Tuesday, September 6, 2016

Realizing the Software Defined Enterprise

While Gartner seem to be the primary advocates of software defined everything, (SDx) it’s rather obvious that SDx is primarily focused on service delivery, infrastructure and networks. I give full credit to Jason Bloomberg for exploring software defined development and devops in his recent blog. [1] He merges SDx and Shift Left ideas saying,  “If we combine no-code with DevOps properly, we now have a way of abstractly representing working production software, including its functionality. Not just the limited-scope apps that some no-code platforms are best known for, but full-blown, enterprise-class applications – created from nothing but their abstract representations with the push of a button.”

Heady stuff! In fact Jason  dismisses any skepticism advocating high risk strategies as necessary for digital transformation, “Given the exponential pace of technology innovation all around us, the greater risk is that we miss the full significance of Software-Defined Everything and its impact on the digital enterprise – until it’s too late.”

Wise heads may be shaking at this point; many will remember early attempts at diagrams to code, computer assisted systems engineering, model based development etc. All of which work in a limited manner, but never achieved the level of capability that is necessary to support enterprise class environments. However it has been clear for some time that this is a realistic goal. The basic concepts were articulated by Jack Greenfield and Keith Short in 2004 while they were at Microsoft, described as the Software Factory – “the configuration of extensible tools, processes and content using a software factory template based on a software factory schema to automate the development and maintenance of variants of an archetypal product by adapting and configuring framework based components.” [2]

Where I part company with Jason is in his promotion of “no-code” as the primary ambition in conjunction with integrated DevOps. The software factory is a “low” code environment, unlike no-code environments under full control of the developer community, who codify common patterns to allow standardization and assembly of common code to perform repeatable tasks; establishing an exceptionally high quality and productivity environment customized for the unique needs of a specific enterprise. But the really big value adds are that the factory governs reference architecture compliance and facilitates evolutionary development, enabling continuous change in initial development and the operational state, because all artifacts are under management. That’s not the full story; there are some key principles that make this practical:
1. A formal reference architecture is required to allow full life cycle meta data management and standardization of delivered artifacts. Note here I mean reference as meta-objects. A key aspect of the reference architecture is that everything is delivered as a service according to defined behavioral and dependency policies that enforce separation of concerns at all levels and reduce dependencies.
2. Rigorous specification of business services and rules independent of implementation. (the abstract representations referred to above) that support test driven development and provide high visibility of intra-project dependencies.
3. Abstracted specification interface removes requirement for (UML or similar) modelling skills. Allows business or business proxies to be responsible for the specification task.
4. Design by contract establishes strong boundaries, visible dependencies and separation of concerns.
5. Automation of infrastructure and codification of exemplar patterns in common code using software factory concepts.
6. Late (generation time) bound technology, allowing open technology architecture (platforms and frameworks) and inheritance of architectural changes with minimal impact on functional code.
7. Design by exception – only new patterns require design. Regular patterns are already codified in the factory.
8. Seamless linkage with Continuous Integration, Test Automation and DevOps.
9. Scalable Agile delivery process uses managed artifacts to provide high visibility of dependencies.
10. Continuous modernization process enables evolutionary capability development and change.

Reading this list, you might be tempted to say, this is just model driven development, or limited code environment, or SOA code generation etc. But the sum of the parts is greater than the whole – it’s a new model which is inherently business driven, with clear separation of business specification and implementations and technology. We call it the Agile Service Factory. [3] Today it is being used to deliver very large scale, enterprise class modernization projects [4] with exceptional productivity and quality, and the outcomes are inherently agile business services and solutions.

References:
1.  Building the Software-Defined Digital Enterprise (Part 2), Jason Bloomberg
2.   Software Factories, Jack Greenfield and Keith Short, Wiley, 2004
3. The Agile Service Factory
4. White Paper: Modernization with Service Architecture & Engineering and the Agile Service Factory

Wednesday, June 29, 2016

Brexit Planning and Modernization

Change is intrinsic to the IT industry and its customers. And most of us, whether in business or government, are deeply focused on enabling business agility, whether through technology change, product innovation, software architecture, agile practices, modernization projects, role and skills development, etc. But the momentous decision of the UK to leave the European Union has prompted me to revisit my change models. Clearly the scale of the implied change is very wide ranging, and the impact on government, industry, commerce and education sectors in the UK and some parts of Europe may be extraordinary, affecting core business and societal models like no other change short of war!

