Définition
Apache Kafka is often used in data and AI infrastructure when there is a need to process a continuous stream of events: clicks, transactions, logs, messages, telemetry or user actions. For models, this is a source of fresh data, events for monitoring and signals for automation.
Exemple
The recommendation service receives product view events through Kafka and updates user attributes almost immediately.
Pourquoi c'est important
The term is important not as an AI model itself, but as part of the infrastructure that feeds data to AI systems and helps build scalable products.
Fonctionnement
Kafka receives events from producers, stores them in topics, and serves them to consumers. Multiple services can read the same data stream independently of each other.
Où c'est utilisé
- streaming analytics
- user events
- monitoring and MLOps
Limites
Kafka requires configuration, monitoring, and understanding of distributed systems. For small projects it may be overkill.
FAQ
Why is “Apache Kafka” useful to know?
The term is important not as an AI model itself, but as part of the infrastructure that feeds data to AI systems and helps build scalable products.