My 5 Enterprise Cloud Predictions for 2013

imageI believe that this is the year when the enterprise will find its way to the cloud.

The mega Internet sites and applications are the new era enterprises. These will become the role models for the traditional enterprise. IT needs remain the same with regards to scale, security, SLA, etc. However, the traditional enterprise CIO has already set the goal for next year: 100% efficiency.

The traditional CIO understands that in order to achieve that goal, IT will need to start and do cloud, make sure that IT resources are utilized right, and that his teams move fast.

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The IaaS Management Market: Evolution, Vendors and More

A lot has already been said about the false cloud use where the IaaS platform utilized as an hosting extension of the IT organization’s data center and not taking advantage of the elasticity benefits to generate a cost effective and scalable IT operation. Using the public IaaS whether it is Amazon, Rackspace or any other vendor means using a highly dynamic environment which presents an increasing complexity hence loss of control. Checking the list below I can say that cloud (including all its layers IaaS, PaaS and SaaS) control basically contains the same aspects as the good old system management.

What is “System management” ?

“refers to enterprise-wide administration of distributed systems including (and commonly in practice) computer systems.”

“System management may involve one or more of the following tasks:

  • Hardware inventories
  • Server availability monitoring and metrics
  • Software inventory and installation
  • Anti-virus and anti-malware management
  • User’s activities monitoring
  • Capacity monitoring
  • Security management
  • Storage management
  • Network capacity and utilization monitoring”

Read More on Wikipedia

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Hybrid Cloudonomics – Part 2

The first part of Weinman’s lecture discussing the basic “go to the cloud” and demonstrating cloud environments’ loads of different corporations’ web applications. In this part we will bring 6 scenarios presented by Weinman, each includes a brief analysis and proof of its cost and benefits.

First lets start with several assumptions and definitions:

> > > 5 Basic assumptions Pay-per-use capacity model:

  1. Paid on use – Paid for when used and not paid for when not used.
  2. No depend on time – The cost for such capacity is fixed. It does not depend on the time or use of the request.
  3. Fixed unit cost – The unit cost for on-demand or dedicated capacity does not depend on the quantity of resources requested (you don’t get discount for renting 100 rooms for the same time).
  4. No other costs – There are no additional relevant costs needed for the analysis.
  5. No delay – All demand served without any delay.

> > > Definitions:

D (demand): Resources demand in a specific time interval. D is characterized by mean (average) and a maximum P (peak) . T (time) is the time duration in which the demand existed {D(t) ,0<t<T}. For example the average demand A can be 5 CPU cores with a peak P demand of 20 CPU cores.

Define C (cost) to be the unit cost per unit time of fixed capacity.

Define U to be the relation between the cost of resources in the cloud (pay-per-use) and a pure dedicated IT solution.

The following six cases presented by Weinman are part of the total eight cases presented in his article “Mathematical Proof of the Inevitability of Cloud Computing”:


Case 1:   U < 1

The simplest case where utility cost less than dedicated ==> Pure pay-per-use solution costs less than a pure dedicated solution.

Proof: The cost of the pay-per-use solution is A (average) * U (premium) * c (unit cost per time) * T (time of use), A*U*c*T. The cost of a dedicated solution built to peak is P(peak of D)*c*T. Since and A<=P and U<1 ==> A*U*c*T < P*c*T

Explanation: It is intuitively understood that if the cloud is less expensive per unit per time period, then the total solution based on paying only for the demand is a less expensive one.


Case 2 :   U = 1 and A = P

The utility premium is the same as the dedicated, and demand is flat (no peak) ==> a pay-per-use solution costs is equal to dedicated solution built to peak

Proof: The cost of the pay-per-use solution is A*U*c*T. The cost of a dedicated solution built to peak is P*c*T. Since U=1 and A=P, ==> A*U*c*T = P*c*T

Explanation: If there is no variability in the demand and the cost is the same, both alternatives have the same cost. That being said, we should remember the assumptions we are under, the very narrow scenario and the fact that we are not considering financial risks.


