Messaging Systems

Message Translator

Translate from one representation into another at an integration boundary so connected applications can evolve without sharing the same data shape.

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The problem
How can systems using different data formats communicate with each other using messaging?
Adapted from Enterprise Integration Patterns under CC BY 3.0. The visualization and explanatory content on this page are original GateSift material.
Original GateSift visualization

How Message Translator works

The message representation changes while its business meaning is preserved or enhanced.

Source format
Message Translator
Target format
1

Receive a message in the producer's structure or envelope.

2

Apply Message Translator to reshape, enrich, wrap or normalize the content.

3

Deliver a representation that the receiving system can understand.

GateSift explanation

What this pattern helps you decide

Translate from one representation into another at an integration boundary so connected applications can evolve without sharing the same data shape.

What happens when processing fails or the same message is delivered twice?
Where does state, correlation or routing configuration live?
How will operators trace the message and understand the decision path?
Common Azure implementations

Where you may see it

  • Liquid, XSLT or Data Mapper transformations
  • Azure Functions mapping
  • BizTalk maps
GateSift relevance

How the analyzers can surface it

  • APIM set-body transformations
  • BizTalk transforms and pipelines

Pattern detection is contextual. GateSift should present these as architectural signals, not claim a pattern is implemented solely because one policy statement or adapter exists.

Source, licence and attribution

The pattern name and selected problem statement are adapted from Enterprise Integration Patterns by Gregor Hohpe and Bobby Woolf under CC BY 3.0. GateSift summaries, Azure mappings, analyzer guidance and diagrams are original. No endorsement by the original authors is implied.

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