Space-Based Architecture (or SBA for short) just might be in your future if your building large-scale distributed systems. By focusing on high-throughput and low latency, SBA joins messaging and in-memory data caching and adds a good measure of load partitioning. However, with the entire industry enamoured with SOA, what place is left for SBA?

Before going too far ahead, you might want to take a look at my previous post “Space-Based Architectural Thinking, or listen to my podcast Space-Based Architecture for the Web. There’s also a 30 minute webcast online describing SBA more fully here. I’m also going to try to stay away from things concerning Jini this time after already discussing the connection between Jini and SOA, and the tradeoffs between two general approaches: Tasks and Spaces vs Message and Handlers.

OK, so the issue of state-management is a big one. Everybody wants to work stateless, because it scales. The only problem is that the business processes that we are automating are long running, meaning that there are external systems or people involved. This makes these processes inherently stateful. So, we need a way to scale statefully – SBA gives us that. For some background on the “Shared Nothing Architecture”, I suggest reading this post on inter-process SOA and this one as well.

Availability also has to be handled, not only in terms of having enough servers online to handle the required load but in having all the data required to process each request be accessible. This has often been handled by the database using ACID transactions – durability being that which solved availability issues, but also hurting latency the most. The problem with saving the state of our long-running business processes/workflows in the database is the load and the responsiveness requirements. In many verticals – telcos, financial, and defense to name a few, we need millisecond level latency on each stage of the workflow. This is what leads SBA to the in-memory, replicated data grid.

Note that SBA only intends to take these workflows out of the database, and not anything else – especially not Master Data. The lifetime of these workflows is incredibly short compared to that of master data like customers and products. It will have much different backup strategies as well. In terms of load, these workflows will be heavy on reads and writes together in the same transactions, but quite low in terms of just reads. If we have workflows that perform work in parallel, we easily end up with concurrency requirements that make DBAs cringe under the barrage of short transactions.

If you’re worried that Workflow Foundation (WF) won’t scale because of the above, you needn’t be. You can (more or less easily) replace the persistence mechanism of WF with your own, saving your workflow instances to an in-memory replicated data grid.

By enabling the objects in the grid to call back into logic on your servers, you have, in essence, done messaging and more. The added benefit that SBA receives from this is a unification of technology between caching and messaging. This translates directly to savings when it comes time to cluster each of those technology’s environments.

Finally, if we can find an attribute in the incoming stream of messages that creates a nice even distribution, we can then partition our load between our servers by that key. This will work up to the point where the load per key increases beyond a single server’s capacity, and then we have to look at re-partitioning, a non-trivial problem. However, if we put objects in our grid that represent the master data, and tie them to our workflow instances with both of those tied to the key of our load, a smart infrastructure can make sure all that data is already resident on the server that is handling that piece of the load. That decreases latency even more since we no longer have to pay network roundtrips to collect all the data needed before we can process it. That’s a substantial advantage for the above verticals.

But all of this has nothing to do with SOA.

Sure, it’ll change how we implement our Services internally, but it has no impact on their interfaces or the top-level service decomposition. In the Java community, the word “service” is often used to describe the logic of a system. Great significance is placed on keeping these “services” simple, as in Plain-Old Java Objects. The fact of the matter is that the logic of the system should be simple and independent of other concerns like data access and communcations (a la Web Services), but that does not make it a service, not in the SOA sense.

For more information on what Services in SOA are like, check out this podcast on Business and Autonomous Components in SOA. Actually, SBA will probably have the biggest impact on the way autonomous components will handle service-level agreements.

So, it appears that even with SOA, SBA has its place. The former dealing with business level agility, the latter dealing with all the technical aspects of supporting that agility. If you’re tasked with the designing the architecture of a scalable, available, high-throughput, low-latency distributed system, I’d strongly advise you to look at SBA – the technical value is overwhelming. Even if you don’t utilize all elements of SBA and choose the Master Worker Pattern instead of load partitioning, you’ll find the technologies supporting SBA to be quite flexible in that respect.

Will Space-Based Architectures be a part of your future? I don’t know for sure, but they’re a most welcome part of my present.

