Udi Dahan   Udi Dahan – The Software Simplist
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Archive for the ‘Business Rules’ Category



Watch out for superficial invariants

Sunday, November 16th, 2014

As I was reading a blog post on CQRS, Aggregate Roots, and Invariants here, I became aware of a mistake I’ve seen many developers make over the years and I thought I’d call it out real quick.

Superficial Invariants

Taken from the blog post mentioned above: “For example, an employee cannot take more annual leave than they have.”

This falls into the trap of applying mathematical thinking (which we developers possess in great quantities) to the business world. The business world isn’t that mathematical (in general), and tends to have many more shades of gray expressed as “business rules” which can, and do, change.

Rules – not invariants

Employees can’t take more annual leave than they have.
… unless their manager approves.
… but that’s only up to 2 days.
… unless their manager is a VP, and then it’s up to 5 days.
… and that negative balance will be deducted from next year’s leave.
… Oh, and if the employee leaves the company before then, then the value of those negative days will be deducted from their final paycheck.

Impact on your domain

First of all, I hope you see that this isn’t something that you would trivially implement on an Employee object.

If you read these rules more carefully, you’ll probably notice that they’re speaking about a long-running process.

First, there is a request for leave. Then there’s an approval (with certain rules) which may come sometime later. And the approval itself may not even end the process – if the balance becomes negative.

And, as you’ve probably heard me say before, you end up with sagas as your aggregate roots (see Race conditions don’t exist from 4 years ago).

And a word about Bounded Contexts

Notice that these rules don’t care very much about things like the employee’s name, phone number, email, etc. Similarly, logic that deals with that data probably doesn’t care about the number of days of leave an employee takes.

In other words, these sets of data and logic can be said to belong to different Sub-Domains (in DDD terminology).

As such, it can make sense to take the annual leave logic and put it in a bounded context separate from the one responsible for the contact info.

In closing

In many of the samples and blog posts I see online, an overly simplified problem domain is implemented showing how the given implementation technique would be applied.

The problem is that developers then use that implementation technique as a “cookie cutter”, trying to fit real-world requirements into it, and then end up making a pretty big mess.

The more you delve into real-world requirements of business domains, the less you’ll see of mathematical invariants (unless, maybe, you’re building a physics engine for a game or something) and the more you’ll see long-running processes unfolding in front of you.

Regardless of whether you use NServiceBus sagas or not, start looking at the world as dynamic long-running processes rather than static noun-centric entities.



Code for my Programming in 4D talk

Wednesday, April 2nd, 2014

Click here for the animationSo, I’ve been a bad presenter.

I’ve given my Programming in 4D talk already several times and I haven’t yet uploaded the code for it.

And seeing as I’m going to be giving it again today (at the DevWeek conference in London), I figured that I should finally get my act together and put it online.

Interestingly enough, the other conferences I’ve spoken at either didn’t record it or didn’t put the recording online. Hopefully DevWeek will do better <FingersCrossed/>.

The overall solution

The scenario I talk about in this presentation is (again) a standard one in the world of retail: customers who want to return products that they’ve purchased and get a refund.

I’ve used our new ServiceMatrix tooling to model the solution like this (click for a larger image):

RefundPolicySolution

If you’d like to download the complete solution, click here.

Now, we’re going to focus on the RefundPolicy object that you can see towards the bottom left.

The Refund Policy

So, in this scenario, what we’re going to implement is a process whereby if you return your products within 30 days of the purchase, you’ll receive a 100% refund; if you return your products within 60 days you’ll receive a 50% refund, and anything longer than that and no refund for you.

Here’s the code:

public class RefundPolicy : Saga<RefundPolicySagaData>, 
                            IAmStartedByMessages<OrderAccepted>, 
                            IHandleMessages<ProductsReturned>, 
                            IHandleTimeouts<Percent>, 
                            IHandleSagaNotFound
{
    public void Handle(OrderAccepted message)
    {
        Data.OrderId = message.OrderId;
        Console.WriteLine("OrderAccepted");
 
        Data.Percent = 100;
 
        RequestTimeout(TimeSpan.FromDays(30), 50.Percent());
        RequestTimeout(TimeSpan.FromDays(60), 0.Percent());
    }
 
    public void Handle(ProductsReturned message)
    {
        Console.WriteLine("ProductsReturned");
 
        Bus.Send<IssueRefund>(m => m.Percent = Data.Percent);
        MarkAsComplete();
    }
 
    public override void ConfigureHowToFindSaga()
    {
        ConfigureMapping<ProductsReturned>(m => m.OrderId).ToSaga(s => s.OrderId);
    }
        
    public void Timeout(Percent state)
    {
        Console.WriteLine("Timeout");
        Data.Percent = state;
 
        if (state == 0)
            MarkAsComplete();
    }
 
    public void Handle(object message)
    {
        if (message is ProductsReturned)
            Console.WriteLine("No refund for you");
    }
}
 
public class RefundPolicySagaData : ContainSagaData
{
    [Unique]
    public int OrderId { get; set; }
 
    public Percent Percent { get; set; }
}

And what’s so good about that?

