This blog has been very quiet for the last few months … and will remain as such until I am finished preparing my lecture about Information Systems for Polytechnique (2009). I should have, at that point, accumulated quite some material for future posts, since I am digging quite hard into the theoretical foundations of "Information Systems".
However, I have been reading so many newspaper articles about "cloud computing" during the last few weeks that I feel like putting a few thoughts on paper. The turning point was the article from "The Economist" last week: as is rightfully noticed, too much hype will likely cause "disillusion". I am actually totally convinced that "cloud computing" is relevant to many businesses and that it represents a revolution that is coming. I have actually explained some of this in my other blog. If you are new to this, a really simple description of the benefits could the following:
There is an implicit warning here: although "cloud computing" is "the way to go" for many cases/enterprises, there is a learning curve and a price to be paid. Especially, it will take time and energy to move from an existing architecture to one that can be "migrated on the cloud". However, "Cloud Computing" is not the "ultimate solution" for everything and I do not believe for a second that "software is dead". Let me give three simple reasons for which one may decide to stay on the "firm ground" as opposed to ""move to the cloud":
Hence we get two negative answers to the following questions:
To summarize, I would propose two "axioms/theorems/conjecture" about "cloud computing":
The first "theorem" could be labeled the "Google Theorem" since Google operations are an existence-proof of these two affirmations. They could be justified independently … and make perfect sense to anyone who has been in charge of running the IT department of a large-scale company. However, the same experience of being the CIO of a large company also suggests that performance and data synchronization/distribution issues will prevent quite a piece of the IS application portfolio to be moved to a cloud architecture, at least for the next few years.
In a previous post I have listed flexibility as one of the four pillars of agility. I defined flexibility very loosely with the following sentence: " the technical ability to cover a large span of business situations and processes with the existing set of IT services and capabilities."
This requires a little bit of further explaining. Especially, there are two ways to obtain this ability which are both relevant:
We can summarize by defining flexibility as the combination of functional flexibility (ease of change) and operational flexibility ( at run-time, without change to the existing binaries).
The first kind may be labeled "mechanical flexibility". The analogy makes sense because when you modify a mechanical device, you must (most often) shut it down before changing or adding a new piece. Most of what you can read about IT agility is actually of this kind. New technology, rule-based engines, meta-data parsers are all designed to extend the functional flexibility. This is definitely true of integration infrastructure technology that I have come across during the last few years. There are a few noticeable exceptions (such as using UDDI for dynamic discovery of services) but … surprisingly … they have not made it to mainstream IT yet.
I will call the second kind "organic flexibility" for obvious reasons: changing the SI without shutting it down (without the "go live" step) reminds us of living organisms which grow, change and adapt themselves without having to halt their biological processes. The boundary is subtle: everyday running systems are modified by the input of their users. So what? It turns out that for the same systems (at least those that I known of) there also exists "hidden"/admin parameters that cannot be changed without stopping and restarting the system. It also turns out that most major changes require writing new code, to re-compile, re-link or re-connect, hence a new "go live".
I must confess that I have been trained for twenty years to think about flexibility in a mechanical way. However, I now believe that the flexibility that matters the most is the organic kind. This will become truer and truer as the stringent requirements of real-time digital business will demand no shut-downs of any kind.
Organic flexibility is a matter of organization, people and processes as much as of technology. However, there is a technological part: one may not achieve this behavior (easily) with legacy technology. A key is obviously the availability of dynamic meta-data that is interpreted as parameters and modifies the behavior in a deep way. The challenge starts when different components must share a change of parameters to achieve a new behavior. This means and requires that propagating new parameters becomes a IT run-time service. The technology for this type of propagation is there, once again we find rule-based engines, scripting engine, automation tools such as processflows. If I reflect on the IT projects that I have been a part of, 80% of the energy is spent making sure that there is enough flexibility ("enough parameters") to make the component "future-proof", and 20% is spent thinking about the processes that are used to change these parameters. Designing an organic information system requires to change the ratio to the opposite.
