Institutional Amnesia, Cargo Cults and Software Development

When George Santayana stated that “Those who cannot remember the past are condemned to repeat it.”, he wasn’t talking about technology. When Brenda Michelson and Ed Featherston said much the same thing recently, they were:

It’s a sad fact of life that today’s silver bullet is likely to be yesterday’s junk which was probably the day before yesterday’s silver bullet.

Poor design choices are made for a variety of reasons. Sometimes it’s a matter of ego. Sometimes inadequate analysis is the culprit. Focusing on technology rather than problem-solving can be another pitfall. Even attempts at post-hoc justification of a prior bad decision can drive new mistakes.

An uncritical acceptance of tradition is a significant source of problem designs. Eberhard Wolff recently took a swipe at one old standard:

The stock reason for a tiered/distributed design is scalability. However, it’s not a given that distributing X horizontal layers across Y machines (yielding X/Y instances) will yield better results than Y machines, each with all three layers deployed on the same machine. The context in which this sort of distribution makes sense is far from universal. Even when the costs of distribution are outweighed by the benefits, traditional monolithic horizontal layers will likely be less efficient than vertical slices. One of the purported benefits of microservices is the ability to independently scale according to business concerns (vertical slices organized around bounded contexts) rather technology concerns (horizontal layers).

The mention of microservices brings to mind the problem of jumping on bandwagons. How many applications currently under development are being designed using this architectural style because it’s the “next big thing” rather than because the style fits the problem? Sam Newman, author of O’Reilly’s Building Microservices, in “Microservices for Greenfield?”, even states that he considers the style to be more suitable for evolving an existing system rather than building from scratch:

I remain convinced that it is much easier to partition an existing, “brownfield” system than to do so up front with a new, greenfield system. You have more to work with. You have code you can examine, you can speak to people who use and maintain the system. You also know what ‘good’ looks like – you have a working system to change, making it easier for you to know when you may have got something wrong or been too aggressive in your decision making process.

You also have a system that is actually running. You understand how it operates, how it behaves in production. Decomposition into microservices can cause some nasty performance issues for example, but with a brownfield system you have a chance to establish a healthy baseline before making potentially performance-impacting changes.

I’m certainly not saying ‘never do microservices for greenfield’, but I am saying that the factors above lead me to conclude that you should be cautious. Only split around those boundaries that are very clear at the beginning, and keep the rest on the more monolithic side. This will also give you time to assess how how mature you are from an operational point of view – if you struggle to manage two services, managing 10 is going to be difficult.

This same over-eagerness is present in front-end development as much as back-end development. Stefan Tilkow recently tweeted regarding the trend of jumping straight into complex Javascript framework applications rather than evolving into them based on need:

In my opinion, the key to effective design is being able to give a good answer when asked “why”. Being able to articulate the reasons behind the choices made is critical to justifying them. By reasons, I mean a logical explanations of how the techniques chosen contribute to the desired ends. Neither “X recommends this” nor “This is what everybody’s doing” count. Designing, developing, and evolving software systems is not a game of following a recipe. In the words of Grady Booch:

Service Versioning Illustrated

Hogarth painting the muse

My last post, “No Structure Services”, generated some discussion on LinkedIn regarding service versioning and how an application’s architecture can enable exposing services that are well-defined, stable, internally simple and DRY. I’ve discussed these topics in the past: “Strict Versioning for Services – Applying the Open/Closed Principle” detailed the versioning process I use to design and maintain services that can evolve while maintaining backwards compatibility and “On the plane or in the plane?” covered how I decouple the service from the underlying implementation. Based on the discussion, I decided that some visuals would probably provide some additional clarity to the subject.

Note: The diagrams below are meant to simplify understanding of these two concepts (versioning and the structure to support it) and not be a 100% faithful representation of an application. If you look at them as a blueprint, rather than a conceptual outline, you’ll find a couple SRP violations, etc. Please ignore the nits and focus on the main ideas.