Well, not to steal my own thunder and give you a reason not to watch the video when it comes out, the trick is in the two RequestTimeout calls that are invoked when an OrderAccepted message arrives. You see, what that does is that it takes the data that defines the behavior of the refund policy and persists that via a queue, which will play back the data to our object according to the defined schedule.

This way, if/when the business decides to change the rules (say, reducing the timeframes to 20 days and 40 days), that will only affect users who are placing new purchases. The customers who made a purchase 50 days earlier (when the rules were still 30/60) will get the correct behavior applied to them.

Next steps

Of course, nobody would want a developer to have to open this code and change it in order to make a simple change like 30/60 -> 20/40, so we could externalize the data by creating a dictionary property on the saga where the key is the TimeSpan and the value is the Percent. Then, we could pull those values from either a config file or database and inject them into the property on the saga.

Here’s how the code of the saga would change:

public class RefundPolicy : Saga<RefundPolicySagaData>, 
                            IAmStartedByMessages<OrderAccepted>, 
                            IHandleMessages<ProductsReturned>, 
                            IHandleTimeouts<Percent>, 
                            IHandleSagaNotFound
{
    public Dictionary<TimeSpan, Percent> DataDefinitions { get; set; }
 
    partial void HandleImplementation(OrderAccepted message)
    {
        Data.OrderId = message.OrderId;
        Console.WriteLine("OrderAccepted");
 
        Data.Percent = 100;
 
        foreach(var kv in DataDefinitions)
            RequestTimeout(kv.Key, kv.Value);
    }

And the code to do the property injection would look like this:

public class RefundPolicyDataConfigurator : INeedInitialization
{
    public void Init()
    {
        Dictionary<TimeSpan, Percent> data = null /* get from config instead */;
        Configure.Instance.Configurer
            .ConfigureProperty<RefundPolicy>(p => p.DataDefinitions, data);
    }
}

Classes the implement INeedInitialization are invoked at process startup, and that call to ConfigureProperty instructs the container to set the DataDefinitions property of our RefundPolicy every time it is resolved (which is on every message).

In closing

We now have a solution which allows non-developers to make changes to the refund policy definitions without requiring us to deploy any new code to production. Also, any changes that are made will preserve the promises we made to our users in the past.

Of course, if you want changes to rules to impact all users immediately, this approach wouldn’t be so good.

Again, if you’d like to download the complete solution, the code is here, and if it wasn’t already obvious, this code makes use of NServiceBus quite heavily.

When the recording comes online, I’ll update this post with a link as well as do another blog post.

Hope you like it.



JPA with REST, OData, and SQL

Sunday, November 4th, 2012

Feeling a little bit rant-y today, as I just saw some more abuse of remote calls, this time on the Java side of things.

JPA is the Java Persistence API – a kind of ORM, as you’d expect. Luckily, a lot of the web services stuff was already on the way out by the time that EclipseLink DBWS came out. DBWS allowed you to expose database artifacts as web services.

I mean, it’s not like we have any other interoperable ways of accessing data, right?

Anyway, like I said, that didn’t take off, but now they’re reinventing it – this time with REST!

In case you had any doubts, REST is pure awesomeness and adding it to anything else makes it awesome too. Lest anybody take this out of context (it’s happened before), I’m being sarcastic.

Here it is.

God knows they couldn’t let Microsoft totally dominate this area with OData coming out quite some time ago. In case you were wondering, OData was designed to provide standard CRUD access of a data source over HTTP.

Of course, none of these support any transactions so if you actually wanted to do some meaningful business logic on top of this CRUD, you wouldn’t have any consistency. And, let’s face it, if you’re not doing any meaningful business logic, just basic persistence, you just do it. That problem’s been solved a long time ago.

Can we please stop reinventing SQL already?



UI Composition vs. Server-side Orchestration

Monday, July 9th, 2012

orchestra_compositionFollowing on my last post called UI composition techniques for correct service boundaries, one commentor didn’t seem to like the approach I described saying:

“I’m sorry, but with all due respect I must strongly disagree. You haven’t avoided any orchestration work at all, you’ve just moved it in to client side script!

How are you going to deal with the scenario that one of the service calls fails? Say a failed credit card payment, or no more rooms left? In more javascript??

I would much rather take the less brittle approach of introducing an orchestration service. Like it or not, however trivial it may be, there is a relationship between these services, if one call fails, they both fail. This should be reflected in the architecture, not hidden in javascript. With an orchestration service you also either get transactions for free provided by infrastructure, or alternatively if the underlying service doesnt support this, explicit and unit testable control over recovery.”