Case 3 : U = 1 and A < P

Pure pay-per-use solution costs less ==> a pure dedicated solution.

Proof: The cost of the pay-per-use solution is A*U*c*T. The cost of a dedicated solution built to peak is P*c*T. Since U=1 and A< P, Then: A*U*c*T = P*c*T

Explanation: This is very important for the understanding of the benefits for pay-per-use: if there is an element of variability, there is a major benefit to choosing this approach. Now let’s find out what happens in the case that the utility cost is greater than the fixed utility cost.


Case 4 : 1 < U < P/A

If the utility premium is greater than 1 and it is less than the peak-to-average ratio P/A, that is, 1<U<P/A then a pure pay-per-use solution costs less than a pure dedicated solution.

Proof: The cost of the pay-per-use solution is A*U*c*T. The cost of a dedicated solution built to peak is P*c*T. Since U<P/A, Than: A*U*c*T < A*PA*c*T = P*c*T

Explanation: What this means is that the utility unit cost can be higher than a fixed solution up to a certain point and still be the right economical choice. That point is a variable of the variation of the demand. In simple terms, we save money by not possessing unused resources when the demand is low.


Case 5 : U > 1 and TpT < 1U 

Lets add some definitions to the ones above:

  • Tp (peak duration) to be the duration where the demand was at peak
  • ε to be the gap between the actual peak and the per-defined peak (that is, if the resources demand exceeds (P – ε) we’ll use the cloud for our resources).

If U stands for how much more expensive the cloud is versus a fixed solution, in this case it will be easier to look at the Inverse of U (how much the fix solution is more expensive than the cloud). This case means that the percentage duration of the peak is less than the inverse of the utility premium, than a hybrid solution costs less than a dedicated solution.

Proof: The hybrid solution consists of (P ε) internal resources and the rest, ε will be handle on-demand by pay-per-use Tp of the time. The total cost equation is: 

 Given [(P ε) * T * c]+ [ ε * Tp * c * U ] and Our assumptions were: TpT  <  1/U   ==> Tp * U < T  and [ε * Tp * c * U] < [ε * T * c] ==> combine those ==> [(P ε) * T * c]+ [ ε * Tp * c * U ] < [(P ε) * T * c]+ [ε * T * c] ==> A dedicated solution cost is: [(P ε) * T * c]+ [ε * T * c] = P * T * c

Explanation: What that means is that there might be a less expensive way than internal fixed solutions if there is some variation of demand. Obviously an optimal solution should be according to its your own characteristics of demand.


Case 6 : “Long Enough” Non-Zero Demand

Lets define:

  • The total duration of non-zero demand to be TNZ. TNZ is the sum of all periods where the demand was above zero. 
  • Define ε to be the dedicated resources.

If the utility premium is greater than the dedicated and the percentage duration of non-zero demand is greater than the inverse of the utility premium, i.e., U > 1, and TNZT > 1/U than a hybrid solution costs less than a pure pay-per-use solution.

Proof – (This proof is the mirror image of the prior one). The cost of serving this demand with utility resources is: ε * TNZ * U * c. The cost of serving the demand with dedicated resources is: ε * T * c. Since TNZT > 1/U than T < TNZ * U Than ε * T * c < ε * TNZ * U * c 

Explanation: This means that you’ll need to consider using the cloud even if it’s more expensive to satisfy a portion of the demand and the baseline of your demand you use dedicated resources.


Let’s Summarize – 

The analysis Weinman does is basic including very strict assumptions. It ignores cloud enhanced pricing options (such as AWS spot and reserved instances). It is important to add that those options still doesn’t provided by most IaaS vendors hence this should be taken in mind when selecting an IaaS vendor. Nevertheless, this important research gives us an excellent opportunity to understand the overall approach and mechanisms which affect out cloud architecture decision.