Internal API Diagram

In the beginning, there was an application consisting of a class named Greeter, which had the job of constructing a greeting for some named person from another person. A user interface was created to collect the necessary information from the end-user, pass it to Greeter and display the results. The input to the Greet method is an object of type GreetRequest, which has members identifying the sender and recipient. Greeter.Greet() returns a GreetResponse, the sole member of which is a string containing the Greeting.

And it was good (actually, it was Hello World which until recently was just a cheesy little sample program but is now worth boatloads of cash – should you find yourself using these diagrams to pitch something to a VC, sending me a cut would probably be good karma 😉 ).

At some point, the decision was made to make the core functionality available to external applications (where external is defined as client applications built and deployed separately from the component in question, regardless of whether the team responsible for the client is internal or external to the organization). If the internal API were exposed directly, the ability to change Greeter, GreetRequest and GreetResponse would be severely constrained. Evolving that functionality could easily lead to non-DRY code if backwards compatibility is a concern.

Note: Backwards compatibility is always a concern unless you’re ditching the existing client. The option is synchronized development and deployment which is slightly more painful than trimming your fingernails with a chainsaw – definitely not recommended.

The alternative is to create a facade/adapter class (GreetingsService) along with complementary message classes (GreetingRequest and GreetingResponse) that can serve as the published interface. The GreetingsService exists to receive the GreetingRequest, manage its transformation to a GreetRequest, delegate to Greeter and manage the transformation of the GreetResponse into a GreetingResponse which is returned to the caller (this is an example of the SRP problem I mentioned above, in actual practice, some of those tasks would be handled by other classes external to GreetingsService – an example can be found here).

Internal API with External Service Adapter Diagram

Later, someone decided that the application should have multilingual capability. Wouldn’t it be cool if you could choose between “Hello William, from your friend Gene” and “Hola Guillermo, de su amigo Eugenio”? The question, however, is how to enable this without breaking clients using GreetingsService. The answer is to add the Language property to the GreetRequest (Language being of the GreetingLanguage enumeration type) and making the default value of Language be English. We can now create GreetingsServiceV1 which does everything GreetingsService does (substituting GreetingRequestV1 and GreetingResponseV1 for GreetingRequest and GreetingResponse) and adds the new language capability. The result is like this:

Internal API with External Service Adapters (2 versions) Diagram

Because Language defaults to English, there’s no need to modify GreetingsService at all. It should continue to work as-is and its clients will continue to receive the same results. The same type of results can be obtained using a loose versioning scheme (additions, which should be ignored by existing clients, are okay; you only have to add a new version if the change is something that would break the interface, like a deletion). The “can” and “should” raise flags for me – I have control issues (which is incredibly useful when you support published services).

Control is the best reason for preferring a strict versioning scheme. If, for example, we wanted to change the default language to Spanish going forward while maintaining backward compatibility, we could not do that under a loose regime without introducing a lot of kludgy complexity. With the strict scheme, it would be trivial (just change the default on GreetingRequestV1 to Spanish and you’re done). With the strict scheme I can even retire the GreetingService once GreetingServiceV1 is operational and the old clients have had a chance to migrate to the new version.

Our last illustration is just to reinforce what’s been said above. This time a property has been added to control the number of times the greeting is generated. GreetingsServiceV2 and its messages support that and all prior functionality, while GreetingsService and GreetingsServiceV1 are unchanged.

Internal API with External Service Adapters (3 versions) Diagram

As noted above, being well-defined, stable, internally simple and DRY are all positive attributes for published services. A strict versioning scheme provides those attributes and control over what versions are available.

A Service by Any Other Name

Romeo and Juliet - balcony scene

I remember when reuse was the Holy Grail. First it was object-oriented languages, then object modeling, then components, then services. While none of these has lived up to the promise of rampant reuse, one thing has – language. We have learned to overload and reuse terms to the point that most are no more descriptive than using the word “thing”. “Service” is one of these.