If you’ve read Scott Hanselman’s great post Some guiding principles for Software Development, you’ve probably seen his point about “Fewer assemblies is better”, and might be thinking that you’ve seen me write about this before. If so, you’re absolutely right.

Here are some choice quotes:

In the end, you should see bunches of projects/dlls which go together, while between the bunches there is almost no dependence whatsoever. The boundaries between bunches will almost always be an interface project/dll.

This will have the pleasant side-effect of enabling concurrent development of bunches with developers hardly ever stepping on each other’s toes. Actually, the number of projects in a given developer’s solution will probably decrease, since they no longer have to deal with all parts of the system.

Taken from So many Dlls, so little time.

And from a more recent post, One wrong DLL = 3 months gone:

Obviously, if there is less source to go through, the programmer will, on average, find the origin of the defect faster. And, as we all know, it usually takes longer to find the bug than to actually fix it.

So, by splitting up different classes and interfaces into different DLLs, we can manage dependencies in the system so that less source needs to be examined.

However, if you did want to roll up all these DLLs into fewer physical files, you could do just that using the tool ILMerge. This might make sense as a part of getting your software ready for installation. Also, access to client computers that are having problems might make you consider this.

Bottom Line

I’d say more assemblies is generally better, and merge when necessary – but don’t change your design on that account.

So you’re code threw an exception for some reason. Now, your WF workflow gets terminated. You’re not a happy camper. You go looking for help and find this practical set of solutions, but think to yourself “it shouldn’t be this hard”.

And you’re absolutely right.

The fact of the matter is, you don’t have to do anything special to deal with failures in workflow. It all can be handled in terms of messaging, since the only interesting kind of workflow is the “long-running” kind. Long running workflows are those that may involve calling out to other services/systems, or involve humans in the process. Conversely, “short-running” workflows involve receiving a single message, handling it by calling code on the same server, in the same process, and on the same thread, and possibly returning a response. Simple request/response interaction is short-running. Things you might think to use BizTalk for would probably be long-running.

Take a look at this post which shows that long-running workflow is just regular messaging with a sprinkle of state-management.

Anyway, in my article describing failure handling for messaging, these workflow failures fall under the following category and solution:

Other kinds of failure conditions include having our DB transactions fail because they were chosen as the victim of a deadlock. The appropriate system level error handling is to just retry the transaction a bit later. Once again, if we were using our queues within the context of a transaction scope that included that of the database, the message would return to the queue when that deadlock exception bubbled through. This is exactly the behavior that we want in this case, although having the message go to the end of the queue instead of the front would also be just fine.

Other kinds of failure conditions we might run into include things like unique-constraint violations, attempting to perform actions on entities that no longer exist, and other activities where trying them over again probably won’t yield any different behavior. In these cases, if an exception were to cause the perpetrating message to return to the input queue we’d get exactly the wrong behavior. At the very least we would want to maybe log the exception information

So, in some cases, it makes perfect sense for the workflow to let the exception bubble through. Not so that the workflow will be terminated, but rather that the message which triggered it would be tried again. You can configure Workflow Foundation to have this behavior as well, or so I’ve been told.

Now you’re happy, the problem’s been solved for you – by design. No need to go mucking around in the nooks and crannys of FaultHandlers, CallExternalMethodActivity, and hacking the InsertWorkflow stored procedure.

Clean, Correct, and Simple – courtesy of The Software Simplist.

Additional References:

• Ron Jacobs interviews me on SOA and Workflow
• A conversation on Workflow Foundation and Service Orientation

It appears that something of a consensus has been reached on the issue of Entity Services. So far I’ve been against them, describing them as a Common SOA Pitfall, among other things. Roger Wolter from Microsoft (and one of the brains behind SQL Service Broker) has also called out against them from a data perspective. But the recent back-and-forth I had with the pragmatic Nick Malik, from Microsoft’s Enterprise Architecture Group clinched it. Jack van Hoof also seems to be in agreement.

Entity Services are in the Application Architecture domain.
They are not a member of the Services which are the primary unit of decomposition of SOA.

