Our system grew organically. Service A calls service B synchronously, B calls C, C calls D. When D goes down, the entire chain fails. With Apache Kafka, we moved to event-driven architecture.
The Problem: Synchronous Chains¶
In synchronous architecture, latency is additive and availability is multiplicative. With each added service, the system gets worse. Retry and circuit breaker help, but synchronous coupling is fragile.
Kafka as Event Bus¶
- Persistence — events on disk, configurable retention
- Ordering — guaranteed within partition
- Replayability — consumer can read from any offset
- Throughput — millions of messages per second
Event Sourcing Pattern¶
Instead of storing the current state of an order, we store every change as an event: OrderCreated, PaymentReceived, ItemShipped. The current state is a projection of these events. Complete audit trail, replay, temporal queries.
Kafka Connect¶
JDBC source connector reads changes from database, Elasticsearch sink connector indexes events. Configuration in JSON, no custom code.
Event-Driven Architecture is an Investment That Pays Off¶
The transition to Kafka wasn’t simple — we had to change our way of thinking. But the resilience, scalability and flexibility are worth the investment.
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