Since this is a common point of view, I thought I’d take the time to explain a bit more.

Let’s start at a fairly high level.

On failures

I’ve talked many times in the past about how to handle technical causes for failure like server crashes, database deadlocks, and even deserialization exceptions. Messaging and queuing solutions like NServiceBus can help overcome these issues such that things don’t actually fail – they just take a little longer to succeed.

On the logical side of things, the CQRS patterns I talk about describe an approach where aggressive client-side validation is done to prevent almost all logical causes for failure. The only thing that can’t be mitigated client-side are race conditions resulting in actions taken by other users at the same time.

In short, it really is uncommon for things to fail when being processed server-side.

Back to the specific example

The concerns raised in the comment specifically talked about a failed credit card payment or no rooms left in the hotel, so let’s start with the credit card thing:

In my last post I talked about collecting guest and credit card information from the user as a part of the “checkout” process when making a reservation for a hotel room. Just to be clear – there is a final “confirm your reservation” step that happens after all information has been collected.

What this means is that we aren’t actually charging the customer’s card when we collect that data, therefore there is no real issue with a failed credit card payment that needs to be handled by the client-side javascript. When the customer confirms their reservation, yes, there might be a failure when charging the card though there are only some specific types of rates for which the hotel charges your card when you make a reservation.

In general, failed credit card payments are handled pretty much the same way for all ecommerce – an email is sent to the customer asking for an alternative form of payment, also saying that their purchase won’t be processed until payment is made.

In any case, it is only after the reservation is placed that the responsible service would publish an event about that. The service which collected the credit card information would be subscribed to that event and initiate the charge of the card when that event arrives (or not, depending on the rate rules mentioned).

With regards to there not being any rooms left, well, first of all, there’s overbooking – hotels accept more reservations than rooms available because they know that customers sometimes need to cancel, and some just don’t show up. Secondly, there is a manual compensation process if more people show up than there are actual rooms to put them in. In some cases, a hotel will bump you up to a higher class of room (assuming there aren’t too many reservations for those), and in others they will call a “partner” hotel nearby and put you up there instead.

In summary

While arguments can be made that yes, these issues have been addressed in this specific example, there may be other domains where it is not possible to do these kinds of “tricks”. Although I do agree with that in theory, I’ve spent the better part of 5 years travelling around the world talking to hundreds of people in quite a few business domains, and every single time I’ve found it possible to apply these principles.

In short, the use of UI composition allows services to collect their own data, making it so anything outside that service doesn’t depend on those data structures which makes both development and versioning much easier. Technical failure conditions can be mitigated at infrastructure levels in most cases and other business logic concerns can be addressed asynchronously with respect to the data collection.

Give it a try.



A CQRS Journey – with and without Microsoft

Thursday, March 29th, 2012

Update – clarification post here.

circlesI was on a call recently with the Advisory Board for the Microsoft Patterns & Practices (P&P) CQRS Journey project where they were showing the current state of their development. Towards the middle of the call, I mentioned that I found there to be too many concerns in one place and that I had expected there to be a division into multiple sub-domains/bounded contexts/business components (BCs). The answer was that they hadn’t gotten to the other areas yet and that’s why at that point in time there was only one BC.

The conversation got a bit derailed at that point, and I was asked how I would do it (though not quite as politely), ultimately leading to my tweeting this:

I think I got over 50 people who wanted in on this, while some of them urged me to work with P&P rather than separately. I think I’ll do both, hopefully resulting in two implementations that can be compared – one based on Azure (done by P&P) and the other based on NServiceBus (done by my guys). Who do you think is more worried 😉

But first things first

The fundamental flaw that I see happening with many software projects (including the P&P CQRS effort) is that not enough time is spent to understand the underlying business objectives – the thinking behind the use cases / user stories. Developers assume behavior is “like” that of another/similar domain – when the difference in the details matter a lot. That often leads to software boundaries that aren’t properly aligned with those of the business.

The effects of this lack of alignment may be felt only much later in the project, when we get a requirement that just doesn’t fit the architecture we’ve set up. I’ve blogged about the symptoms of this problem about 2 years ago in my post Non-functional architectural woes.

We need to get into the nitty-gritty of our problem domain to find out what makes it special.

Not all e-commerce is equal

Anytime somebody is going to make a purchase online, developers immediately create some kind of “order” entity with a bunch of “order lines”, just like they read about in all the blog posts and books. Then, all sorts of other behavior are shoe-horned around those entities and… voila, a working system.

The domain of conferences is different – we don’t actually ship products when people register so payment concerns are very different. If our company is purchasing 5 tickets to the conference, the number of people (and which specific people) that eventually go to the conference may be very different than the people we had originally registered – there doesn’t tend to be that kind of volatility in traditional B2C retail (like selling books to people online).

