Identify the payload or state that must survive beyond the current processing attempt.
System Management
Message Store
Capture selected message metadata or payload references in a separate store for search, reporting, audit and replay without changing the primary flow.
How can we report against message information without disturbing the loosely coupled and transient nature of a messaging system?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 Store works
The integration persists data or processing state so it can be recovered, deduplicated or retrieved later.
Message or payload
Message Store
Durable reference / state
Apply Message Store to persist, reference or verify that state.
Retrieve or reuse the stored information when the flow continues or recovers.
What this pattern helps you decide
Capture selected message metadata or payload references in a separate store for search, reporting, audit and replay without changing the primary flow.
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?
Where you may see it
- Application Insights or Log Analytics
- Cosmos DB audit store
- Blob archive
How the analyzers can surface it
- Logging and archive endpoints
- Payload retention risks
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.