These productivity factors may have greater effects than technology factors, but their implementation is not easy, and requires discernment in terms of the scope of application.
The third area of progress is the information system architecture, which we distinguish from the technology section, because it involves what is known as “enterprise architecture”, a subject which spans information technology, business processes and “strategic alignment” of the information system. Enterprise architecture is used as a complexity control strategy so that the integration costs of a new application do not reach an irreversible level as the IS grows. This is mostly a defensive strategy that is used when the complexity is precisely such that integration becomes the predominant part of IT projects. As a result, the effect that is noticed is not a “productivity miracle” but the return to a “comfort zone” where integration costs are proportional to the functional complexity of the application.
The conclusion we can make at this stage of the analysis is that there are undisputed productivity factors in terms of information system development but these are not necessarily easily deployed; the gains remain measured.
The visible part of these gains is all the more modest that another part is consumed by three heavy trends of enterprise IT[4]:
Users of general-public software such as office suite tools will have noticed that more and more resources are required to run their favorite applications (e.g. word processing), mostly due to these three reasons.
I have just finished writing a new chapter for the third edition of my book « Entreprise Architecture & Business Process Management » (which is only published in French, unfortunately). This new chapter deals with "SOA and Agility", two buzzwords of these IT times.
A part of this chapter deals with the concept of "sustainable architecture" following what I wrote in my previous post. I have proposed to paraphrase the definition from the Brundtland report:
"Sustainable development is development that meets the needs of the present without compromising the ability of future generations to meet their own needs."
into a definition of that spells out the "sustainable development" of the IT architecture:
"Sustainable architecture is the Entreprise Architecture that enables the development of today's IT services without compromising the ability to develop tomorrow's services because of an ever-increasing complexity or the induced scarcity of resources (money or skills)."
To gain this sustainability, I have been advocating for quite some while for "fractal" architectures (hence, "fractal" methods). I mean methods that can be broken into pieces and applied differently (and at different rates) to different situations. This fractal view applies to middleware, to enterprise architecture, but also to data models or to process models. The information system (as a whole) needs to grow (as a living object) according to different rates of pressure that are applied to its different parts. The CEISAR architecture documents make a very elegant and clear point about the value that exists when breaking long "end-to-end" business processes into smaller, more manageable pieces.
The major part of this new chapter is devoted to agility (mostly because I hear too much nonsense about solving the agility issues with technology). To give a short summary, I see four forces that contribute to agility:
Notice that, except for the second one, these are organizational traits and not technical ones. This, by the way, is also true of being able to leverage the value of SaaS. The software services provided by SaaS are not especially great. Using them is smart from a business and an organizational perspective, and requires "business agility/flexibility" even more than technical skills or abilities.
As I wrote earlier, SOA's main contribution is to provide a framework for sharing and reusing services. It also helps to achieve agility, but more as a second-order consequence rather than a direct cause-effect path, and not without efforts and dedication. The first-order benefits of reuse and share are cost and complexity reduction. On the other hand, as I have already explained earlier, SOA is foremost a governance principle, before being an architecture framework. If the stakeholders do not play "the game", the existence of a beautiful ESB (enterprise service bus) will not provide as much benefits as expected. As a governance principle, SOA sets principles and rules that must be followed.
If this sounds very different from a crude idea of what a "biology-inspired" IS could be … it is indeed! The strength of biomimecry as a design principle is found in what nature does very well:
One thing that nature does not do so well is the "economy principle", the "simplicity of design". When biologists study mechanisms in living objects, they are often surprised by the level of redundancy, by the complexity of the processes (which have been obtained through evolution). By the way, when we look at legacy code, we often get the same impression J …
There are two consequences:
Nature is organized around a simple principle that says that evolution cannot be stopped, which also applies to information systems. Hence the only mechanism to cope with complexity is to clean, to remove unnecessary things. Nature does great job of cleaning (and recycling) unnecessary things in living organisms. This is another aspect which may be borrowed, especially when managing a SOA. A key issue is to master the complexity (and the sheer number) of services. The book will mention a few tools and techniques to manage this catalog of shared services, but the first principle is to limit its size. Since evolution cannot be stopped, old services need to be removed.
