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My last post explored some distinguishing characteristics of three common architectural styles in an attempt to understand better how they differ and therefore how they may apply in different contexts. A fourth distinguishing characteristic of these architectural styles is the way in which state is managed during the execution of a business process.

There are three aspects of state that I want to consider:

• Management – how state change is initiated or managed through a business process.
• Monitoring – how state is monitored or accessed or derived during the execution of a business process.
• Consistency – how state is made consistent across different systems involved in a business process.

A summary of the state characteristics of the different architectural styles is listed in the following table along with the other characteristics discussed in my last post.

In EAI, state is managed within one application and then synchronised to other applications, usually after the business process has completed. This means that in some cases state may be inconsistent across the organisation or its systems. That may or may not be a problem (see ‘Eventually Consistent‘) but is a common side effect when a business process is executed within one system rather than across systems in an independent process layer. During the execution of an EAI process, there is often no monitoring of the state. I.e. the process may simply replicate data changes to other systems without explicily tracking state. A limited form of state monitoring may exist in the sense that the local application or associated middleware may check the status of data synchronization and error out in the event of an exception. I refer to this as ‘local’ state monitoring. So under the EAI architectural style, state is managed locally, monitored locally (if at all) and is eventually consistent.

Under SOA, the driver of a business process is BPM orchestration in an independent process layer. In this case, we can say that state is managed centrally (in the BPM layer) and monitored centrally (also in the BPM layer). State in end-systems is updated progressively through the business process (via service calls) and so we could say that state is ‘progressively’ consistent as opposed to ‘eventually’ consistent.

Under EDA, there is no central or even local management of state. Instead, events signify distributed actions which together may be used to infer the state of a system. To the extent that any ‘management’ occurs, we could say that state is managed in a distributed fashion – one or more agents each acting on their own. Perhaps  it is more accurate to say that state is manifested globally. Converesely, state is monitored centrally within an Event Processing (CEP) layer which correlates events to infer system state. Under EDA, state is progressively consistent because the system is progressively reacting to events which are a by-product of a hidden or implicit business process.

I’ve recently been thinking about simple ways to characterise the different architectural approaches we use in distributed systems today. Three simple architectural characteristics I have come up with are:

• Asset – this is a core capability or “thing” that must be built, procured, maintained and managed in a corporate IT “inventory”.
• Element – these are the “atomic” building blocks used in the process of Composition.
• Composition – this is the mechanism which allows the different assets to work together to support a business requirement.

If we apply these characteristics to three common architectural approaches then we get the results in the following table.

EAI, although  unfashionable is still prevalent – even dominant in the industry. For EAI, we are primarily concerned with applications (usually COTS) which embody and support the requirements of different parts of the business. Multiple applications must be coordinated to support the whole business. The primary coordination mechanism under EAI is synchronization of state between the different applications – primarily via data integration. The composition element is the API.

SOA is characterised by Services as the key asset. Services are acquired or built to execute business operations. Elemental Services are composed to support business processes – a sequence of operations which results in a business outcome. BPM (or process orchestration) is the composition mechanism within SOA. The underlying functionality of a Service may reside in one or more applications, but from an SOA perspective this is of secondary importance…SOA is concerned with the Service, not necessarily its implementation.

EDA (Event Driven Architecture) is characterised by Event Services as the key asset which represent an asynchronous notification of an important event associated with the business. Elemental Events are correlated and further processed to derive higher-order business intelligence which may in turn trigger other Events. The primary composition mechanism within EDA is Event Processing (or CEP). An important part of this composition mechanism is the ability to manage or track system state.

This characterization gives more clarity to the difference between JABOWS and true SOA. Many so-called SOA projects have simply involved the “bottom up” exposure of application APIs using web-services standards – resulting in “Just a Bunch of Web Services” which don’t realise the business value of a true SOA. JABOWS is EAI because the applications are the core “asset”. A true SOA has a “top down” process-centric architecture with Services as the core asset.

Happy New Year! Asynchronicity is busting out all over the web and my prediction is that 2010 will be the year of “events”:

• Of course Twitter has brought The concept of publish/subscribe messaging to the masses and we enjoyed their journey of discovery to the heights of scalability in 2009.
• XMPP has been embraced by the real-time web crowd, most publicly in Google Wave but also in other “back-web” contexts such as Gnip.
• Web sockets is an experimental feature of HTML 5 which enables push messages directly to web pages.
• New frameworks for event-driven programming are emerging such as EventMachine, Twisted, Node.js.
• In 2009 every major software vendor had a CEP product.