An SOA Service may be implemented using Entity Services, or not. If so, those Entity Services are not allowed to be accessed outside that SOA Service’s boundary. As such, they are an implementation detail of SOA. In which case we can have very interesting discussions about the relative value of Entity Services over things like the Domain Model Pattern.

So, as Jack said: “No, entity services are not an anti-pattern.”

However, when you’re going to decide on the main Services that are going to be a part of your SOA, those Entity Services don’t belong there.

For more information, take a look at my article from the Microsoft Architecture Journal, only partially available by virtue of the Wayback Machine: Autonomous Services and Enterprise Entity Aggregation

Some Technical Difficulties

Ayende and I had an email conversation that started with me asking what would happen if I added an Order to a Customer’s “Orders” collection, when that collection was lazy loaded. My question was whether the addition of an element would result in NHibernate hitting the database to fill that collection. His answer was a simple “yes”. In the case where a customer can have many (millions) of Orders, that’s just not a feasible solution. The technical solution was simple – just define the Orders collection on the Customer as “inverse=true”, and then to save a new Order, just write:

Although it works, it’s not “DDD compliant” 🙂

In Ayende’s post Architecting for Performance he quoted a part of our email conversation. The conclusion I reached was that in order to design performant domain models, you need to know the kinds of data volumes you’re dealing with. It affects both internals and the API of the model – when can you assume cascade, and when not. It’s important to make these kinds of things explicit in the Domain Model’s API.

How do you make “transparent persistence” explicit?

The problem occurs around “transparent persistence”. If we were to assume that the Customer object added the Order object to its Orders collection, then we wouldn’t have to explicitly save orders it creates, so we would write service layer code like this:

On the other hand, if we designed our Domain Model around the million orders constraint, we would need to explicitly save the order, so we would write service layer code like this:

But the question remains, how do we communicate these guidelines to service layer developers from the Domain Model? There are a number of ways, but it’s important to decide on one and use it consistently. Performance and correctness require it.

Solution 1: Explicitness via Return Type

The first way is a little subtle, but you can do it with the return type of the “CreateOrder” method call. In the case where the Domain Model wishes to communicate that it handles transparent persistence by itself, have the method return “void”. Where the Domain Model wishes to communicate that it will not handle transparent persistence, have the method return the Order object created.

Another way to communicate the fact that an Order has been created that needs to be saved is with events. There are two sub-ways to do so:

Solution 2: Explicitness via Events on Domain Objects

The first is to just define the event on the customer object and have the service layer subscribe to it. It’s pretty clear that when the service layer receives a “OrderCreatedThatRequiresSaving” event, it should save the order passed in the event arguments.

The second realizes that the call to the customer object may come from some other domain object and that the service layer doesn’t necessarily know what can happen as the result of calling some method on the aggregate root. The change of state as the result of that method call may permeate the entire object graph. If each object in the graph raises its own events, its calling object will have to propagate that event to its parent – resulting in defining the same events in multiple places, and each object being aware of all things possible with its great-grandchild objects. That is clearly bad.

What [ThreadStatic] is for

So, the solution is to use thread-static events.

[Sidebar] Thread-static events are just static events defined on a static class, where each event has the ThreadStaticAttribute applied to it. This attribute is important for server-side scenarios where multiple threads will be running through the Domain Model at the same time. The easiest thread-safe way to use static data is to apply the ThreadStaticAttribute.

Solution 3: Explicitness via Static Events

Each object raises the appropriate static event according to its logic. In our example, Customer would call:

And the service layer would write:

The advantage of this solution is that it requires minimal knowledge of the Domain Model for the Service Layer to correctly work with it. It also communicates that anything that doesn’t raise an event will be persisted transparently behind the appropriate root object.

Statics and Testability

I know that many of you are wondering if I am really advocating the use of statics. The problem with most static classes is that they hurt testability because they are difficult to mock out. Often statics are used as Facades to hide some technological implementation detail. In this case, the static class is an inherent part of the Domain Model and does not serve as a Facade for anything.

