to explain or justify to your leadership. At a minimum it will demonstrate that you’re taking the lead on “doing something” rather than ignoring the issue and blaming corporate inertia. You’ll certainly be doing your company a huge favor by ensuring that they don’t appear to disappear from the face of the earth when a disaster occurs.

Mark Thiele is executive VP of Data Center Tech at Switch, the operator of the SuperNAP data center in Las Vegas. Thiele blogs at SwitchScribe and at Data Center Pulse, where is also president and founder. .He can be found on Twitter at @mthiele10.

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Customers have come to understand the potential of having an agile IT environment, but by and large most of them don’t fully understand what that means for their current IT model or organization and legacy environments. I fear that we are heading to a point in the next 12 months where we will see a strong customer backlash in the form of brake lights or return to sender notes.

If your solution can stand the light of day, then you shouldn’t have any trouble helping your potential customers better understand what the adoption of said technology, when done correctly, might mean. You must be willing to make it clear that buying an engine, even a really good one, isn’t buying a car. If we continue to sell engines to mechanics, we must give them the knowledge to build the car. We at least need to help them understand that the engine alone isn’t enough. They need the rest of the car.

Here be dragons

There are several challenges I see developing in this marketplace that will help fuel the backlash such as:

• Too many vendors who are all trying to gain a foothold before the money runs out or the customer gets wiser, whichever comes first
• Vendors and service providers that really don’t understand corporate IT and can’t explain in strategic terms how cloud will and should affect the IT group and enable the business at large

There is more to building an agile or fluid IT environment that just creating faster provisioning and or reducing your capex spend and replacing much of it with operational expenditures

• Confusing messages about what is or isn’t a cloud
• Large, big box players are attempting to demonstrate their relevance in the new cloudier markets
• A clear understanding of the links between agile infrastructure and process or organizational change requirements is missing

The challenges here among others lead to a lack of understanding among buyers who then either don’t buy or buy without thinking through the downstream impacts or roadblocks to realizing real benefits.

Help your customer to help yourself

So how to avoid the backlash? Remember that you aren’t selling disk, CPU, or a piece of software anymore. You’re selling a strategic opportunity to your customers and you need to staff up accordingly. Your team needs experience with organizational design and a greater understanding of what business trigger is better advanced by an agile IT environment.

You also need to incent the sales team correctly. Most sales organizations don’t emphasize a long-term strategic customer focus, but rather the effort is on “how much can I sell in the shortest sales cycle or by quarter end”. This tactic for sales might work in the short term, but won’t make you any long-term friends.

Create sales and consulting strategies that take into account the “two ITs” that will continue to exist for the next 7-10 years. A sale to a startup or small business will be very different from a sale to a large established business or an enterprise. The small business doesn’t have the legacy process, infrastructure, and staffing, so their ability to quickly adopt and realize the benefit of agile IT is more obvious. With an enterprise the wrong adoption process will get the CIO fired and could put the business at risk. Doing things more quickly is great, but only if you have the people and process to guarantee that the ‘”correct” things are happening quickly.

Finally, look for the right partners and don’t try to be everything to all people. While most would agree that Amazon has the most feature-rich cloud solution, it offers little if anything in the form of support for how your organization should adopt and integrate agile IT. Other IT team incentives and strategies for making the agile IT change in your organization can be found here.

We read it in every guide for sales and business relationships, “the supplier needs to act as a partner”. If you’re acting as a partner to your agile IT buyer, then you should participate in preparing them to be successful. In no part of the IT market is this any more important than in the cloud space.

Customers must act too.

And customers, I’m not letting you off the hook either. Stop looking at cloud as the “why” and start looking at how an agile IT environment will allow you to deliver greater business value to your customer “whys”. Engage your service provider partner in discussions at the correct levels of leadership (on both sides). Identify third parties that can add value to the mix. In other words, don’t be afraid to ask for help.

This isn’t just a new set of hardware, it’s a change in mindset about how IT serves the business. If we want people to buy into that, we have to educate them, support them and tell them the truth. Then maybe we can avoid this trough of disillusionment.