The OASIS Reference Model for Service Oriented Architecture 1.0 defines a service as “…a mechanism to enable access to one or more capabilities, where the access is provided using a prescribed interface and is exercised consistent with constraints and policies as specified by the service description”. This definition includes nothing about protocol, media types, messaging patterns, etc. Essentially, this definition applies to anything that exposes something to consumers over in a defined interface in a defined manner.

Well, that’s helpful. It doesn’t even resolve whether it’s referring to the application providing services or the specific endpoints exposed by that application. In the context of Domain-Driven Design, a service may even be share the same process with its client.

Some services are meant to be interactive. A request is made and a response is returned. Such a service is extremely useful when the response is being presented to an actual human user in response to some action of theirs. This immediate gratification provides an excellent user experience provided latency is minimized. When interactive services are composed within another interactive service, this latency burden quickly increases as the remote client can’t regain control until the service regains it from each remote service it’s called (barring a timeout).

Some services are meant to work asynchronously. These work well particularly well in system to system scenarios when there’s no need to for temporal coupling. A significant trade-off for this model is the additional complexity involved, particularly around error condition feedback.

Some services (typically SOAP-based) are meant to receive and return highly structured and well-defined messages invoking tasks to be performed. This works extremely well for many system to system communications. Others (typically RESTful services) provide more of a variation of media types which are dealt with using CRUD operations. These work particularly well when the client is mainly presenting the response (perhaps with some minimal transformation) to an end user. If the messages are less well-defined, then the level of client complexity increases. Services using well-defined messages that are exposed externally will typically have different versioning requirements than services meant for consumption by internal clients (where “internal” is defined as built and deployed contemporaneously with the service).

The points behind this litany of service definitions and usage patterns? Different styles are appropriate to different situations and precision in communication is important to avoid conflating those styles.

Providing functionality via a service, regardless of the type of service, is not sufficient to meet a need. Functionality should be exposed via the flavor of service that corresponds to the needs of the client. Otherwise, the client may incur more effort and complexity dealing with the mismatch than the functionality is worth.

The concept of a message-oriented API for the back-end allows it to meet all of these needs without violating the DRY principle. Just like UI components, service endpoints (SOAP or REST style) should not contain domain logic, but delegate to domain services. As such, this provides a thin layer primarily concerned with translation between the format and messaging pattern required externally and that required by the domain services. This allows internal consumers (again, where “internal” is defined as built and deployed contemporaneously with the back-end) to work either directly in-process with domain services or remotely via a very thin shim that retains the same message structure and solely provides the network communication capabilities. External consumers should have their own endpoints (perhaps even separate sites) that cater to their needs.

Having the thinnest possible service layer not only prevents duplication of logic but also lessens the burden of standing up new endpoints. Lowering the cost of an endpoint makes it easier to justify providing tailored APIs. APIs that are tailored to specific client types are simpler to consume, further reducing costs.

In my last post, I asked “do you need a service layer?” The answer remains, “it depends”. But now there’s a new wrinkle, “if you need a service layer, does it need to be a remote one?”

Fears for Tiers – Do You Need a Service Layer?

Tiered Wedding Cake

One of the perils of popularity (at least in technology) is that some people equate popularity with efficacy. Everyone’s using this everywhere, so it must be great for everything!

Actually, not so much.

No one, to my knowledge, has created the secret sauce that makes everything better with no trade-offs or side effects. Context still rules. Martin Fowler recently published “Microservices and the First Law of Distributed Objects”, which touches on this principle. In it, Fowler refers to what he calls the First Law of Distributed Object Design: “don’t distribute your objects”. To make a long story short, distributed objects are a very bad idea because object interfaces tend to be fine-grained and fine-grained interfaces perform poorly in a distributed environment. “Chunkier” interfaces are more appropriate to distributed scenarios due to the difference in context between in-process and out of process communication (particularly when out of process also crosses machine, even network boundaries). Additionally, distributed architectures introduce complexity, adding another contextual element to be accounted for when evaluating whether to use them.