In the meantime, SOA has become so damn synchronous. But it doesn’t have to be!

One of the fundamental tennets of SOA is that reducing coupling between systems makes them more scalable, reliable and agile (easier to change). SOA goes a long way to reducing coupling by providing a contract-based, platform independent mechanism for service providers and consumers to cooperate. However I still think we can improve on current SOA practices in further reducing coupling.

Coupling still intrudes into many aspects of how SOA is practiced today:

• HTTP transports tie us to a regimen of synchronous request-reply with timeouts which creates tight couplings between provider and consumer. Even though one-way MEPs were an original feature of SOAP, message-oriented transports remain the forgotten orphan of web-services standards.
• Many SOA services are conceived, implemented and maintained as point-to-point entities…providers and consumers forced into lock-step due to inadequate versioning and lifecycle management.
• Process orchestration layers often form a bridge between service providers and consumers, which on the face of it provides some level of indirection. But in many cases orchestration provides limited value and may actually serve to increase the overall system coupling.

In many cases we can achieve the benefits of service orientation to much greater effect by exercising a little scepticism toward some of these shibboleths of the web services world and embracing a more asynchronous, event-oriented way of building processes. So this year, embrace your asynchronous side and do something to reduce your system coupling: build some pub/sub services, learn about Event Processing or Event-Driven Architecture, try one of the technologies I pointed to above.

Just as developers should embrace multiple languages to broaden their skills, so should architects embrace and be fluent in multiple architectural styles.

In a recent comment on my Architectural Characteristics posts, Andy astutely observes that I may be “shoe-horning”. By this I assume he means that I’m taking a large and rather lumpy concept and trying to squeeze it into a smaller and more uniformly shaped container while risking some distortion in the process. I’ll admit that in this respect I’m probably guilty as charged.

But I should clarify my purpose in doing this. I’m trying to cut back the various architectural styles under consideration to a simpler form where the essential characteristics can be discerned without confusion from some other non-essential characteristics. So rather than shoehorning, I’m trying to setup a strawman model which can be used as a starting point for discussion. Or maybe like a physicist I’m trying to model a very complex phenomenon using linear approximations which explain the broad outlines of the phenomenon at the risk of falling short on some of the details.

To extend this latter metaphor, I don’t think it is too much of a stretch to say that the architectural styles I’m considering could be likened to “fundamental” architectural styles and that real-world architectures could be viewed as “superpositions” of those fundamental architectures.

If we consider the simplified forms of EAI and SOA that I describe, each style falls short of representing a real world architecture, but the upside is that the EAI and SOA styles as I describe them are distinct and easily differentiated. So we have a model which provides a way of distinguishing between different styles (via the characteristics I’ve discussed) but falls short of exactly matching a “real-world” architecure.

If we look at any real-world architecture in recent years, I think we can see a superposition of EAI and SOA concepts. This probably reflects an evolutionary path between the two styles. EAI as practiced in the early noughties had already developed the idea of a normalised data model and technology independent interfaces. These were not standardized, but some of the characteristics of SOA were apparent in what was then called EAI.

Similarly, EAI was not always about data integration. There was (and is) a distinction between data integration and process integration. EAI techniques could be used to orchestrate processes across multiple systems. This is even closer to the concept of SOA which has at its core the notion of an independent process layer seperate from the service layer.

Even if we don’t superpose EAI and SOA into one solution, there are still legitimate ways in which EAI, SOA and EDA coexist within any particular architecture. We can easily imagine a solution in which a business process is orchestrated via SOA services, reference data is synchronised using EAI and overall process state is monitored using EDA techniques such as Event Processing.

So real-world solution architectures exhibit some overlap between the different architectural styles – EAI, SOA and EDA. Some of this is due to evolutionary legacies, or due to plain-old confusion between the different styles (e.g. JABOWS as really being EAI). Some of it is also due to legitimate mixing of different styles for different aspects of a solution.

I think that real-world architectures can benefit from seperating out the “essence” of each architectural style and being explicit about how those styles are being applied. Reducing architectural styles to simplified forms clarifies the stucture of a real-world architecture. Not very different from Design Patterns, really.