Top Domain Model: behaviors, processes and reactions

TL;DR

After pivoting two nights straight (here and here) it’s time to settle down and ask is it possible to stick just to aggregates to model your domain? Is it possible to make it any better with services or maybe another tool is needed?

Actions and state

Aggregates define the boundaries of transactions. That’s their primary target. They narrow down not only our thinking (in a positive sense), but also provide an ability for scaling out our model. If every aggregate sits in its own bucket, there’s nothing easier to save it as a document, or a stream of events within one partition. Their boundaries won’t be ever crossed. The last one is actually a wishful thinking. Who would like to transfer money without ever receiving them on the other side?

Actions and reactions

Think in processes. One account is debited, the other is credited. The second does not have to happen in the same transaction. Moreover, the second, in its nature, is a reaction to the first account being debited. In a natural world reactions often happen at the same time. Modelling them in this way (transactions across all the aggregates) might be more realistic but for sure, is not more useful. The more elements in the transaction, the higher probability of failing… and so on and so forth.

Aggregates + processes

The above is a description of a perfect couple. Aggregates and processes are two tools that you can use to model any domain. Actually, if you dared to say that you don’t need processes, I’d say that you could be wasting your time modelling a really boring and simple domain with a DDD tooling. From the tooling perspective, whether you want to event-source everything all the way or use good old fashioned orm with a message bus, it’s up to you. Just remember, that the true power in your model comes from combining aggregates and processes.

Summary

Modelling aggregates that just work (TM) is impossible. Any, even moderately complex domain contains a lot of reactions and processes that need to be captured in your model to make it usable. Next time, you think about an aggregate reacting to something, ask yourself, what kind of process is this, how should I name it, how to model it?

Top Domain Model: I’ve been pivoting all night long. Again

TL;DR

In the last entry we noticed that we can model out some problems by selecting a different aggregate an event belongs to. In this episode, we will revisit this idea by referring to the good old-fashioned Twitter and its timelines. How timelines are created? Is everyone treated equally? Is it only aggregates’ identities that should be pivoted or maybe our thinking as well?

Fans in, fans out

The model behind Twitter timelines is quite simple. It’s also different for people having 10 followers or 10 millions. The difference is the number of timelines that needs to be updated when Madonna writes a tweet or a @JustAnotherAccountLikingMadonna2019 retweets one of their favorite performer thoughts. Notifying 10 millions people is not that easy and takes a bit longer. Writing to 10 timelines is easy and fast.

Golden customer

A similar reasoning might be added to a golden customer profile or any kind of dimension that distinguishes an aggregate type in your model. Sometimes, a behavior will be slightly altered, sometimes it will be totally rewired. The most important idea is to don’t stick to the initial model. Let yourself ask important questions to distill and clarify it. To discover these golden customers that require different handling, to discover Madonnas that require cargo shipping to deliver tons of their tweets and so on and so forth.

A new type or not

Sometimes, this reasoning will bring you new types of aggregates, sometimes it will be a process based on a dimension distinguishing a Madonna-like aggregate instance. As always, every model will be wrong, but some of them will be more useful than others.

Summary

Don’t stick to the initial aggregate type. Ask more modelling questions, that can bring you new types of aggregates or processes depending on a specific dimension value of already existing aggregate. Pivot not only identities, but also your thinking.

Top Domain Model: I’ve been pivoting all night long

TL;DR

This is the next entry in the Top Domain Model series of loosely coupled posts describing different modelling approaches. In the last one we covered a temporal dimension, it’s time to consider what is an aggregate and where an event belongs to.

Endorsements

We all love receiving endorsements on LinkedIn, don’t we? How would you model such a feature? How would you draw a boundary of the aggregate? Would one aggregate be sufficient enough? Let’s first reason about a single aggregate provided by a user.

Endorsements profile per user

You could easily imagine providing an Endorsements aggregate per user. It could be visualized as a REST subresource of a user like

/user/1231423/endorsements

This could be implemented in a simple way and would handle properly situations where endorsing somebody is not that frequent. In other way, that the probability of having two users endorsing the third at the same time is quite low. What if it was a famous CTO who just created his profile? What if the number of endorsements would be bigger that 100/s? This model would not hold? What would it then?

Pivot to the rescue

When modelling, answering what’s the subject and what’s the action is not that straightforward. You may say that:

An user is endorsed by another

which means that user’s endorsements are modified by another user. But you could also rephrase this to

An user endorses another

Which could be modeled as endorsements storing another users tags in YOUR aggregate. This model, even with a lot of people endorsing is easily scalable: everyone is applying endorsements for other users in their own aggregate. You won’t endorse more than 10 skills a sec, will you?

This approach requires to create a separate, reactive view applying all the events to the read side, so that the famous CTO gets their skills displayed. But this, as it can be eventually consistent, is much easier than overcoming a high throughput scenario for writes.