How do we businesses, government departments, educational establishments and individuals make plans? I suggest before you can even start planning, a model is needed to aid understanding of what's happening, and where you are in the process. As it happens one of my colleagues just passed me a link to Jason Bloomberg's blog on Architecting Change as a Core Competency [1]. This includes a model for understanding change, and in the table below I have taken the liberty to extend Jason's model.
TYPE OF CHANGE
Characteristics
DEFINED
Understood; stable present and future
LINEAR
Manage growth/decline
CYCLICAL
Product / Service / Market maturity
DISCONTINUITY
Unexpected event - terrorist attack, disaster, death of key personnel;
ACCELERATING
Inflexion points triggered by technology change; e.g disintermediation, industry platforms, Uber, Apple in Music etc
CHAOTIC
Seemingly simple decision causes wide impact, unpredictable effects; e.g merger, acquisition, demerger,
UNDEFINED
High level of uncertainty over model and outcomes

The model is not like a maturity model in which we are in one state at any point in time. It seems clear that many of us in the UK and Europe will be experiencing discontinuity (it's unexpected, sudden and largely unplanned for), and chaos (the simple decision to leave the EU triggers an unimaginable number of potential consequences, for instance, there are evidently 40,000 pieces of UK and EU legislation that will be impacted) and lack of definition, (the arrangements will only emerge over time, perhaps over many years). The chaotic element is further amplified by the absence of anyone in charge and the number of parties (28 EU countries) to the current and any future agreement.

So given we have a major discontinuity with chaotic impact and very little definition of the approach, do we just metaphorically sit on our hands and do nothing until the politicians make some agreements? Already we see some large enterprises are indicating their likely strategy; commonly financial, telecomms and IT organizations making initial plans to relocate key parts of their business; either because regulatory requirements mandate operation in the EU, or standards such as Cloud data make it imperative to move data centers, or the EU digital strategy make it imperative that telecomms enterprises are located in the EU, or new EU borders require new, enhanced or multiple tariff and security management.

While these type of changes will happen over time, there are others that are urgent; many businesses are right now adjusting resources and prices to leverage or compensate for changes in demand caused by currency shifts. Tactical changes will usually be accommodated in existing systems; but more profound changes may mean significant change in the core business model over time. The model below is a very simple model and highlights the central things that may be subject to change. Modelers will recognize instantly that these "things" are core entities that generally "run the business" and generally endure while the core mission and objectives of the enterprise remain stable. And consequently, Brexit triggered changes may well have profound changes to the business model.
For many enterprises this change may well be an existential event. That existing systems will require such major change that radical modernization effort will be required. Perhaps enterprises have been delaying modernization of core, back end systems because the cost justification is not compelling - and for many that cost justification will now become overwhelming and urgent. What will be necessary however is for systems modernization (people, process and technology) to be carried out in a manner that the enterprise can continuously adapt because Brexit triggered changes will be happening progressively for the next two to (say) seven years. It's time to start planning right now, so that as the regulatory requirements and trade agreements are framed the systems are in place to respond.  

[1] Architecting Change as a Core Competency

Relevant Blogs: Modernizing the modernization strategy

Tuesday, April 12, 2016

Scaled Agile Factory - Going Beyond the Usual Suspects

Abstract: If you address the question of how to scale Agile projects by considering what framework to use, you are only looking at one aspect of the problem. Scaling is all about coordination – managing enterprise considerations and cross program dependencies, and the defacto frameworks (SAFe, LeSS and DAD) focus on the people and process dimensions. However, in combination with a factory approach you may be able to automate many of the compliance and dependency management issues.

