Event-Driven Analytics Pipeline
Event-Driven Systemhigh complexity
Deterministic topology derived from YAML knowledge entities. Nodes represent workloads, datastores, patterns, and risk components. Edges show typed relationships with propagation direction.
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Propagation Paths
Topology Graph5 nodes · 0 edges
Click a failure mode below to trace propagation
Workload
Datastore
Cache
Event stream
Pattern
Risk node
Risk path
Failure Propagation Trace
Topology Notes
- ·PostgreSQL logical replication slot feeds CDC connector (e.g. Debezium). Connector publishes per-table topics to Kafka.
- ·Kafka topic partition count should be set at creation based on the anticipated peak consumer parallelism. Increasing partitions later breaks keyed message ordering.
- ·Analytics consumers read from Kafka topics and write to a columnar analytics store (e.g. ClickHouse, BigQuery, Redshift). The analytics store is outside this scenario's scope.
- ·Replication slot must be monitored. Set a WAL retention alert at 50% of available disk. A failing consumer that is not consuming will accumulate WAL indefinitely.