When it comes to testing the Domain Model, we don’t have to mock anything out since the Domain Model is independent of all other concerns. This leaves us with unit testing at the single Domain Class level, which is pretty useless unless we’re TDD-ing the design of the Domain Model, in which case we’ll still be fiddling around with a bunch of classes at a time. Domain Models are best tested using State-Based Testing; get the objects into a given state, call a method on one of them, assert the resulting state. The static events don’t impede that kind of testing at all.

What if we used Injection instead of Statics?

Also, you’ll find that each Service Layer class will need to subscribe to all the Domain Model’s events, something that is easily handled by a base class. I will state that I have tried doing this without a static class, and injecting that singleton object into the Service Layer classes, and in that setter having them subscribe to its events. This was also pulled into a base class. The main difference was that the Dependency Injection solution required injecting that object into Domain Objects as well. Personally, I’m against injection for domain objects. So all in all, the static solution comes with less overhead than that based on injection.

Summary

In summary, beyond the “technical basics” of being aware of your data volumes and designing your Domain Model to handle each use case performantly, I’ve found these techniques useful for designing its API as well as communicating my intent around persistence transparency. So give it a try. I’d be grateful to hear your thoughts on the matter as well as what else you’ve found that works.

Related posts:

• Fetching Strategy Design – showing how to separate the concern of eager loading from both your Domain Model and your Service Layer.
• Better Domain-Driven Design Implementation – showing the basics of how valuable interfaces between your Domain Model and the Service Layer can be.
• Lazy Loading, and how messaging fixes everything again – describing the advantage of O/R mapping your message classes as well.
• Query Objects vs Methods on a Repository – discussing the scalability (in terms of number of developers and queries) of Query Objects.

After seeing Mark’s post on Reasons for Isolation describing the ways Layered Architectures break down, and the ways making it more testable can change it, I’ve got to wonder – is Layering just too simplistic to actually work?

Just the other day I was doing a design review for a fairly simple Smart Client whose design was layered. In order to stay away from interfaces that accepted dozens of ints, strings, and dates, they wanted to have each layer talk to the other using “entities”. So where are these entities defined – oh, in a “vertical layer” that all the horizontal layers talk to.

OK, so we’ve taken the simplistic one-dimensional layered architecture and added a dimension. What now?

Well, it seems that having the business logic and the entities in separate layers goes against one of the most basic Object Oriented principles – encapsulation. So, let’s put the entities back in the Business Logic Layer. But then how will the Data Access Layer accept those objects as parameters?

So, that is solved by keeping Entity Interfaces in the “vertical” shared “layer”, and having the entities in the business logic layer implement those interfaces. That way, the data access layer can still accept parameters corresponding to those interfaces:

void InsertCustomer(Shared.Entities.ICustomer customer);

So far so good. Now, we want more testable UI layer code – so we use Model-View-Controller (MVC) – of whichever flavor suits your fancy. I’d say that Supervising Controller is a must. You could also add another presenter for more complex screens as in Passive View, but I’d be less strict on that. So, in which layer do these Controllers/Presenters sit? And is the Business Logic Layer the Model? Or is the Model just part of it?

Well, our Supervising Controllers are those who decide what action to do and when, where to get the data from, etc. That sounds like business logic to me. So let’s put them in the BLL. Presenters for the Passive View are much more UI centered, so let’s put them in the Presentation Layer. But we don’t want them tied to the implementation of the view, so we’ll put them in a separate package, and have them depend only on the view’s interface. So we’ll put the view interfaces in a package separate from the view implementation as well.

If it wasn’t clear up to this point, all the questions raised in this post are architectural in nature – as in they have a substantial impact on the structure and flow of the system, and will definitely have a profound effect on its maintainability. In other words, if you think that Layer Diagram covers your design – you’re probably deluding yourself. Personally, I think that’s why many developers consider architects to be “out of touch with the real world”.

When you have a design that answers these, and other architectural concerns, you’ll find that layering is of little importance. The specific constraints on each package are what counts. The fact that the Presentation Layer can talk to the Business Logic Layer doesn’t mean that the classes in your Views Implementation Package can. A large part of an architects work is to specify these constraints, and communicate them to the team. Tools like FxCop may help in terms of enforcing these constraints, but I believe that getting the team to actually “buy-in” is more effective.