The question of how to scale Agile development has been around a while. In January 2015 I commented [1] on a clear trend in which my customers were voicing concerns about loss of consistency; inability to govern; lack of coordination and increasing time to market. Since then I have observed many large organizations adopting SAFe (Scaled Agile Framework) perhaps because it appears to be the only game in town, or perhaps there’s good marketing or there’s strength in numbers. But the criticisms of SAFe [2] haven’t gone away. The central and continuing concern is that SAFe compromises core Agile principles of self-organizing, cross functional teams that have full responsibility for the delivery of potentially shippable increments. And that SAFe looks suspiciously like WaterScrumFall because there’s a high overhead of portfolio, value stream and project management and in all probability intentional architecture. Now I have mixed opinions on SAFe; I see positives in value streams and product management which are important. And for organizations that have large programs, highly organized, structured approaches will be seen as lower risk, and indeed something that takes them some way down the Agile path, without straying too far from conventional management comfort zones. But the outcomes are unlikely to be inherently “agile”.

What SAFe does, is provide a rather conventional approach for a complex problem that most enterprises have – that is to deliver high integrity solutions that can work in an enterprise context that demands cross project dependency management, consistent data and reference architecture, collaboration with the existing portfolio complexities, compliance with enterprise standards and governance etc.

There are alternatives. Craig Larman and Bas Vodde in their books [3] and more recently with their LeSS initiative [4] have pursued a very different path that starts with Scrum and scales by understanding the needs for coordination while adhering to core Scrum principles. In their forthcoming book [5] they say, “LeSS is (1) lightweight, (2) simple to understand, and (3) difficult to master—due to essential complexity”. And this allows us to contrast the different approaches; while SAFe clearly works at some level, it has its roots in conventional large scale project management, whereas LeSS is lightweight, but requires much deeper understanding of the systems dynamics because of the inherent complexity of all the coordination requirements.
So the real question underlying Scaling Agile should be, “can we address some of the coordination requirements in a manner that reduces complexity and eliminates some of the need for additional layers of management or events?”

In my post Service Factory 2.0 [6] I describe the conceptual background of the Software Factory, ideas pioneered by my old friend Keith Short and Jack Greenfield while they were at Microsoft. Today these have evolved and become specialized around a framework of tools, repeatable processes and patterns for creation and assembly of services – manifest as first order components with formal interfaces. If you consider that all core business functionality is increasingly composed of services and their operations, this provides us with a reference architecture that by design implements separation of concerns.  Figure 1 below is a conceptual view of the scope of the service factory in terms of managed objects.
Figure 1

Naturally there will be other patterns involved in any solution including UX and workflow; but for most enterprise class solutions, a high proportion of the functionality should comprise services and business rules. This allows a consistent, highly automated approach to architecture, requirements specification, design and test. The factory effectively implements a proven service reference architecture as a platform which can be customized for individual programs, projects and technologies. While the factory platform is similar to an architecture runway in scope and intent, because it is model based the factory framework enables continuous evolution of the platform capabilities that are automatically inherited into work in progress factory code allowing program wide changes to be incorporated, often with minimal or no change to the service specific code. And the factory is a repository of the life cycle artifacts that can be leveraged for various management tasks including governance of traceability, impact analysis, etc. 

Let’s consider the key coordination and management activities typically required in a scaled agile program and how the factory may facilitate that. In Figure 2 below I have used the SAFe layers of portfolio, program and team, albeit without the value stream level. But apart from that, the view is intended to be framework neutral. The diagram illustrates how the Factory provides a full life cycle backplane that establishes the underlying (meta) model that ensures all the participants are in compliance with core concepts from portfolio planning through to delivery and production. The populated model is therefore able to provide essential information particularly about dependencies, but equally complete traceability and governance between business requirements and delivered services and rules.  
Figure 2