Mark Thiele is executive VP of Data Center Tech at Switch, the operator of the SuperNAP data center in Las Vegas. Thiele blogs at SwitchScribe and at Data Center Pulse, where is also president and founder. He can be found on Twitter at @mthiele10.

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Charles Dickens (who may be rolling in his grave) was right. When it comes to the debate on public versus private clouds or commodity versus legacy IT, there seems to be no room for nuance. So, while cloud and commodity IT are the way of the future, private Cloud and legacy IT are here to stay.

Underlying IT strategy considerations (What’s good for you)

Cloud computing is supposed to save us money, and most would argue that it can. Cloud computing is also supposed to provide agility and flexibility in how you deploy and manage your IT solutions, enabling improved business capabilities. The problem is that depending on what you’re doing and when you’re doing it, saving money could be the only reason for adopting or not a reason at all.

If savings was the motivation for moving services to the cloud I might argue that depending on the depth and breadth of adoption you could be using the wrong decision drivers. In other words, how often are major shifts in IT done with savings in IT as the “why”? Savings is the outcome of the “why.”

Personally, I always look for ways to make IT more cost effective and efficient, but not at the expense of real progress. If you’re spending your time focused on cost savings and efficiency as the why then you’re likely missing greater opportunities for adding business value. As I’ve said before, you must get away from thinking of IT as a tool to use to reduce the cost of IT.

How to know if the public cloud is your best bet.

• Limited exposure to heavy infrastructure investments like mainframes and enterprise applications
• IT staff are more likely to have been brought up in the days of rapid development, virtualization automation and services on demand
• More accepting of risk to availability or supportability of your environments (more open to “open source”)
• In a smaller business there tends to be greater flexibility and agility in decision making
• Enterprises that have new application requirements should look at all options (SaaS, Public Cloud, Private Cloud, etc.). Time to market, skills and costs should be the deciding factor, not dogma.
• The above characteristics lend themselves to allowing a company to go whole hog into a new IT strategy and to accept risks where more established enterprises can’t or won’t. Generally smaller companies and younger companies will take this risk.
• The staff is much less likely to feel emotional attachment to a SAN or to working on servers and are therefore less likely to feel threatened by looking to an external provider.

So who wants to stick with private cloud?

• Companies with a decade plus of investment in IT staff, infrastructure and enterprise applications
• Those in industries where regulatory and financial controls are stricter, more comprehensive and carry greater risk when failure occurs
• CIOs working at places where business change takes much longer and acceptance for risk to the status quo is much lower
• Places that have dedicated staffing for very specific roles, which makes it harder to unify quickly around a major change to infrastructure or applications
• Businesses with a much larger infrastructure base, allowing for deeper staff knowledge and improved economies of scale

The characteristics of a large enterprise mean that many investments in IT have consequences that are measured in the $100s of millions. Any short term investment in hardware or private cloud solutions is immaterial to the greater opportunity for the company. This doesn’t mean that a large enterprise can’t or shouldn’t look to use public cloud where it makes sense, but it does mean that they don’t have to in order to be competitive. In the end, very few companies will ever fail because their infrastructure cost area little higher. However, they could fail if their infrastructure doesn’t protect the business or respond appropriately to need.

Your mileage may vary

Enterprises can’t and won’t just dump expensive and critical legacy environments so they can move something to public or private cloud. Smaller businesses can now adopt technologies, applications and distributed infrastructure in ways that were formerly only available to much larger organizations. We will have a noisy cloud technology market for some time to come and the split of cloud computing models means that there will be room for everyone.

So depending on where you sit the market could look great or scary. It could look like it’s not really changing for the better, or it could look like it’s moving too fast. However, the fact is that change to a cloud operating model is happening and competition will be the deciding factor. Companies will adopt those strategies that offer them the best combination of agility, and cost, while appropriately addressing their level of risk tolerance.

Mark Thiele is executive VP of Data Center Tech at Switch, the operator of the SuperNAP data center in Las Vegas. Thiele blogs at SwitchScribe and at Data Center Pulse, where is also president and founder. He can be found on Twitter at @mthiele10.

