Kafka ana amfani da shi a yawancin abubuwan da ke da alaƙa da babbar adadi, ainihi, ko yaɗe-yaɗen bayani — aika da saƙo, tuɓe bayani, gida mai halittar abubuwa, sarrafa yaɗe, tara awalwalen, da kari. Fahimtar abubuwan da aka ba da alaƙa yana bayyana inda Kafka ya dace.
Abubuwan da aka ba da alaƙa
✓ MESSAGING / event streaming → decoupled pub/sub between services at scale
✓ DATA PIPELINES / integration → reliably stream data between systems (databases, services,
data warehouses, analytics) — a central data "backbone"
✓ EVENT-DRIVEN ARCHITECTURE → services emit and react to events; event sourcing (events as
the source of truth)
✓ STREAM PROCESSING → real-time processing/analytics on event streams (Kafka Streams, Flink)
✓ LOG AGGREGATION → collect logs/metrics from many services into one stream
✓ ACTIVITY TRACKING → user activity, clickstreams, telemetry at high volume
✓ CHANGE DATA CAPTURE (CDC) → stream database changes to other systems
✓ METRICS / monitoring → real-time metrics collection and processing