In his post, under “Further Readings”, Fowler references an older post of his on Dr. Dobb’s titled “Errant Architectures” (a re-packaging of Chapter 7 of his book Patterns of Enterprise Application Architecture). In that, he discusses encountering what was a common architectural anti-pattern of the time (early 2000s):

There’s a recurring presentation I used to see two or three times a year during design reviews. Proudly, the system architect of a new OO system lays out his plan for a new distributed object system—let’s pretend it’s some kind of ordering system. He shows me a design that looks rather like “Architect’s Dream, Developer’s Nightmare” with separate remote objects for customers, orders, products and deliveries. Each one is a separate component that can be placed in a separate processing node.
I ask, “Why do you do this?”

“Performance, of course,” the architect replies, looking at me a little oddly. “We can run each component on a separate box. If one component gets too busy, we add extra boxes for it so we can load-balance our application.” The look is now curious, as if he wonders if I really know anything about real distributed object stuff at all.

The quintessential example of this style was the web site presentation layer with its business and data layer behind a set of web services. Particularly in the .Net world, web services were the cutting edge and everyone needed them. Of course the system architect in the story was confusing scalability for performance (as were most who jumped onto the web service layer bandwagon). In order to increase the former, a hit is taken to the latter. In most cases, this hit is entirely unnecessary. A web application with an in-process back-end can be load-balanced much more simply than separate UI and service sites, without suffering the performance penalty of remote communication.

There are valid use cases for a service layer, such as when an application provides a both an interactive user interface and is service-enabled. When there are multiple user interfaces, some front ends will benefit from physical separation from the back-end (native mobile apps, desktop clients, SharePoint web parts, etc.). Applications can be structured to accommodate the same back-end either in-process or out of process. This structure can be particularly important for applications that have both internal (where internal is defined as built and deployed simultaneously with the back-end) and external service clients as these have different needs in terms of versioning. Wrapping the back-end with a service layer rather than allowing it to invade a particular service implementation can allow one back-end to serve internal and external customers either directly or via services (RESTful and/or SOAP) without violating the DRY principle.

Many of the same caveats that apply to composite applications formed from microservices (network latency, serialization costs, etc.) apply to these types of applications. It makes little sense to take on these downsides in the absence of a clear demonstrable need. Doing so looks more like falling prey to a fad than creating a well thought out design.

[Wedding Cake Image by shine oa via Wikimedia Commons.]

Organizing an Application – Layering, Slicing, or Dicing?

stump cut to show wood grain

How did you choose the architecture for your last greenfield product?

Perhaps a better question is did you consciously choose the architecture of your last greenfield product?

When I tweeted an announcement of my previous post, “Accidental Architecture”, I received a couple of replies from Simon Brown:

While I tend to use layers in my designs, Simon’s observation is definitely on point. Purposely using a particular architectural style is a far different thing than using that style “just because”. Understanding the design considerations that drove a particular set of architectural choices can be extremely useful in making sure the design is worked within rather than around. This understanding is, of course, impossible, if there was no consideration involved.

Structure is fundamental to the architecture of an application, existing as both logical relationships between modules (typically classes) and the packaging of those modules into executable components. Packaging provides stronger constraint of relationships. It’s easier to break a convention that classes in namespace A doesn’t use those in namespace C except via classes in namespace B if they’re all in the same package. Packaged separately, constraints on the visibility of classes can provide an extra layer of enforcement. Packaging also affects deployment, dependency management, and other capabilities. For developers, the package structure of an application is probably the most visible aspect of the application’s architecture.

Various partitioning strategies exists. Many choose one that reflects a horizontally layered design, with one or more packages per layer. Some, such as Jimmy Bogard, prefer a single package strategy. Simon Brown, however, has been advocating a vertically sliced style that he calls “architecturally -evident”, where the packaging reflects a bounded context and the layering is internal. Johannes Brodwall is another prominent proponent of this partitioning strategy.