This blog is moving very slowly (although one would think that there are enough provoking statements in this message to generate a few comments). I actually thought that it was dead, but there are a few readers coming everyday (that's what the stats tools say). I may accelerate the posting rhythm in a few months, when I'll be preparing a new course on the "Theory of Information System".
After five years spent as a CIO, I have developed the following conviction:
[1] Major architecture re-engineering projects are fuelled by pain (one could say : no pain, no gain :)).
Enterprise Architecture (EA) projects (I should rather say programs, as in a family of projects) require an unusual amount of effort and alignment throughout a long period of time. The alignment is even more difficult to achieve than the sustained level of effort, especially with a large IT organization. Alignment here means the fact that a large group of people decide to make sub-optimal choices, from their own viewpoint, to achieve a larger-scope goal. It may be strange way to look at alignment but it makes sense: if the logical choice for each actor was to move towards the same direction, there would be nothing to talk about :)
Introducing an EA scheme (what we French call "urbaniser" the information system) usually occurs because a blazing limitation of the IS has been found. It is too slow, not flexible or agile enough, not reliable enough and, most often, too expensive, etc. The level of pain is necessary to break through a "decision/action" threshold, since there are obvious risks. From a technology perspective, an EA relies on an integration infrastructure (ESB, EAI, ETL, and so on). From a culture perspective, new concepts and a new vocabulary are introduced.
What happens if the program is successful? After a while (it could be a long while :)) the pain recedes. As a consequence the alignment starts to weaken. This is not simply an internal/organizational issue for the IT department. Deploying an EA approach is a corporate endeavour, which requires from all business division a common wish to build a global system. The alignment here means that each division is ready to relinquish some of its interests for the common good.
Because of this weakening of the common resolve, the master plan becomes too heavy to carry and one returns to (some of) the previous faulty behaviors that caused the pain in the first place… I have been thinking about this for the last three years and I have come to build a second conviction:
[2] Service Oriented Architecture is the sustainable approach to develop a "well-architectured" information system over time.
This statement probably sounds lame and dull to anyone familiar with the SOA (Service Oriented Architecture) concept. All possible "claims to fame" have already been made when SOA is concerned :). I should first state a few caveat:
Hopefully my second book will be available soon to English-speaking readers (since I have finished the translation). They will see that one of my central theme is that a "well designed IS" is a corporate responsibility, not something that may be left to the CIO. The CIO may take the leadership for a "special re-engineering" program/effort, but this cannot last. Eventually it is a matter of management culture (unless the CIO wants to become a "dictator" but he or she usually gets fired quickly if this temptation is too strong :)).
Pierre Bonnet recently opened a web site about this very topic: http://www.sustainableitarchitecture.com/home. His book about the same topic will be out next month. The web site is really interesting, together with the companion site about the Praxeme method. If you go and read through it (which I encourage you to do :)), you may think that it develops a similar line of ideas (obviously, with more details and more thought-though principles). I actually agree with everything … but I do not think that it reflects truly what sustainable development is really about: people. I am personally a big fan of the ACMS approach (Agility Chain Management System). Unfortunately, (or fortunately, since no so many people may understand what it :)), this is not where I see the issue for deploying a SOA Enterprise Architecture in a sustainable way. There (rightfully so) a lot of talk about SOA governance nowadays. Unfortunately it remains complex and abstract, whereas the issue is the appropriation from all stakeholders in the company. I will return to this topic in further postings, since I believe that this (SOA governance) is the key to agility. I fear for those who will promise agility from the sole technical merits of a SOA architecture.