In the LeSS framework, Larman and Vodde disregard constructs such as ART (Agile Release Train) and 8 to 12 week PIs (Program Increments) and also the Hardening Sprint, preferring to use the standard Scrum duration of 2 to 4 weeks, with continuous integration.  We might assume these management constructs (ARTs and PIs) were invented because of the difficulty of effective inter team communications, and the overhead that creates. Larman and Vodde have a lot of good ideas about how to manage effective inter Teams communications, but their approach is essentially based on feature or story dependencies. In the factory environment inter-team dependencies can be more accurately based on service operation dependencies. But this is just the tip of the iceberg, in terms of how the factory can be leveraged to manage activity. The service specification becomes a pivotal work product; as it becomes available other teams and team members have access to detailed behaviour information that can inform and facilitate working ahead for developing depending services, test case development including automation assistance in case development, plus devops. 

Another huge issue in Agile projects is managing technical debt. In the factory environment the standard patterns generate all the infrastructure and shared code, and when changes take place, as discussed above, teams can perform an architecture update, inheriting all the changes to bring their project in line with the latest reference architecture. And because the factory is driven by the specification level, independent of technology it is inherently late binding, allowing change if technology with minimum impact.  

By utilizing work products that are part of a defined process based on the full life cycle reference architecture, the factory approach reduces the essential complexity of the scaling task. All moving parts are under management. This doesn’t detract from the inherent purity of the Agile approach. Rather, the defined process provides clarity over the minimum necessary “planning work” (intentional architecture, rules definition and business requirements). And the reference architecture and factory process provide a firm foundation on which emergent architecture can be more effectively carried out by the cross functional delivery team. This is likely to encourage programs to adopt a hybrid approach to their organizing model, embracing elements of LeSS like guidance to optimize multiple concurrent Scrum based sprints with continuous delivery, and to complement them with minimum necessary elements of SAFe, particularly those that are required to communicate to more conventional stakeholders. But, at least for mid-sized projects, maybe up to 10 teams, it seems overkill to adopt the formality of PI Planning and everything that comes with it.

In this post I have focused on the scaled Agile approach for projects, but it’s also useful to understand the factory has other important outcomes. First the highly modular nature of the reference architecture (see Figure 1) leads to “solutions” that are inherently agile. Because solutions are comprised primarily of services and rules with strong formal contracts, implemented using component based implementation patterns, the horizon of change is likely to be very constrained. Further the specification approach in which services, rules, data and processes are defined independent of implementation and technology provides high levels of visibility to the business, and high transparency and traceability of the implemented solution. Finally, we have a way to realize architecture in inherently agile solutions without Big Upfront Design, or indeed Big Upfront Organization, that will of course never become legacy because they can be continuously evolved. 


[2] Reasoned criticisms of SAFe

[3] Scaling Lean & Agile, Craig Larman and Bas Vodde, Addison Wesley, 2009



Monday, February 8, 2016

Going Beyond Defined Agile Methods

I’ve been spending nearly half my time in Philadelphia over the past while, and I just happened to have a spare Saturday yesterday, so I hightailed it downtown. I had two objectives – to explore the Museum of Art and to attend a Brahms concert by the Philadelphia Symphony Orchestra. One of the featured exhibitions in the adjacent Perelman Building caught my eye. It’s named, Work on What You Love: Bruce Mau Rethinking Design. I wasn’t sure what to expect; I certainly hadn’t heard of Bruce Mau before, but I am always interested in design and design methods.

The gallery is essentially laid out to be controversial, to challenge one’s status quo thinking. In a video, Mau says, “practically everything that we do is being designed or redesigned; if you think about the way that we live now our life from womb to tomb is a design experience. If we want a great life experience you have to design it.” Mau goes on to say his work is focused on allowing people who aren’t designers to have access to the power of design, in their life, their work, in their business. Giving people the tools to design their future in a highly positive way.

Almost at the door of the gallery is a huge exhibit detailing his “incomplete manifesto for growth”. And the manifesto principles look like a superset of the Agile development manifesto, but writ large, with vastly greater ambition. First there are 43 principles. What! I say to myself, how can that many principles be useful? But of course once you start reading you are hooked. The Agile principles are embedded, but there’s much more. Let me give you a taster:

1. Allow events to change you. You have to  be willing to grow. Growth is different from something that happens to you. You produce it.