 It is the the enterprise leader’s responsibility to treat their cloud establishment as part of the organization strategy including its architecture decision. From our experience and study of this evolving trend we found that sometimes the cloud decision might be taken by the operational leader (i.e. IT manager) without any intervention of the enterprise higher management. This is totally wrong, going forward the company will find itself suffer from huge cloud expenses and issues (such as security and availability) and will need to reorganize hence reinvest and hope it is not to late. In this post we presented another option for cloud deployment when a mixture of resource allocation from within the enterprise and from the cloud might be the best economic solution. We also saw that it depends on several factors like the variation of the demand and its prediction.


This is only a sneak peek to Weinman’s complete article “Mathematical Proof of the Inevitability of Cloud Computing” . To Learn more about the above scenarios and more, we strongly suggest to read it.

Hybrid Cloudonomics: a Lecture by Joe Weinman – Part 1

Posted by Nir Peled

Joe Weinman is well known in the cloud computing community as the founder of Cloudonomics. Presenting complex simulation tools, Weinman characterizes the sometimes counterintuitive business, financial, and user experience benefits of cloud computing including its on-demand, pay-per-use and other buisness aspects. Last month I had the pleasure of participating in Weinman’s webinar. Weinman discussed several interesting points which I would like to share with you.

Weinman started by contradicting what seem to be the fundamental assumptions regarding the Cloud and its benefits. There was nothing radical about what I heard but it made me think and challenge all the things I took for granted –

1 – Cloud is a brand new technology and business model  > > >  The same business model and attributes are being applied in hotels, rental car services, etc’.

2 – Cloud encompasses services accessed over the web via browser  > > >  The cloud is a general architecture module and the Web/IP/Browser (is as important as they may  be) are far from telling the whole story. There are other types of networking technologies such as Optical Transport MPLS and VPLS that need to be leveraged to unlock the value of the cloud. You don’t necessarily need to use a browser to get services in the cloud (examples include – audio conferences, webinars, M2M etc.)

 3 – Large clouds have great economies of scale > > > Not completely true because today the large cloud providers are using the same architecture that is available for any enterprise, therefore there is no major benefit from their scale in terms of economy. However,  they do benefit from other characteristics like scalability, geographic dispersion and statistic of scale.

 4 – IT is like electricity, so all IT will move into the cloud  > > > IT is not like electricity, from the economic perspective, electricity has the benefit of the economies of scale. While IT decisions are complex and the economic decision on how much of your IT to keep in the enterprise and how much to put in the cloud is based on numerous factors such as flexibility, cost, nature of the application etc.

5 – It’s important to replace CAPEX with OPEX > > > It is not always important to do so and it very much depends on financial decisions that the company makes regarding its financial and funding activities.

6 – Cloud cost reduction will drive lower IT spending > > > Weinman mentioned the Jevons paradox effect, is the proposition that technological progress that increases the efficiency with which a resource is used tends to increase (rather than decrease) the rate of consumption of that resource.

Joe refers to the argument (from his work) that “The mathematical proof of the inevitability of cloud computing” is the economic rationale for hybrid. He demonstrated demand variability of several corporations as you can see below:
 

Example 1: HP.com – There is not so much variability

Example 2: Large search provider – Weekends Vs. Monday to Friday

Example 3: Tax preparation firm– Growth of the early filers and then April 15th (tax day in the USA) drop to 0 on the 16th of April.

 

In the second part of his lecture, Weinman demonstrated six optional cases for cloud deployment including detailed calculations for the IT environment costs. He defines a variable U which is the relation between the cost of resources in the cloud (pay-per-use) and a pure dedicated IT solution. For example if U<1, that is, the utility premium is less than the unity, a pure pay-per-use solution costs less than a pure dedicated solution. In the Part 2 we will present those six options in details and will be able to give you a great insight about your hybrid cloud plans.

Stay Tuned !

Nir.

The author of this article is Nir Peled, a reporter and a contributor `I Am OnDemand` .

Nir Peled