It’s also quite likely that if a company is sending many people to a conference that they wouldn’t be paying by credit card – invoicing and payment may happen much later. That is no reason to block registration from completing.

Not all registration systems are equal

I understand how people can look at systems like TicketMaster and use that as a model for this system but, once again, the differences in the domain matter.

First of all, most people don’t purchase movie tickets weeks in advance – conference tickets do go on sale that far in advance. Second, if the movie you want to go to is sold out this week, no big deal, you’ll see it next week – conferences are more of a one-time/yearly deal. Third, you usually go to the movies with family/friends – if you can’t get tickets for everyone, you’ll go next week. When it comes to conferences, there is no “next week”, so whoever can go, does. Also, attendees going to a conference together are usually coworkers, not family – there are less qualms about leaving someone behind.

This is already leading us to a model where we should not view a group registration as a single success or failure affair. This will have an impact on the commands, events, and transactions that flow through our system.

In any case where people are reserving something far in advance, there is a high likelihood of cancellations. This is similar to the domain of hotels/hospitality where you can cancel your reservation up to N days before your arrival at no charge. This also tends to influence the payment structure – we’d rather not have to return people’s money as there can be per-transaction charges for that, instead delaying payment can make sense.

Similar to how hotels overbook by a certain amount (to offset cancellations), our conference might look at doing something similar. The difference is that in the case of a hotel, the guest will likely just book a room in a different hotel in the case the first hotel was fully booked. This probably won’t happen with a conference.

For that reason, we want to remember who wanted to come to our conference even when we thought we were full. You see, our best chance of filling a seat that opened up due to a cancellation is by a person who wanted to register before. What we need here is a waiting list – something that doesn’t make the same kind of sense for hotels or airlines (although airlines do use waiting lists, just that that is usually exposed to travel agents and not to travelers booking online).

First-come, first-served – fairness

The traditional developer thinking about systems is rooted in synchronous and sequential processes. In attempting to give a good user experience, developers want to give the user final confirmation as quickly as possible – whether that’s success or failure.

This results in a first-come, first-served user interaction model – whichever user registers in our conference management system first, the better the chance they’ll get what they want. That sounds like a pretty fair system, the only thing is that fairness was not a requirement.

In the real world, if people are standing in line for tickets, they’d get really upset if the tellers decided somewhat arbitrarily to serve people in the back of the line before those in the front. The great thing about online systems is that nobody can see the “virtual line” – the system can be as unfair as we like and there isn’t a real way for the users to know that this is happening.

Why be unfair?

While conferences, theaters, and airlines all want to have all seats filled, the difference between the ongoing models of airlines and theaters and the once-a-year model of the conference influence how sales are done. Some companies send a lot of employees to our conference so we want to give them preference in registration. This is area that we have the most leverage over – when it comes to the masses who arrive in ones and twos, there’s not very much we can do. It makes sense to bend over backwards for a large group, but not for a small one. A commitment from a large company tends to mean more than that from a small one.

If Boeing has already registered 70 people to your conference and now wants to send 5 more, are you really going to tell them “sorry, we’re fully booked”, or are you going to do everything in your power to keep them happy so that next year they’ll want to keep working with you? Wouldn’t it be nice if you could “unregister” some people to make room for the Beoing guys.

Now, you can’t necessarily do this up until the last minute, but potentially 2 weeks (or whatever) before the event could be reasonable, leaving people the ability to cancel flights and hotels without charges (assuming we tell them during registration that they should buy refundable plane tickets).

The easiest way to “unregister” someone is to not tell them that their registration was confirmed. In short, 2 weeks before the start of the event we finalize all registrations deciding (based on our internal priority) who gets in and who doesn’t. We may have logic that decides to immediately finalize registration from Boeing (and other select customers) without waiting until 2 weeks before the event.

Just don’t look TOO unfair

Appearance is everything. Perception matters. You don’t want to get a reputation for being unfair.

So when we open registration, we can allow the first N people to bypass our waiting list and get accepted right away (payment still needing to be handled later). At that point, you can start moving new registrations through the waiting list.

The thing is, nobody knows that you aren’t actually full at that point 🙂

Influences on architecture

I hope you’re getting the impression that this collection of scenarios is going to have a big impact on the design. It indicates to us which parts of the business need to be 100% consistent with each other and which parts can be eventually consistent – ultimately defining where one bounded context stops and another begins. This has a direct impact on the events that we’d end up with – who would publish what, and how many others would subscribe to it.

I know some people will look at the above scenarios and say “but what if the requirements were different?”. The thing is that not all requirements are created equal. In working with our business stakeholders, we need to identify which elements are stable and which are potentially volatile and, yes, that’ll be different in each project. We want to align the main boundaries of our software with the stable business elements.