5. Go deep. The deeper you go the more likely you will discover something of value.

8. Drift. Allow yourself to wander aimlessly. Explore adjacencies. Lack judgment. Postpone criticism.

9. Begin anywhere. John Cage tells us that not knowing where to begin is a common form of paralysis. His advice: begin anywhere.

13. Slow down. Desynchronize from standard time frames and surprising opportunities may present themselves.

16. Collaborate. The space between people working together is filled with conflict, friction, strife, exhilaration, delight, and vast creative potential.

20. Be careful to take risks. Time is genetic. Today is the child of yesterday and the parent of tomorrow. The work you produce today will create your future.

22. Make your own tools. Hybridize your tools in order to build unique things. Even simple tools that are your own can yield entirely new avenues of exploration. Remember, tools amplify our capacities, so even a small tool can make a big difference.

29. Think with your mind. Forget technology. Creativity is not device–dependent.

31. Don’t borrow money. Once again, Frank Gehry’s advice. By maintaining financial control, we maintain creative control. It’s not exactly rocket science, but it’s surprising how hard it is to maintain this discipline, and how many have failed.

39. Coffee breaks, cab rides, green rooms. Real growth often happens outside of where we intend it to, in the interstitial spaces—what Dr. Seuss calls “the waiting place.”

41. Laugh. People visiting the studio often comment on how much we laugh. Since I’ve become aware of this, I use it as a barometer of how comfortably we are expressing ourselves.

These are just a sample. You get the idea. This is Agile for the real world. For those people that are stuck in the zone of religious adherence to Agile development methods this may be anathema. But it’s a wakeup call. Invent your own.

The complete list and much more . . .

Work on What You Love: Bruce Mau Rethinking Design
November 21, 2015 - April 3, 2016

AFTERWORD: I wonder to what extent these principles map to a variety of design disciplines? In fact surely all design disciplines are creative processes. Would this include musical composition? I see no reason why not.

Saturday, November 7, 2015

Modernizing the modernization strategy

I was amused this week to be contacted by Researchgate, a syndication platform that have somehow republished my paper Enterprise resource planning: Componentizing the enterprise application packages that was originally published in April 2000 by the ACM. [ref 1] It was entertaining reading something I authored over 15 years ago, but quite refreshing that much of the thinking makes sense today. The gist of the paper was to discuss how some of the package vendors had responded to the impending Y2K event by componentizing and service enabling their packages, many of which at that time were exemplars of the worst monolithic application architecture (sic). At that time I observed that the componentization was a key factor in the huge growth of the EAI (enterprise application integration) market, and provided a genuine alternative to the conventional “buy or build” choice by enabling “buy, build or reuse”.

And this is really where my thinking has evolved considerably. Fifteen years ago we were very focused on transactional systems with a much lower requirement for flexibility. Today, and indeed for the past decade, I advise a radically different approach which is much more strongly business focused.

All too often the big question that bubbles to the surface is “should we buy or build?” And not surprisingly the buy option is often seen as an easier option because current systems are viewed as problematic and the organization has little or no competence in large scale systems development. In fact, for many organizations that have outsourced IT, development is not seen as a core business capability. So the question of buy or build becomes focused on whether a suitable package exists at an affordable price, where suitable means “supports our processes and information needs as we understand them today”.  And package vendors are well equipped to demonstrate how they have readymade and low risk capabilities that have high levels of configurability.

These days I advise a focus on just two important questions:
1. What are the systems requirements of our future business?
Many enterprises recognize their business models are changing rapidly and that there are numerous triggers, including technology, regulation, demographics, climate change, economics and more, that only indicate much more volatility. Most enterprises operate established sector specific models that have many conceptual elements that are shared with competitors, with clear areas of differentiation. Geoffrey Moore [ref 2] gave us excellent vocabulary to describe the Core and Context areas of our business, in which Core business capabilities should be highly differentiating and Context capabilities are managed to be equivalent to the competition, but no better. So the primary question to attempt to answer is, how might the balance between Core and Context shift over the coming years? If the shift is likely to be towards the Context, where competitive equality is a high probability outcome, then a buy solution “may” be appropriate if there is a package that really fits with the business model. This could well be true of highly regulated industries, semi-state organizations etc. However all the signs are that in the general commercial market there is likely to be a frenzy of innovation of core capabilities. That a high level of unpredictability inherent in some of the major triggers would indicate the most appropriate strategy will prioritize maximum flexibility  and response to change. And that leads on to the second important question.  