Single-dimensional layered architectures don’t work. They violate Einstein’s maxim:

Make everything as simple as possible, but not simpler.

Layering – “simpler” to the point of simplistic.

In this podcast we answer questions about how to use autonomous components to unify disparate building blocks like servers, middleware, and databases in order to handle the technical complexity of complying with detailed service-level agreements. Reuse of business logic, database schemas, and messaging topics between autonomous components are discussed as well.

Download via the Dr. Dobbs’ site.

Or download directly here.

And here’s this week’s question:

Hi Udi,

Thanks again for your continued assistance. I was very much interested by your advice to consolidate each of the services related to each product family into a single service, but as autonomous components.

From your description of autonomous components from a prior podcast, it seems that they are much the same as services – in that they communicate only via loosely coupled messaging, and can have their own databases. Would you say that the main difference between autonomous components is that different autonomous components within a service may in fact share business logic and databases? If so, it would seem that combining these services into a single service with 3 autonomous components would be a matter of definition, rather than an architectural shift. Any information you could provide to clarify this distinction would be fantastic.

Something else that’s been playing on my mind of late – is whether or not you would consider a topic as having to belong to a specific service. That is, would you say it is bad practice to have multiple services publish on a common topic? I suppose if we have multiple services publishing on a common topic, then they should be defined as autonomous components, belonging to a single larger service – in which case that common topic would belong to that new service.

As usual your advice is always extremely helpful. Please keep those podcasts coming!

Best Regards,
Bill

Additional References

• Podcast on Message Schemas between multiple Publishers and Subscribers
• Podcast on Business and Autonomous Components in SOA

In this podcast we answer questions about how to solve dependencies between systems that subscribe to events in SOA. We’ll also get into the pitfalls of employing distributed transaction when reusing existing systems even behind service boundaries.

Download via the Dr. Dobbs’ site.

Or download directly here.

And the original question was:

Udi:

I have a question regarding publishing events that relate to data changes. I found the article you wrote in the Arch Journal #8 very helpful. I think striving for autonomy is very important. The scenario I was thinking about is how can you ensure synchronization across subscribers of a particular event.

For example, System A publishes an event when customer information is updated. There are several systems that subscribe to this event. Two of the systems, System B and System C, need to be sync regarding customer information. System B uses operations from System C using the customer data. Using your example, System B has a process that runs for all “Preferred Customers”, and it uses processes on System C. However, System C may not have process the event to and may have a customer as preferred.

I have several thoughts, but would like to get your thoughts on this scenario. Are there any best practices or patterns?

Phil

Additional References:

• Autonomous Services and Enterprise Entity Aggregation (Article in Microsoft Architecture Journal)
• Podcast on Autonomous Services and Pub/Sub

You can find more episodes like this in the Ask Udi archives.

I see this all too often.

A company has some legacy (read “good”) code in one platform (let’s just use Java for this example). This company has now decided to standardize on the other platform (Microsoft’s happy). The company doesn’t want to throw away and/or rewrite the assets they already have from the previous platform.

What do they do?

Web Services, of course!

Obviously this has to be a part of the “grand” SOA effort currently under way. Here’s a chance to build some reusable services, right?

The only problem is that in order for things to work right, they really must have a chatty interface, and flow transaction context between these “services”, and all the other things I describe as anti-patterns.

So, what’s the solution?

Well, Web Services isn’t the only kind of interop out there. Take a look at what the guys from MainSoft are doing. Not only does it work, it’s been working for years now. You can go the other way too – run .NET code on JVM based application servers. And there are more solutions out there. There’s JNBridge (with some nifty online demos), and EZ JCOM who also do COM interop.

Bottom line, there are good technical solutions out there for reusing and interop-ing with assets from multiple platforms. Therefore, now that we’ve slain the holy cow of interop, there is absolutely no good reason or justification to create tightly coupled services.

Period.