And don’t even try to create a system so flexible that it could handle any new requirement without any architectural changes – down that path lies madness. User-defined custom fields used in user-defined custom workflows, all of it appearing in reports with sorting, filtering, and grouping. You might as well give your users Visual Studio.

Back to P&P

I don’t know if P&P will adopt this set of requirements for their CQRS Journey. The thing here is that we can see the collaborative nature of the domain quite clearly – multiple actors working in parallel where the decisions of one affect the outcomes of another.

The requirements that I’ve seen being handled in the CQRS Journey so far don’t seem complicated enough to justify anything more than a 2-tier architecture – it’s feeling somewhat over-engineered right now. I know that people in the community see other benefits to CQRS but I’ll have to put up a separate blog post describing why there are other better solutions than CQRS most of the time.

Anyway, I’m willing to see how things progress and tweak these requirements (up to a point) so that both the NServiceBus solution and the Azure solution are addressing the same problem.

In closing

Occasionally I hear people still raising the agile mantra against Big Design/Requirements Up Front. The thing is that Agile Manifesto never said to intentionally bury your head in the sand with regards to the purpose of the system. It was a push-back against spending months in analysis without anything but documents coming out, but the goal was to reach a middle ground. Nobody ever said “no design up-front” or “no requirements up front”.

I’m going to try to work with both P&P and the alumni of my Advanced Distributed Systems Design course to come up with simplest possible solution that addresses the requirements (functional and non-functional).

Hope you’ll find this journey interesting.

Update – clarification post here.



Don’t try to model the real world, it doesn’t exist.

Monday, March 5th, 2012

Recently I’ve started talking more about modeling and its relation to the real world.

no spoonHere’s where it all starts from:

Don’t try to model the real world, it doesn’t exist.

I know that that sounds like a very Matrix-y kind of statement, so let me explain.

The “Real” World

The problem with the “real” world is that you are limited by the laws of physics. The thing is that somewhere along the history of software development, we got this idea that if only the structure of our software represented physical reality, then our software would be maintainable, flexible, robust, … in short, good.

glassThe thing is that a single physical entity can have multiple meanings to various stakeholders.

Let’s look at something simple, like a glass:

From a developer’s perspective we might call that a Product and not think very much more of it. We’d be happy that we could come up with a single abstraction that allowed us to model all the different kinds of products the same way.

Yet, in talking with our business stakeholders, one might call it inventory, another might call it a liability (think of breakage requiring insurance), and another call it merchandise. The important thing to note is that the data relevant to each of those meanings is so different from one stakeholder to another.

And that brings me to “customer”

One of my least favorite entities – a lingering symptom of the Northwind disease.

When someone walks into your store for the first time (whether that store is physical or virtual), are they a customer? Even if they haven’t ever bought anything? Even if you don’t know their name? Are they even a User then? I mean, it’s not like we’re going to force people to login (or create an account) just to browse the site, right? A term like Visitor, Prospect, or Lead sounds like it would describe this type of concept better.

After wandering around your store for a while, they come up to you and ask for help finding something. If this pattern repeated itself over and over again for the same category of item, would that be meaningful to the business? Don’t you think that should be modeled? I hope your answers are yes, and yes. This is the domain of merchandising, and seems more related to Visitors than to Customers.

Let’s say your selling to other businesses rather than to consumers. In the B2B space, it is common not to receive payment for goods or services for some time – you might have heard terms like Net30, which means you will be paid up to 30 days later (in some cases, this may be from the end of the month of the invoice rather than the date of the invoice).

If you talk to the business folks in charge of these scenarios, you’ll hear them talk about Accounts Payable and Accounts Receivable. Yep, they are the accountants. If you were to go about building a DDD Ubiquitous Language, it sounds like the term Account would be a better choice than Customer. The thing is that accountants use the same language regardless of how quickly an account is settled – like if payment is done by credit card at the time of purchase.

There is no Customer.
There is no Product.

The same goes for so many other problem domains.

I know it feels counter-intuitive to not have a single class representing a single physical thing. It feels like it’s the exact opposite of Domain-Driven Design. It feels anti-object-oriented. But remember, most stakeholders you talk to don’t focus on the physical elements either.

The one thing left to be modeled from “reality”

And that’s identity.

It would be most accurate to say that the physical thing you perceive is nothing more than identity serving to correlate all the separate business concerns to each other. It’s this ID that ties the Visitor on the site, to the Account, to the Addressee (for shipment).

These IDs are needed primarily for reporting and UI reasons – it isn’t likely to have a business action operate on entities correlated this way in the same transaction.

Nouns, Verbs, and Reality

In building your ubiquitous language, look past the nouns and verbs visible on the surface.

