Event Streaming Kafka Event Hub Architecture

Build real-time event fabrics for process orchestration, telemetry pipelines, and resilient enterprise integration.

Event streaming architecture scope

Enterprise event streaming architecture defines topic strategy, schema governance, replay controls, and processing boundaries across producers and consumers. Kafka and Event Hub patterns support high-throughput real-time data movement, but effectiveness depends on event contract discipline and operational controls.

Event design and integration patterns

Teams should define event taxonomies, partitioning strategy, ordering expectations, and dead-letter workflows before scaling publishers. Architecture should separate mission-critical process events from analytical telemetry streams to preserve reliability and recovery posture.

Related pathways: Integration and API Hub, Data Integration Hub, and integration fabric architecture.

Observability and governance

Streaming platforms require end-to-end monitoring for lag, throughput, consumer health, and contract compliance. Governance models should define ownership and SLO accountability for event domains so cross-team dependencies remain manageable.

Cross-stack alignment: iPaaS MuleSoft Boomi Celigo Architecture and API Management Kong Apigee Architecture.

Hub pathways

Return to Integration and API taxonomy, continue to Data Integration taxonomy, or review Cloud Infrastructure pathways.