2. What are the cultural requirements of the future business? 
Everyone will recognize the extraordinary innovation culture demonstrated by organizations such as Amazon, Google and the vast numbers of start-ups leveraging technology opportunities. And this cultural paradigm shift is not restricted to so called Internet companies. Many large, conventional businesses recognize the existential threat and have responded, integrating bricks and mortar operations and processes with Internet portals, apps, IoT and B2B architectures. Crucially evolving their products and services in which information is an integral component. And most of these innovating companies are exploring Agile development practices demonstrating the extraordinary innovation, productivity and quality that can be achieved by a convergence of business and IT skills and expertise. Some of these organizations have reinvented their business models because they have been brave enough to change from command and control to delegated responsibility development models. They are demonstrating tomorrow’s enterprise is an information enterprise where conventional demarcation lines between IT and business need to be challenged and reengineered. Do packaged solutions have a place in such a high innovation culture? Of course – for the obviously Context areas of the business such as general ledger and receivables they make sense. But for Core business capabilities, a packaged solution must look like the dead hand of a commodity.

You may ask, “but back in April 2000 you expected a flourishing integration market, based on buy, build and reuse, why is that not applicable today?” And my answer is, “That actually happened in the noughties. But today we have a different challenge. Burdening creative people with huge integration and semantic transformation complexity is not a great way to reinvent the future business, as the past will be an anchor holding you back. Integration will be necessary and essential, but your core business architecture should be optimized as much as possible”

In a recent blog post I said, “modernization is not about achieving a new plateau of capability and functionality. Rather it is about enabling continuous, short cycle time response to change”. It’s about creating an Agile Enterprise.

CODA: Geoffrey Moore’s concept of Core relates to the centrality and mission critical nature of a capability. This should not be confused with the CBDI-SAE concept of Core Business Service, which is the service layer managing the state of the business. 

References:
1. Componentizing the enterprise application packages , David Sprott. ACM April 2000 
Researchgate  (public domain)
ACM (subscription or pay as you go)
2. Geoffrey Moore, Dealing With Darwin


Monday, August 3, 2015

Enterprise Modernization - The Next Big Thing!

“We tend to think the strong will survive, but a virus is a very small thing that kills big things.” Horace Dediu, Clayton Christensen Institute, speaking about the fall of Nokia.

All enterprises, be they large or small, national or multinational, commercial or government agency, American or Chinese, Japanese or European, are carrying the dead weight of their history and almost certainly continuing to add unnecessary complexity and excessive cost that will progressively reduce effectiveness, with the potential to trigger existential crises. Newer enterprises including Internet platform and Cloud based companies are not immune from this effect. As Horace Dediu has commented, Nokia is a classic case of a large enterprise brought from market leadership to irrelevance and zero value in an extremely short space of time.

In the past, modernization has become synonymous with technically related "application modernization" The term "modernization" is commonly used to refer to information systems, applications and technologies. And it is very common for systems or applications to be "modernized" because a technology has come to the end of its life, or an application is so antiquated that it cannot support newer business process patterns such as multi-channel and mobile. More generally organizations clearly implement modernizing programs without necessarily using the modernizing name. For example transformation programs or projects will often involve considerable elements of modernization. Similarly adoption of Agile methods may be considered a form of process modernization. Or the introduction of DevOps practices, enterprise architecture, master data management, life cycle management etc. But it is notable that each of these forms of modernization are discipline centric. It is very rare for an enterprise to undertake concerted effort to understand what modernization really means for a specific enterprise and to plan and execute modernization that delivers inter-discipline collaboration in support of specific modernization objectives and goals.

