Organizing VCS Repositories by Domain: An Effective Alternative for Mono and Multi Repos

Domain repositories provide an alternative to monorepositories and multi-repositories for organizing code. This approach balances the benefits of both while mitigating their disadvantages. By isolating code by domain, domain repositories can improve collaboration, reduce cognitive load, and scale more effectively as the business grows. While there are potential downsides to consider, such as difficulties in splitting or merging domains, the benefits make domain repositories an attractive option for many software development projects.

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Bounded Context patterns: Fan-out Specification Context

One of the challenges of designing distributed systems is balancing the local and global complexity. In some cases, we might want to reduce the local complexity (and cognitive load) by splitting a single system into multiple smaller ones, that are going to be loosely coupled.

That often brings a problem of managing the specification of behaviours of the subsystems in the context of the whole system. Usually, we want to have the specification consistent between the subsystems, but at the same time keep them loosely coupled and independent.

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EventStoreDB vs Kafka

There is quite a lot of confusion in the community with regards to EventStoreDB and Kafka - especially when it comes to event sourcing. Developers not familiar with both products are having a hard time deciding which technology they should use, how do they compare and what are the trade-offs that they will have to make.

In this article, you will learn what the two solutions offer, how to use them effectively, and when to use one over the other. In order to do that, we first need to agree on the definition of event sourcing and requirements that the solution should meet.

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Event Sourcing: Snapshotting

In an Event Sourced system, the current state of an aggregate is usually reconstituted from the full history of events. It means that before handling a command we need to do a full read of a single fine-grained stream and transport the events over the network. For a well-designed aggregate, it’s usually not a problem as it’s lifecycle is bounded to a specific time period and the number of events doesn’t grow indefinitely. But what if our design isn’t optimal, or we have some outliers that are requiring thousands of events to be transported every time we want to handle a command?

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Event Sourcing: Aggregates vs Projections

One of the topics that came up a few times (and I noticed quite a number of searches for it) is how the Aggregates and Projections differ or relate to each other. The reason for this confusion is that some parts of the implementation logic are very similar - in particular, the current state of an Aggregate derived from the event log. In this blog post, we will explore the differences and look at some examples.

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