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Confluent integration
Bring Confluent events into Uplyst's business model, connecting governed streams with the customers, assets and operations they describe.
- Confluent streamsOperational events carried through Kafka
- Schema RegistryAvro, Protobuf and JSON Schema definitions
- Uplyst business modelEvents connected to the entities and processes they describe
Business context for Confluent streams
Confluent provides data streaming capabilities built around Apache Kafka. Uplyst connects approved streams to its intelligence layer, linking events with enterprise records and the relationships between them.
Where Schema Registry is used, its definitions describe how records are decoded. Uplyst's business model adds the context of the customer, transaction, asset or process represented by the event.
- Transport
- Topics, partitions and consumer groups
- Structure
- Schema formats and compatibility policies
- Business context
- Entities, relationships and process state
Schema formats and evolution
Schema Registry supports Avro, JSON Schema and Protobuf. Compatibility policies help producers and consumers continue exchanging records as schemas change.
A compatible schema can still change business meaning. Units, identifiers and status definitions are part of the mapping to Uplyst's business model, alongside the structure of each event.
Kafka and Schema Registry access
Confluent Cloud provides service accounts, API keys and authorization controls for its resources. Access to Kafka records and access to Schema Registry are configured for the resources the integration needs.
The connection depends on the selected Confluent Cloud or Confluent Platform environment, its network configuration and the permissions of the workload identity.
- Kafka
- Topic and consumer permissionsAccess to the operational event stream
- Schema Registry
- Schema permissionsAccess to the definitions needed to decode events
Continuity across event versions
Schema references and source event identifiers help connect historical records with current business entities. An older event can still describe the same payment, customer or asset after an application changes its schema.
This continuity supports investigations that span product releases, source migrations and replayed event history.
From stream activity to business exceptions
An event may be delayed by connectivity, rejected by its schema or incomplete for a business process. Connecting those conditions with the affected records gives operational teams a clearer view of what needs attention.
Confluent streams are useful for customer activity, payment processing and supply chain events where several applications contribute to the same business outcome.
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