Transfer layer
The combination of the system mapping DSL and the pattern library that enables learned operational intelligence to be applied to a new infrastructure environment without retraining. When pointed at a new environment, only a SystemMapping is required; the pattern worker immediately begins matching incoming primitives against the existing pattern library.
The transfer layer is the answer to the question of whether operational AI has to start from scratch every time it encounters a new infrastructure environment. Traditional monitoring rules are environment-specific: a rule written for a Kafka cluster at one company does not transfer to a different cluster at another company because the metric names, thresholds, and alert conditions differ. The transfer layer breaks this coupling by separating what is learned (the pattern library, expressed in vendor-agnostic operational primitives) from what is environment-specific (the system mapping, which translates vendor metrics into primitives). The pattern library carries all the confidence history, intervention rankings, and causal relationships that have been learned across every environment the system has operated in. The system mapping is the thin, environment-specific adapter that requires an operator to specify, but once specified, the full pattern library activates immediately. A pattern that achieves 0.92 confidence for backpressure management in environment A starts at 0.92 in environment B the moment a system mapping is provided - the confidence history transfers because the underlying pattern is vendor-agnostic.