The all in one strategy is, in my opinion, a limited one. Because so many of the of the products I’ve worked on have evolved to include service interfaces (often as separate sites), I favor keeping the back-end separate from the front as a rule. While a single package application could be refactored to tease it apart when necessary, architectural refactoring can be a much more involved process than code refactoring. With only soft limits in both the horizontal and vertical dimensions, it’s likely that the overall design will become muddled as the application grows. Both the horizontal and the vertical partitioning strategies allow for greater control over component relationships.

Determining the optimal partitioning strategy will involve understanding what goals are most important and what scenarios are most likely. Horizontal partitions promote adherence to logical layering rules (e.g. the UI does not make use of data access except via the business layer) and can be used for tiered deployments where the front-end and back-end are on different machines. Horizontal layers are also useful for dynamically configuring dependencies (e.g. swappable persistence layers). Vertical partitions promote semantic cohesion by providing hard contextual boundaries. Vertical partitioning enables easier architectural refactoring from a monolithic structure to a distributed one built around microservices.

Another option would be to combine layering with slicing – dicing, if you will. This technique would allow you to combine the benefits of both approaches, albeit with greater complexity. There is also the danger of weakening the contextual cohesion when layering a vertical slice. The common caution (at least in the .Net world) of harming performance seems to be more an issue during coding and builds rather than at run time.

As with most architectural decisions, the answer to which partitioning scheme is best is “it depends”. Knowing what you want and the priority of those wants in relation to each other is vitally important. You won’t be able to answer “The Most Important Question” otherwise.

On the plane or in the plane?

…I’m getting IN the plane! IN the plane! Let Evil Knievel get ON the plane! I’ll be in here with you folks in uniform! There seems to be less WIND in here!
(George Carlin commenting on airport announcements)

Words have meaning, but we sometimes use them in a casual manner. George Carlin made a career pointing out absurdities from casual usage. Likewise, lawyers have good days or bad days depending on the precision or lack of precision in the use of language. A recent article on TechRepublic caught my eye for that same reason: if “Poll: How much of your logic is in services?” is taken literally, there’s a huge problem.

Having your business logic “in” services as opposed to “behind” services means you’ve either limited your flexibility or you will violate the “Don’t Repeat Yourself” (DRY) principle. The principle of interoperability that underlies service orientation is potentially impaired if the application logic is tightly bound to the communication method that exposes it. Last month, Davy Brion complained about the use of WCF services as an intermediary between a web front end and the back-end of the application. He identified the performance impacts as well as the increased complexity of both development and deployment. However, if your non-UI logic is inseparable from the service itself, you cannot avoid this without redundant code. The only way to expose functionality via multiple methods (e.g. REST and SOAP services, direct connection, message queues, etc.) when working in this manner is to duplicate the functionality for each method – not an ideal situation.

A more flexible architecture can be achieved using a message-oriented business layer that can be wrapped by one or more services or consumed directly. Internal clients that are deployed concurrently with the back-end can use the “native” message format, either by directly referencing the business layer (for a web application) or through a service facade (for Smart Clients, SharePoint web parts, etc) as may be appropriate. External clients can be handled via strictly versioned services that translate to and from the canonical format. This strategy allows not only controlled versioning, but also the ability to provide multiple endpoints for a unified code base. Having only one version of business logic should yield a far more robust system than one where the same business task is implemented multiple times.

Layered Architectures – Sculpting the Big Ball of Mud

The notion of SHEARING LAYERS is one of the centerpieces of Brand’s How Buildings Learn [Brand 1994]. Brand, in turn synthesized his ideas from a variety of sources, including British designer Frank Duffy, and ecologist R. V. O’Neill.

Brand quotes Duffy as saying: “Our basic argument is that there isn’t any such thing as a building. A building properly conceived is several layers of longevity of built components”.

Brand distilled Duffy’s proposed layers into these six: Site, Structure, Skin, Services, Space Plan, and Stuff. Site is geographical setting. Structure is the load bearing elements, such as the foundation and skeleton. Skin is the exterior surface, such as siding and windows. Services are the circulatory and nervous systems of a building, such as its heating plant, wiring, and plumbing. The Space Plan includes walls, flooring, and ceilings. Stuff includes lamps, chairs, appliances, bulletin boards, and paintings.

