Previously we spend some time preparing the code to support multiple kinds of events and data, rather than just supporting blog posts. In this part we’ll add user accounts, together with the required authentication and authorization code. We’ll again use event sourcing and the memory image to keep track of all users and currently active sessions. But the biggest changes to the application are related to security, and authorization in particular. It turns out event sourcing allows for an additional layer of authorization which allows us to whitelist any change a particular user is allowed to make.
Continue reading Simple event sourcing – users, authentication, authorization (part 6)
In the previous part we added blog post comment functionality. In this part we’ll do some refactoring and change the memory image implementation to automatically retry domain logic on optimistic locking conflicts, giving us a simplified form of transactions. We’ll also change the event store to support multiple types of event streams in a single event store.
Continue reading Simple event sourcing – refactoring and transactions (part 5)
After our deep dive into a Redis event store implementation we’re now getting back to actually adding functionality to the blogging application. Like the Getting started with Rails guide we’ll add the capability to add comments to blog posts. Adding this functionality is straightforward, but it will require us to look into resolving conflicts when multiple people make modifications to the same blog post or comment concurrently.
Continue reading Simple Event Sourcing – conflict resolution (part 4)
In the previous part we developed a fake event store for our blogging application. This event store just kept all events in-memory, making it unsuitable for production use. But it did allow us to adapt our application to using an event store, and let us work out the details of the event store interface without having to worry about an actual persistence mechanism.
In this part we’ll develop an event store implementation on top of Redis, a key-value store with support for additional data structures (such as lists and hashes), publish/subscribe, and transactions. If you’re more interested in adding new application functionality, you can safely skip this part and go to part 4 – conflict resolution.
Continue reading Simple event sourcing – Redis event store (part 3)
In the first part of this series we developed a simple blogging application that uses event sourcing to keep track of all changes made by the users. However, we did not yet write these events to durable storage. This means all data is lost when the application is restarted, which is clearly not acceptable. Saving and restoring events will be the responsibility of the event store, which we’ll start implementing in this part. But before we get to actually writing events to disk, we must first tackle the problem of maintaining data consistency when using event sourcing.
Continue reading Simple event sourcing – consistency (part 2)
This is the first part of a series on building an event sourced application. We’ll build a simple blogging application (inspired by the Ruby on Rails “Getting Started” tutorial), so the domain should be familiar. This allows us to focus on implementing a memory image based architecture using event sourcing. Another goal is to show that this kind of architecture is not more complex (and arguably, simpler) than those implemented by traditional database centered applications. The example code is in Scala using the Play! web framework, but should be understandable enough if you come from a Java (or similar) background.
Continue reading Simple event sourcing – introduction (part 1)
Play! is a web framework for Java and Scala. Play promises to bring the developer productivity of web frameworks like Ruby on Rails to the Java and Scala languages. Of course, it wouldn’t make much sense just to copy Rails. So Play adds its own spin: Play 2.0 is fully statically type checked, giving the developer quick feedback when something doesn’t make any sense.
Now that Play 2.0 is getting closer to final release I took some time to dive in. Here are my first impressions, using the Scala APIs.
Continue reading Play! 2.0: A First Impression
While implementing a simple event store for an example application I needed to serialize JSON data to binary arrays and turn those bytes back into the original JSON. Obviously, that’s a piece of cake!
Continue reading Serializing strings, Unicode, and randomized testing using ScalaCheck
This is the fifth and final part of this series. In this last part we’ll reduce the boilerplate code related to handling events and as a bonus we’ll also make handling validation a bit nicer. But before we take a deep dive into the code, let’s consider the design of the last three Invoice implementations.
Continue reading Towards an immutable domain model – monads (part 5)
We’re already on the fourth part of this series. In this part we’ll explore how we can improve on the original design now that the invoice is immutable.
Continue reading Towards an immutable domain model – believe the type (part 4)