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Model Translation

Written by Oleksandr Sydorenko

Updated at May 5th, 2025

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A bounded context is the boundary of a model—a ubiquitous language. As you learned in Chapter 3, there are different patterns for designing communication across different bounded contexts. Suppose the teams implementing two bounded contexts are communicating effectively and willing to collaborate. In this case, the bounded contexts can be integrated in a partnership: the protocols can be coordinated in an ad hoc manner, and any integration issues can be effectively addressed through commu‐ nication between the teams. Another cooperation-driven integration method is shared kernel: the teams extract and co-evolve a limited portion of a model; for exam‐ ple, extracting the bounded contexts’ integration contracts into a co-owned repository.

In a customer–supplier relationship, the balance of power tips toward either the upstream (supplier) or the downstream (consumer) bounded context. Suppose the downstream bounded context cannot conform to the upstream bounded context’s model. In this case, a more elaborate technical solution is required that can facilitate communication by translating the bounded contexts’ models.

This translation can be handled by one, or sometimes both, sides: the downstream bounded context can adapt the upstream bounded context’s model to its needs using an anticorruption layer (ACL), while the upstream bounded context can act as an open-host service (OHS) and protect its consumers from changes to its implementa‐ tion model by using an integration-specific published language. Since the translation logic is similar for both the anticorruption layer and the open-host service, this chap‐ ter covers the implementation options without differentiating between the patterns and mentions the differences only in exceptional cases.

The model’s translation logic can be either stateless or stateful. Stateless translation happens on the fly, as incoming (OHS) or outgoing (ACL) requests are issued, while stateful translation involves a more complicated translation logic that requires a data‐ base. Let’s see design patterns for implementing both types of model translation.

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