Watch out for statements like “in reality…” and “in the real world…” as they are really just one person’s interpretation of their perception of reality. Not one of us is able to see reality clearly – it’s all just perceptions. Recognize that, like models, all perceptions are wrong, but some may be useful.

Model the perceptions – at least you can have first hand experience of those.

Forget about reality – all that exists is perceptions.

In closing

Transcend the physical.

In software there is no gravity, no mass, and as many dimensions as you choose to create.

Break free of the Matrix.

You are the god of your software.



Inconsistent data, poor performance, or SOA – pick one

Sunday, September 18th, 2011

One of the things that surprises some developers that I talk to is that you don’t always get consistency even with end-to-end synchronous communication and a single database. This goes beyond things like isolation levels that some developers are aware of and is particularly significant in multi-user collaborative domains.

The problem

Let’s start with an image to describe the scenario:

Inconsistency

Image 1. 3 transactions working in parallel on 3 entities

The main issue we have here is that the values transaction 2 gets for A and B are those from T0 – before either transaction 1 or 3 completed. The reason this is an issue is that these old values (usually together with some message data) are used to calculate what the new state of C should be.

Traditional optimistic concurrency techniques won’t detect any problem if we don’t touch A or B in transaction 2.

In short, systems today are causing inconsistency.

Some solutions

1. Don’t have transactions which operate on multiple entities (which probably isn’t possible for some of your most important business logic).

2. Turn on multi-version concurrency control – this is called snapshot isolation in MS Sql Server.

Yes, you need to turn it on. It’s off by default.

The good news is that this will stop the writing of inconsistent data to your database.
The bad news is that it will probably cause your system many more exceptions when going to persist.

For those of you who are using transaction messaging with automatic retrying, this will end up as “just” a performance problem (unless you follow the recommendations below). For those of you who are using regular web/wcf services (over tcp/http), you’re “cross cutting” exception management will likely end up discarding all the data submitted in those requests (but since that’s what you’re doing when you run into deadlocks this shouldn’t be news to you).

The solution to the performance issues

Eventual consistency.

Funny isn’t it – all those people who were afraid of eventual consistency got inconsistency instead.

Also, it’s not enough to just have eventual consistency (like between the command and query sides of CQRS). You need to drastically decrease the size of your entities. And the best way of doing that is to partition those entities across multiple business services (also known in DDD lingo as Bounded Contexts) each with its own database.

This is yet another reason why I say that CQRS shouldn’t be the top level architectural breakdown. Very useful within a given business service, yes – though sometimes as small as just some sagas.

Next steps

It may seem unusual that the title of this post implies that SOA is the solution, yet the content clearly states that traditional HTTP-based web services are a problem. Even REST wouldn’t change matters as it doesn’t influence how transactions are managed against a database.

The SOA solution I’m talking about here is the one I’ve spent the last several years blogging about. It’s a different style of SOA which has services stretch up to contain parts of the UI as well as down to contain parts of the database, resulting in a composite UI and multiple databases. This is a drastically different approach than much of the literature on the topic – especially Thomas Erl’s books.

Unfortunately there isn’t a book out there with all of this in it (that I’ve found), and I’m afraid that with my schedule (and family) writing a book is pretty much out of the question. Let’s face it – I’m barely finding time to blog.

The one thing I’m trying to do more of is provide training on these topics. I’ve just finished a course in London, doing another this week in Aarhus Denmark, and another next month in San Francisco (which is now sold out). The next openings this year will be in Stockholm, London; Sydney Australia and Austin Texas will be coming in January of next year. I’ll be coming over to the US more next year so if you missed San Francisco, keep an eye out.

I wish there was more I could do, but I’m only one guy.

Hmm, maybe it’s time to change that.



The Danger of Centralized Workflows

Wednesday, July 13th, 2011

It isn’t uncommon for me to have a client or student at one of my courses ask me about some kind of workflow tool. This could be Microsoft Workflow Foundation, BizTalk, K2, or some kind of BPEL/orchestration engine. The question usually revolves around using this tool for all workflows in the system as opposed to the SOA-EDA-style publish/subscribe approach I espouse.

The question

The main touted benefit of these workflow-centric architectures is that we don’t have to change the code of the system in order to change its behavior resulting in ultimate flexibility!

Some of you may have already gone down this path and are shaking your heads remembering how your particular road to hell was paved with the exact same good intentions.

Let me explain why these things tend to go horribly wrong.

What’s behind the curtain

It starts with the very nature of workflow – a flow chart, is procedural in nature. First do this, then that, if this, then that, etc. As we’ve experienced first hand in our industry, procedural programming is fine for smaller problems but isn’t powerful enough to handle larger problems. That’s why we’ve come up with object-oriented programming.