It turns out that there is a totally different meaning for "sustainable IT architecture" ! If one looks at the electric consumption of a data center, it is raising dangerously over the years (with respect to the double issue of energy price increase and greenhouse gas emissions). Electric consumption here includes both the powering of the computers and their cooling. Both tend to be proportional to the square of the processor frequency (one way to look at it, although the resistance decreases with the smaller scale designs). Both tend equally to be proportional to the amount of computation that is made, which is clearly growing fast in most companies.
This is why Google is seeing energy consumption as a key issue. For instance, read this newspaper article to find out about Urs Hoelzle approach to reduce server electricity footprint (more technically-savvy readers may look at this :)). Since then, Hoelzle has said Google is looking into neutralizing its carbon emissions by the end of the year.
The link with architecture is as follows. The simplest way to increase the computing power without increasing the consumption is to use massive parallelism. I don't have time to go into details today. One may look at the StorageMojo web site to get a lot of interesting stuff.
I have just finished Ray Kurzweil book "the Singularity is near" (2005). As usual, this is a fascinating book, especially from this "sustainable development of IT" perspective. From a general perspective, it is a refreshing view from a "technology optimist" which offers a clear break from the prophets of doom. As far as computing is concerned, Kay Rurzweil offers hope for software designers to be able to use much, much faster hardware (although, if you read the book, you'll see that the name may no longer be appropriate :)), something that I am dreaming off each time I run of my "game theory simulation" :)
Ray Kurzweil's optimism does not cancel the validity of Google concerns (different time scale). One might say, then, that a sustainable architecture needs to run on a grid-like structure (or any other form of massively parallel system architecture).
What does Lean Manufacturing (and experience) say ? Obviously the first shop costs less to operate (cost for producing one unit) on paper, but unless it operates in a ideal world with no variations at all, it actually costs more in real life. The second approch costs less from an inventory perspective, but mostly it is more flexible (with respect to priority changes) and more robust (with respect to load variations).
Let us now consider two information systems, from our scope of large-scale, distributed information systems (many parallel nodes running business processes) :
Here also, the first data center is clearly cheaper to build than the first one. The second one has a few advantages: better SLA (service level agreement) may be promised to the customer (tighter = faster garanteed response time), and the upgrade process (when the company grows) may be planned in a more regular way) ... but let us assume that these are not compelling advantages. That is, let us suppose that the customer accepts the two different SLA:
There is another way to say it: if your IS is run in such a way that message queues are often full of pending requests, setting up a proper SLA is a very difficult job, because predicting the behaviour (response time) of an overloaded queing system is hard science. It is not enough to add reasonamble margins (such as, promise a 10 minutes response time because the average processing time is 1 minute).
There is nothing new here. This experiment confirms what experience or intuition shows. What is interesting (and what surprised me) is the HUGE difference that the computing experiment reveals.
I plan to do similar experiments within the (global) entreprise context. I need a model that links the behavior of the IS with that of the company itself. Fortunately, I can rely on the great work (and models) just released by the CEISAR.
The CEISAR is a French initiative, under the patronage of the Ecole Centrale, to create a repository of models and practical knowledge about Enterprise Architecture. A first gem is their global model (follow "main concepts" then "Core Business System" on their web site), an attempt to define Enterprise Architecture with 10 key concepts. Another extremely useful piece that is part of the first release is a document about entity modeling. In one of my books I complained that this type of knowledge was not accessible (and could only be obtained from experience). It is nice to see real-life-experts, such as Jean-René Lyon, share their knowledge about such topics.
I definitely plan to adhere to CEISAR's terminology and framework for my own future work about IS architecture. One of the most pressing issue (as I have already testified on this blog) is to build a framework/model to explain, discuss, simulate data distribution and synchonization protocol. The only way to make this a relevant topic is to keep a very broad perspective, that includes a model of the coupling between IS and business. The nice conclusion is that this type of work falls neatly between my two topics of interest (cf. my other blog) : IS efficiency and Enterprise efficiency.