Feature photo courtesy of  Flickr user piermario; Server photo courtesy of Flickr user Paul Hammond; Odometer photo courtesy of Flickr user  quasireversible.

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Better tools for big data.

So, if it’s safe to assume that big data is real, and that you should be investing, where do you start and what should you expect as you go through the adoption process? Big data today, is what the web was in 1993. We knew the web was something and that it might get big, but few of us really understood what “big” meant. Today, I believe we aren’t even scratching the surface of the big data opportunity.

A good example of potential big data use models can be found here.

Current issues with adoption.

There are a number of issues that will affect your ability to successfully adopt and make best use of a big data solution, but the three I believe are most critical are:

1. Useable enterprise tools — The tools that will allow any business to fully utilize big data aren’t ready.
2. Lack of staff expertise — The availability of data scientists or folks with a similar background is limited at best.
3. Data gravity — As Dave McCory pointed out in his post on data gravity, where data is created/sent is where it ends up being used. The applications and people need to come to the data as I explained.

How will these adoption issues affect big data as a business opportunity?

Useable enterprise tools — The current suite of products include Greenplum, Cloudera’s Hadoop and others, which are making headway in many large enterprises. However, these tools are still new and generally require large technical teams trying to solve issues for companies like eBay and Sears. A smaller company would be less likely to gain the appropriate return on investment, because of the high complexity of implementation combined with low overall volume.

Lack of staff expertise — This area is similar to enterprise tools. Even if you’ve got 10 people working on the refinement of the system, it’s likely going to boil down to that one wizard/expert who can work magic with your data. Putting a large number of people on the problem won’t guarantee success.

Data gravity — Considering the strong possibility that most organizations will struggle to fulfill the promise of their big data strategy with internal resources, we are likely to see a proliferation of services from various cloud providers. My concern here is that the use characteristics of Big-Data-as-a-Service aren’t being thoroughly examined.

The questions and big picture concerns.

Thanks to complex implementations, the data divide could grow.

I see big data quickly becoming a competitive advantage, which is the good news. However, I see significant parallels between the ability to pay for and adopt big data and the first decades of the mainframe. Only a few companies could afford mainframes, and those companies that could afford them were able to develop real advantage. With the introduction of the internet and cloud computing we have moved to a much more democratic model of IT availability, but big data has the potential to re-insert that gap between the haves and the have-nots.

When thinking about democratizing the use of data, the following questions come to mind. They can relate to your implementations, but also are worth thinking about in general. They are:

• Where will your data reside?
• How will you get your data to the service?
• Will tools be delivered across the wide area network (WAN) to be run locally against your in-house data?
• How will you collect and capture your own data?
• If you store your data with a service how often will you use it? Or will you likely be paying to keep it handy for rare uses? (I call this the problem of “Data in Waiting”)
• If you store your data on the service providers storage such as on S3 but you don’t want to pay for it when it’s not in use, will you delete it? How will you know it has been deleted?
• If your big data is running in a public cloud, what tools, and strategies will you use to make that data available to customers and other applications (integration)?
• Will big data cause you to buy more WAN capacity?
• Will big data cause you to rethink your enterprise application strategy?

So what’s the solution to bring data to as many businesses as possible?

To make big data available to everyone we need quite a few things to happen. We need to figure out simple use cases for data to solve common problem sets. Then we must make those available to developers so they can build tools that make solving those set problems easy. We need to continue to push the boundaries of cost-effective disk storage and network capacity, or provide ecosystem environments that allow for direct access over a private network. In an ideal world we will do both.

We’ll know big data has arrived when the use of the service is integrated into common business software tools that are used by the majority of your businesses employees. Also key will be the ability of any knowledge worker to run their own questions/queries against internal and external data sources. The average business won’t be able to call big data truly successful or accessible as long as its usability is being defined and managed by a small disconnected team of IT scientists.

Mark Thiele is executive VP of Data Center Tech at Switch, the operator of the SuperNAP data center in Las Vegas. Thiele blogs at SwitchScribe and at Data Center Pulse, where is also president and founder. He can be found on Twitter at @mthiele10.

Interested in big data? Come talk to us at our Structure Data event next month in New York City.

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