I have yet to see an object-oriented workflow drag-and-drop engine. Yes, it works great for simple demo-ware apps. But if you try to through your most complex and volatile business logic at it, it will become a big tangled ball of spaghetti – just like if you were using text rather than pictures to code it.

And that’s one of the fundamental fallacies about these tools – you are still writing code. The fact that it doesn’t look like the rest of your code doesn’t change that fact. Changing the definition of your workflow in the tool IS changing your code.

On productivity

Sometimes people mention how much more productive it would be to use these tools than to write the code “by hand”. Occasionally I hear about an attempt to have “the business” use these tools to change the workflows themselves – without the involvement of developers (“imagine how much faster we could go without those pesky developers!”).

For those of us who have experienced this first-hand, we know that’s all wrong.

If “the business” is changing the workflows without developer involvement, invariably something breaks, and then they don’t know what to do. They haven’t been trained to think the way that developers have – they don’t really know how to debug. So the developers are brought back in anyway and from that point on, the business is once again giving requirements and the devs are the one implementing it.

Now when it comes to developer productivity, I can tell you that the keyboard is at least 10x more productive than the mouse. I can bang out an if statement in code much faster than draggy-dropping a diamond on the canvas, and two other activities for each side of the clause.

On maintainability

Sometimes the visualization of the workflow is presented as being much more maintainable than “regular code”.

When these workflows get to be to big/nested/reused, it ends up looking like the wiring diagram of an Intel chip (or worse). Check out the following diagram taken from the DailyWTF on a customer friendly system:

stateModel

The bigger these get, the less maintainable they are.

Now, some would push back on this saying that a method with 10,000 lines of code in it may be just as bad, if not worse. The thing is that these workflow tools guide developers down a path where it is very likely to end up with big, monolithic, procedural, nested code. When working in real code, we know we need to take responsibility for the cleanliness of our code using object-orientation, patterns, etc and refactoring things when they get too messy.

Here is where I’d bring up the SOA/pub-sub approach as an alternative – there is no longer this idea of a centralized anything. You have small pieces of code, each encapsulating a single business responsibility, working in concert with each other – reacting to each others events.

Productivity take 2: testing and version control

If you’re going to take your most complex and volatile business logic and put it into these workflow tools, have you thought about how your going to test it? How do you know that it works correctly? It tends to be VERY difficult to unit-test these kinds of workflows.

When a developer is implementing a change request, how do they know what other workflows might have been broken? Do they have to manually go through each and every scenario in the system to find out? How’s that for productivity?

Assuming something did break and the developer wants to see a diff – what’s different in the new workflow from the old one, what would that look like? When working with a team, the ability to diff and merge code is at the base of the overall team productivity.

What would happen to your team if you couldn’t diff or merge code anymore?
In this day and age, it should be considered irresponsible to develop without these version control basics.

In closing

There are some cases where these tools might make sense, but those tend to be much more rare than you’d expect (and there are usually better alternatives anyway). Regardless, the architectural analysis should start without the assumption of centralized workflow, database, or centralized anything for that matter.

If someone tries to push one of these tools/architectures on you, don’t walk away – run!



Entities, Transactions, and Broken Boundaries

Saturday, March 5th, 2011

One of the things I cover early on in my course is the problem with traditional layered architecture driving people to create a business logic layer made up of a bunch of inter-related entities. I see this happening a lot, even though nowadays people are calling that bunch of inter-related entities a “domain model”.

Let me just say this upfront – most inter-related entity models are NOT a domain model.
Here’s why: most transactions don’t respect entity boundaries.

That being said, you don’t always need a domain model.
The domain model pattern’s context is “if you have complicated and everchanging business rules” – right there on page 119 of Patterns of Enterprise Application Architecture.

Persisting the customer’s first name, last name, and middle initial – and later reading and showing that data does not sound either complicated or that it is really going to change that much.

Then there are things like credit limits, that may be on the customer entity as well. It is likely that there are business requirements that expect that value to be consistent with the total value of unpaid orders – data that comes from other entities.

The problem that is created is one of throughput.

Since databases lock an entire row/entity at a time, if one transaction is changing the customer’s first name, the database would block another transaction that tried to change the same customer’s credit limit.

The bigger your entities, the more transactions will likely need to operate on them in parallel, the slower your system will get as the number of transactions increases. This feeds back in on itself as often those blocked transactions will have operated already on some other entity, leaving those locked for longer periods of times, blocking even more transactions.

And the absurd thing is that the business never demanded that the customer’s first name be consistent with the credit limit.

What if we didn’t have a single Customer entity?

What if we had one that contained first name, last name, middle initial and another that contained things like credit limit, status, and risk rating. These entities would be correlated by the same ID, but could be stored in separate tables in the database. That would do away with much of the cascading locking effects drastically improving our throughput as load increases.

And you know what? That division would still respect the 3rd normal form.