Each enterprise has unique modernization needs. A bank may see a primary modernization goal to establish core banking systems that reduce the risk of negative customer impact, such as delays or errors in transaction processing. Also to be able to introduce price and product change in days or weeks. A healthcare company may similarly see the requirement to change prices rapidly but equally the need to rapidly implement new legislation. A retail enterprise may see the ability to interact with customers using processes that span multiple technology, shopping and delivery channels, and to be able to influence the customer decision making process to achieve maximum customer satisfaction.  A key element apparent in all these modernizing goals is that modernization is not about achieving a new plateau of capability and functionality. Rather it is about enabling continuous, short cycle time response to change, targeted at the very specific areas that are mission critical for the individual enterprise.

The problem with modernization is that it is widely perceived as slow, very expensive and high risk because the core business legacy systems are hugely complex as a result of decades of tactical change projects that inevitably compromise any original architecture. But modernization activity must not be limited to the old, core systems; I observe all enterprises old and new, traditional and internet based delivering what I call “instant legacy” [Note 1] generally as outcomes of Agile projects that prioritize speed of delivery over compliance with a well-defined reference architecture that enables ongoing agility and continuous modernization.

What’s required is a modernization approach and strategy that progressively breaks out business and technology components that establish highly independent units of business capability that comply with a reference model and architecture that ensures architecture agility and implements clear fire breaks between the components.
But as discussed, enterprises are extremely reluctant to undertake modernization as they see it as all cost and risk. Transformation projects are widely viewed in the same way. And anyway immediate business priorities always trump housekeeping!

There are various aspects to a successful modernization approach. But the most important are:
1. Define Agility Vectors. Identify the top priorities for business agility and integrate relevant actions into all business projects. Here are some examples:
a. Radical improvement (time and cost) in response to legislative change
b. Generalization of existing capabilities to support new products and services
c. Dramatic reduction in new product time to market
d. Integration of existing capabilities to leverage disparate channels
e. Separation of common and customer/channel specific capabilities
I refer to these as “vectors”. Mission critical goals that will require actions and change right across the organization. Single projects are generally not going to cut it. Therefore the vectors provide a mechanism to exert influence (demand shaping) over the incoming application demand management pipeline and to select and coordinate multiple project actions.
2. Mandate Reference Architecture for Agility. Establish a reference architecture for business agility that defines the minimum necessary architecture compliance to ensure continuous business evolution. Mandate that all core business capabilities are implemented as software services and components.
3. Integrate Agile Architecture AND methods. Implement Agile practices that give equal weight to agile architecture and agile project delivery. Demonstrate small, incremental delivery steps, business capability by capability, service by service.
4. Govern business agility. Automate governance by establishing model driven architecture and development tooling that ensures compliance with the reference architecture.
5. Integrate Business and IT. Practice conceptual business modelling to establish common business and IT vocabulary independent of existing applications, align business and software services and reengineer the organization around business capabilities and services.
6. Get top level sponsorship for the Enterprise Modernization Roadmap. Recognize enterprise modernization as a major business priority and elevate to the highest levels of the enterprise to make it happen.

The enormous, disruptive creativity of Silicon Valley is transforming how companies make decisions, store data, reach potential customers, outsource activities, processes and capabilities, and how people communicate, make friends, protest and shop. No enterprise is immune from this effect.

Accordingly, modernization today means reinventing the way enterprises work, the business model and systems, and being genuinely agile. You only do this by ripping up today’s world and turning it into a genuinely flexible structure of independent components that can flex and morph continuously.

Application Modernization should be long dead and buried. Enterprise Modernization is an existential priority for all enterprises, not just those with mainframes and COBOL!

