Persistence

MicroDCS uses Redis to persist operational state needed for delivery coordination, job tracking, and multi-instance processing patterns. This page summarizes the persistence requirements behind that choice.

Persistence Requirements

The dataclasses used for OPC UA Job Management need to be persisted in a form that supports schema evolution and can store nested structures without excessive mapping overhead. A document-oriented persistence approach fits those requirements well.

The framework also needs persistence support for CloudEvent deduplication and for coordinating state publication so that changed variable values are emitted by a single publisher in multi-instance scenarios.

Redis

MicroDCS stores dataclasses in Redis JSON. The associated dataschema value is written to an additional _dataschema field and is derived from the model Config class during serialization.

For the OPC UA Job Management implementation, Redis eventing is used to coordinate a single-instance publisher from a multi-instance receiver and event-publisher setup. Events are published directly to MQTT, while state variables are published through the OPC UA pub-sub mechanism so unchanged values do not need to be sent repeatedly.

• Redis course notes
• Redis Labs Python developer path
• RedisVL hash vs JSON guide - JSON fits the nested model structure used by MicroDCS
• Redis OM for Python: globally unique primary keys - not required here because MicroDCS does not generate new primary keys through Redis OM