Converging processes


Completing an order is not an easy process. A payment gateway may not accept payments for some time. A coffee can be spilled all over the book you ordered and a new one needs to be taken from a storage. Failures may occur in different moments of the pipeline, but still your ordered is received. Is it a one process or multiple? If one, does anyone takes every single piece into consideration? How to ensure that eventually a client will get their product shipped?

Process managers and sagas

There are two terms used for these processors/processes. They are process managers and sagas. I don’t want to go through the differences and marketing behind using one or another. I want you to focus on a process that handles an order and that reacts to three events:

  • PaymentTimedOut – occurring when the response for Payment was not delivered before the specific timeout
  • PaymentReceived – the payment was received in time
  • OrderCancelled – the order for which we requested this payment was cancelled

What messages will this process receive and in which order? Before answering, take into consideration:

  • the scheduling system that is used to dispatch timeouts,
  • the external gateway system (that has its own SLA),
  • messaging infrastructure

What’s the order then? Is there a predefined one? For sure there isn’t.


Your aim is to provide a convergent process. You should review all the permutations of the process inputs. Being given 3 types of input, you should consider 3! = 6 possibilities. That’s why building a few processes instead of one is easier. You can think of them as sub-state machines that later, can be composed into a bigger whole. This isn’t only a code complexity, but a real mental overhead that you need to design against.


Designing multiple small processes as sub-state machines is easier. When dealing with many events to react to, try to extract smaller state machines and aggregate them on a higher level.


Event sourcing: making it functional (7)


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!

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Question your choices

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


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:


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.


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.


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.


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)


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


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.


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?


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.

Event sourcing: making it functional (5)


After defining events of the Payment aggregate it’s time to move on and work on applying these events.

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To apply events, the state of Payment will be extracted to a separate class. This should be a familiar pattern to all event sourcing practitioners, but let me show the code for clear understanding of our approach


How to construct the state

  1. There are no public setters. The state has readonly properties.
  2. All events are applied with an Apply method.
  3. The only way to change the state is to apply an event.
  4. No Apply throws an exception. The event has already happened and the state is just an accumulator of the changes.

New Payment Aggregate

The Payment aggregate now can be transformed to use this state, by removing all the state changes and raising/applying events in these places:



We know how to extract a state from the aggregate and apply all the events. Although Payment uses events, it does not store them in any form nor allows accessing them for processing. In the current shape the Payment isn’t much different from the previous version. We extracted a few event classes and the state, but we still can’t treat events as the first class citizen. we need to move one step further and we will do it in the next blog post.

Zapraszam na szkolenie z EventSourcingu: Warszawa, 16-03-2017

Zapraszam Was na moje szkolenie otwarte dotyczące EventSourcingu w .NET!

Tematem zdarzeń zajmuję się od dawna i nastał czas aby podzielić się tą wiedzą z Wami w formie szkolenia. Rejestracja odbywa się przez system Evenea na tej stronie i tam też znajdziesz wszystkie informacje.

Strona szkolenia

Jeżeli wahasz się i chciałbyś zobaczyć mnie w boju przed szkoleniem, zapraszam na moją jutrzejszą prezentację na Warszawskiej Grupie .NET, pt.

Keep Its Storage Simple Stupid,
an opinionated guide to NoSQL with Windows Azure Storage and Event Sourcing

Podczas niej omówię pewne aspekty projektu w modelu SaaS, w którym zastosowałem zdarzenia i Event Sourcing do obsłużenia złożonej domeny biznesowej. Dla uczestników spotkania przygotowałem też mały prezent związany ze szkoleniem 😉

Do zobaczenia!

Event sourcing: making it functional (4)


In the last entry we defined the aggregate implementation that we’ll work on. Let’s move forward and make it an event sourced aggregate.

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The first and the most important event, is the fact of issuing the payment itself. Let’s define it in the following way:


The event contains all the data provided to the constructor of the payment aggregate in the past.

The next one is raised and applied when the payment is processed successfully. Let’s make it a class without any members. We just want to record a notion of success.


The last but not least is the one raised in case of the error. We make the errors explicit in here as we’d like to react to payments failure. One could model it in a different way, providing one event class, but then again, just follow this take on the payment problem.



We discovered three meaningful events:

  1. PaymentIssued
  2. PaymentProcessedSuccessfully
  3. PaymentProcessedWithFailure

In the next entry we will start rewriting the aggregate to use these.

Event sourcing: making it functional (3)


We’re on our journey to move from event sourcing oriented on the aggregates to a more functional approach. In the first entry, we went through some of the DDD building blocks. In the second, we defined an interface of the aggregate that we’ll work with. Before, going to the event sourced approached, let’s go through the aggregate’s implementation, somehow related to the Blue Book approach, without event sourcing.

All entries in this series:

Payment aggregate!

Let’s dive straight into the code


We can see that a payment is issued for a user, with a specified payment method and a given amount of money. Yes, it’s simplistic, but bear with me, and follow its implementation for a while.

The other method is responsible for receiving the gateway response and applying it onto the aggregate. The status and the description are updated accordingly.

So far so good? In the next entry we’ll make this aggregate event sourced!