Summary

When dealing with high volumes of operations ask, if the model can be pivoted? Maybe, selecting another owner of business operation, or even, modelling a new type of an aggregate, can help you deal with requirements you need to satisfy.

 

Top Domain Model: I’m temporal

TL;DR

This is the first from entries written under wings of Top Domain Model. Nope, it’s not a new TV show for domain driven modellers. It’s a series about domain driven modelling itself. Today, we’ll take a look at models and their temporal dimension.

Reservation

Imagine that you model a system for a major hospital. Unfortunately, the registrations are opened once a year, and multiple people want to register at the same time. It’s even worse, they want to register to get their procedure scheduled in a specific room that has all the needed tools. The first idea could be to model the room as an aggregate. You can imagine hundreds of people trying to update the same aggregate. It won’t work.

Temporal dimension

To address this you could introduce a temporal dimension of the room. Instead of treating it as one room, you could model it as a RoomDay, that represents a schedule for a specific day. This would:

  • spread the saturation over multiple aggregates (possibly with a more less natural distribution)
  • make the aggregate time-bound (once the day passes, whole aggregate can be archived, deleted)

You could chop even further if needed, nevertheless, adding a temporal dimension to an aggregate can easily help you to simplify challenges related to scale and long lifespan of aggregates.

Summary

When modelling an aggregate, that it’s going to be highly contended, ask yourself is it naturally temporal? Possibly it can be replaced by multiple aggregates, each assigned to one year/month/day.

 

Top Domain Model

It looks like a new series is going to be published on this blog!

I received some feedback related to the recent series making your event sourcing functional. Posts in this series will be loosely coupled and more-less self-contained. The topic that will connect them is modelling your domain, aggregates, processes towards models that are useful, not necessarily correct. We’ll go through different domains & different requirements and we’ll try to focus not on the created model (it’s just an exercise) but rather on the modelling approaches and practices.

Put on your modeller’s gloves and safety glasses. It’s about time to crunch a few domains!

 

Event sourcing: making it functional (7)

TL;DR

It’s the seventh chapter of making event sourcing functional. In the last post we introduced the base class for aggregates capturing events and applying them on the state. In this entry we question this choice and make the final step to make our code more functional. Let’s go!

All entries in this series:

Question your choices

Let’s again take a look at the method responsible for receiving the gateway response

paymentstate

This is a void method. It’s not a pure function though. It “returns” its result by passing emitted events to the apply function. We could rewrite it in the following manner:

paymentstate

Now you can probably see, that there are two methods in there. One that emits, the event, possibly taking the state into consideration and the second that applies the event. We can make the first one even more generic and make it return IEnumerable of events.

PaymentState.png

Final revelation

Now you can see, that ReceiveImpl is the true implementation of the aggregate action, but it does not require the aggregate class at all! It gets the state, the action parameter and returns events! The ReceiveGatewayResponse is now just an infrastructure code that applies events, which is totally unneeded! We no longer have the Payment aggregate! All we have is just a set of functions that acts on the state basis, accepts some parameters and returns events. We can make it even an extension to call it in an easier way.

paymentstate

This pure function is so easy to test. You can test it using Given, When, Then with events, but you can test it with regular unit testing as well.

Now you can see that we were able to split the Payment aggregate into set of functions, that accept a state and other needed parameters returning a enumerable of events. Is there anything easier to test and to work with? For sure you need to pay some tax by introducing storing and applying events on the infrastructure side, but still it’s worth it, as we change aggregates, from being classes to just sets of simple functions.

Summary

I hope you enjoyed this series and that I was able to encourage you to see aggregates and event sourcing from a bit more functional point of view. All the commenters, thank you for providing valuable feedback. See you soon!

Event sourcing: making it functional (6)

TL;DR

In the last entry we changed the Payment aggregate to modify state by raising events. The events weren’t captured though. In this post, we’ll change the aggregate to enable recording of these changes.

All entries in this series:

Capturing events

The easiest way to capture events is to make them pass one additional method. We could provide one Apply method in the aggregate itself that beside applying the event it would. To make it usable in all the aggregates we could create a base class that would have this method. Let’s apply it to the Payment first

paymentstate

Now, we need the aggregate base class to hold the capture the applied events.

The base aggregate

We use the base class to track the changes and provide one point of entry to applying events. The dynamic is used to implement it fast. If you wanted to optimize, you could remove it by writing a custom dispatcher that calls directly a method from the derived aggregate.

paymentissued.png

When the action ends, a handler executing it calls GetEvents and gets all the events that were raised during this session. This enables you to write simple tests with a Given-When-Then approach and easily extract the changes for persistence purposes. On the other hand, we introduced the base class for the aggregate. What could be done more?

Summary

By introducing a base AggregateRoot class we enabled capturing all raised events. This simplified a little bit Payment aggregate itself, but introduced the base class. It’s time to move to the final part where we make it functional removing some code we’ve written so far.