These layers change at different rates. Site, they say, is eternal. Structure may last from 30 to 300 years. Skin lasts for around 20 years, as it responds to the elements, and to the whims of fashion. Services succumb to wear and technical obsolescence more quickly, in 7 to 15 years. Commercial Space Plans may turn over every 3 years. Stuff, is, of course, subject to unrelenting flux [Brand 1994].

One of the first treatments of application architecture and design patterns that I ever read was the Foote and Yoder classic “Big Ball of Mud”, from which the quote above comes. It, along with some unsavory characters on the VISBAS-L mailing list, fed my growing interest in the discipline of software architecture. Like many, I at first thought of it as just an anti-pattern. However, as the authors noted:

Some of these patterns might appear at first to be antipatterns [Brown et al. 1998] or straw men, but they are not, at least in the customary sense. Instead, they seek to examine the gap between what we preach and what we practice.

This was an eye-opener. In order to build (and maintain) good systems, one needed to understand how dysfunctional systems evolved. A poorly designed system obviously leads to trouble. Failure to manage change is just as dangerous. Quoting again from “Big Ball of Mud”:

Even systems with well-defined architectures are prone to structural erosion. The relentless onslaught of changing requirements that any successful system attracts can gradually undermine its structure. Systems that were once tidy become overgrown as PIECEMEAL GROWTH gradually allows elements of the system to sprawl in an uncontrolled fashion.

If such sprawl continues unabated, the structure of the system can become so badly compromised that it must be abandoned. As with a decaying neighborhood, a downward spiral ensues. Since the system becomes harder and harder to understand, maintenance becomes more expensive, and more difficult. Good programmers refuse to work there.

This understanding of the danger of chaotic system evolution, coupled with Brand’s notion of Shearing Layers, points the way to avoiding the Big Ball of Mud pattern. Structuring system designs using the principle of separation of concerns into cohesive layers that communicate in a disciplined manner, AKA Layered Architecture, can be used to prevent and/or correct system decay. Ideally, the initial design of a system would incorporate these principles, but it is even more important that they be used to manage change as the system evolves.

There are many variations on the theme, such as Alistair Cockburn’s Hexagonal Architecture, Jeffrey Palermo’s Onion Architecture, and Microsoft’s Layered Application Guidelines, to name just a few. My own style (to be covered in a future post) is similar to the Microsoft model, with some differences. All share the common features of separating presentation, business (process), and data access logic.

Using a layered approach has become increasingly important over the years as the scope of applications has expanded. Applications that were once just a web site fronting a database have expanded to include a variety of additional front ends such as smart clients, web parts, mobile sites, and apps (often for multiple OSs), as well as services for use by third parties. Additionally, many applications are dependent on not only their own data store, but also integrate with other systems as well. A layered approach allows for managing this component proliferation while minimizing redundancy.

Some additional advantages to structuring an application in this manner are:

  • Promoting flexibility in deployment: Components grouped in logical layers can be composed in different physical tiers based on the needs of the situation. For example, a web application may combine all layers on one tier (data persistence, of course, still residing on a separate physical tier). A SharePoint web part, smart client, or the mobile apps may be distributed across multiple tiers (business and data access, exposed via a service facade, sharing one physical tier).
  • Enabling dependency injection: Layers provide an excellent point for making use of inversion of control. For example, the business layer could make use of any one of multiple data access layer implementations (based on the underlying database product) in a manner transparent to it, so long as those implementations shared the same interfaces.
  • Enhancing unit testing: The ability to unit test layers is similarly enhanced in that mock objects can be injected to replace dependencies of the layer being tested.

Just as you wouldn’t buy a house that needed to be demolished in order to change the furniture, you shouldn’t be stuck with a system that must be virtually re-written in order to make relatively modest changes. Change happens; architecture should facilitate that.