Note 1: Understanding Agile Adoption Failure

Friday, March 20, 2015

The Microservices Pattern

For those of us that have been practicing SOA for over a decade, it's surprising that there's so much interest in microservices. In fairness microservices don't look like the vendor play that was early SOA in the early noughties. But experienced SOA practitioners everywhere will be wondering if microservices is actually a good thing. You see microservices is basically an SOA pattern that inherits all the well-known SOA principles and adds characteristics that address the use of SOA for distributed, finer grained software services. And like all patterns, microservices are not applicable to all situations, and it's very important to understand the cost/benefit equation. Those folks that are heralding microservices as the "new SOA" or "the right way to do SOA" are flat wrong. Microservices is a specialization of SOA that has applicability to a relatively narrow problem space.

Componentized Services and Decentralized Data Management.

Capability based services that have reduced dependencies and single point responsibility for data has been a widely used SOA pattern. What's different with microservices is the decentralization of data management and encapsulation of the data in the service component. This is a useful pattern for services that can really own the data AND have high probability of churn in the service information model. The reduced horizon of change will be highly effective in responding to continuous business evolution.  But there's a serious cost to this, and Fowler et al surround the distributed data management advice with caveats.  They say, "Decentralizing responsibility for data across microservices has implications for managing updates. The common approach to dealing with updates has been to use transactions to guarantee consistency when updating multiple resources. . . . Using transactions like this helps with consistency, but imposes significant temporal coupling, which is problematic across multiple services. Distributed transactions are notoriously difficult to implement and . . . as a consequence microservice architectures emphasize transactionless coordination between services, with explicit recognition that consistency may only be eventual consistency and problems are dealt with by compensating operations."

Anyone who has dipped their toe in to this complex and murky pool knows that you do distributed data only when there is a real business requirement that demands this level of sophistication. In the typical enterprise environment there's a requirement for a range of SOA relevant data patterns. Distributed data is just one of many.  

Decentralized Governance

The vision of microservices is very reasonably to facilitate heterogeneous technology platforms. But the Fowler guidance goes much further. "Perhaps the apogee of decentralised governance is the build it / run it ethos popularised by Amazon. Teams are responsible for all aspects of the software they build including operating the software 24/7. Devolution of this level of responsibility is definitely not the norm but we do see more and more companies pushing responsibility to the development teams."
But you don't have to be a Luddite to think that there are elements of governance that need to be centralized; and I'll bet are standardized in Amazon. For example, at a basic level security, logging, reference data and return codes, contract and API meta data and data management (see above), life cycle management etc. But in our practice we also see massive advantages in standardization of much of the (platform independent) architecture runway, SOA patterns etc. The advantages are not just about productivity and quality, which are considerable. They also deliver consistency of approach that has many less tangible benefits in terms of skills and resources, knowledge sharing and integrity of the delivered solutions, while still supporting heterogeneous target platforms. Perhaps this demonstrates the divide between the architect and developer viewpoints. And I have seen far too many enterprises getting into deep water because they have allowed the pendulum to swing too far towards developer independence.  

The concept of microservices is clearly creating much interest and confusion. I commented on the Newman book in an earlier blog that the author didn't seem to understand the difference between a pattern and a process. And perhaps this is the issue with microservices. The concept is essentially about decentralization and distribution, creating freedom of action for developer led teams that deliver something useful for (probably) a narrowly defined set of users. It all looks good in terms of ticks in the "project delivered" box. But it also looks remarkably tactical. And as I commented in my recent blog, lack of consistency leads to inability to govern and increased time to market. And my guess is that microservices, in the way they have been defined, will lead down a very similar path.

Nonetheless, there are some useful aspects to microservices. DevOps specialists are seeing real benefits from smaller units of deployment. Promotion of some of the basic elements such as componentization, automation and evolutionary design are a good thing. But adopting the microservices characteristics as a unified pattern as described is really only applicable to a narrow problem space. And as soon as you adopt the characteristics piecemeal, you have to reassess the cost/benefit. I expect that the widespread interest in microservices will lead to it morphing into a simpler, less complex pattern that does address a wider problem space. But surprise, surprise, we solved that a long time ago, and all we are doing is renaming highly independent Capability based services as microservices!

References: Microservices, Lewis, Fowler, March 2014