Which of these entities do you think would be classified by the business under the “complicated and everchanging rules” category?

And for those entities that are just about data persistence – do you think it’s justified to use 3 tiers? Do we really need a view model which we transform to data transfer objects which we transform to domain objects which we transform to relational tables and then all the way back? Wouldn’t some simpler 2-tier programming suffice – dare I say datasets? Ruby on Rails?

Are we ready to leave behind the assumption that all elements of a given layer must be built the same way?



Race Conditions Don’t Exist

Tuesday, August 31st, 2010

crossing-the-finish-lineNot in the business world anyway.

The problem is that, as software developers, we’re all too quick to accept them at face value. We don’t question the requirements – in all fairness, it was never our job to do so. We were the ones that implemented them, preferably quickly.

For example

Let’s say we get the requirement the following requirements:

1. If the order was already shipped, don’t let the user cancel the order.
2. If the order was already cancelled, don’t let the user ship the order.

The race condition here is when we have two users who are looking at the same order, which is neither cancelled nor shipped yet, and each submits a command – one to ship the order, the other to cancel it.

In these cases, the code is simple – just an if statement before performing the relevant command.

So what’s the problem

A microsecond difference in timing shouldn’t make a difference to core business behaviors. Which means that we’ve actually got here is a bug in the requirements. Users are actually dictating solutions here rather than requirements.

Let’s ask our stakeholders, “why shouldn’t we let users cancel a shipped order? I mean, the users don’t want the products.”

And the stakeholders would respond with something like, “well, we don’t want to refund the user’s money then. Or, at least, not all their money. Well, maybe if they return the products in their original packaging, *then* we could give a full refund.”

And as we drilled deeper, “when do refunds need to be given? Right away, in the same transaction?”

The stakeholders would explain, “no, refunds don’t need to be given right away.”

It turns out we were missing the concept of a refund, as well as assuming that all things needed to be processed and enforced immediately. Once we dug into the requirements, we found that there is actually plenty of time to allow both transactions to go through. We just need to add some checks during shipping’s long-running process to see if the order was cancelled, and then to cut the process short.

So is everything a long-running process then?

That’s actually a fair question – long-running processes are a lot more common than at first appears.

What we’re seeing is that cancellation is now a command that has no reason to fail – just like CQRS tells us. When this command is performed, it publishes the OrderCancelled event, which the billing service subscribes to.

Billing then starts a long-running process (a saga, in NServiceBus lingo), also listening to events from the shipping process, ultimately making a decision when a refund should be given, and for how much.

Deeper business analysis

As we discuss matters more with our business stakeholders, we hear that most orders are actually cancelled within an hour of being submitted. It is quite rare for orders to be cancelled days later.

In which case, we could look at modeling the acceptance of an order as a long-running process itself.

When a user places an order, we don’t immediately publish an event indicating the acceptance of an order, instead a saga is kicked off – which opens up a timeout for an hour later. If a cancellation command arrives during that period of time, the user gets a full refund (seeing as we didn’t charge anything since billing didn’t get the accepted event to begin with), and the saga just shuts itself down. If the timeout occurs an hour later, and the saga didn’t get a cancel command, then the order is actually accepted and the event is published.

Yes, sagas are everywhere, once you learn to see with business eyes, and no race conditions are left.

In closing

Any time you see requirements that indicate a race condition, dig deeper.

What you’re likely to find are some additional business concepts as well as the introduction of time and the creation of long-running business processes. The implementation at that point will pivot from being trivial if-statements to being richer sagas.

Keep an eye out.



   


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“I attended both of Udi's "UI Composition Key to SOA Success" and "DDD in Enterprise Apps" sessions and they were exceptionally good. I will definitely participate in his sessions again. Udi is a great presenter and has the ability to explain complex issues in a manner that everyone understands.”

Eran Sagi, Software Architect at HP
“So far, I heard about Service Oriented architecture all over. Everyone mentions it – the big buzz word. But, when I actually asked someone for what does it really mean, no one managed to give me a complete satisfied answer. Finally in his excellent course “Advanced Distributed Systems”, I got the answers I was looking for. Udi went over the different motivations (principles) of Services Oriented, explained them well one by one, and showed how each one could be technically addressed using NService bus. In his course, Udi also explain the way of thinking when coming to design a Service Oriented system. What are the questions you need to ask yourself in order to shape your system, place the logic in the right places for best Service Oriented system.

I would recommend this course for any architect or developer who deals with distributed system, but not only. In my work we do not have a real distributed system, but one PC which host both the UI application and the different services inside, all communicating via WCF. I found that many of the architecture principles and motivations of SOA apply for our system as well. Enough that you have SW partitioned into components and most of the principles becomes relevant to you as well. Bottom line – an excellent course recommended to any SW Architect, or any developer dealing with distributed system.”

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