Serverless functions can trigger instantly when new data arrives in streams or databases. Each function processes a slice of data independently, enabling parallel analytics at scale. There’s no need to keep analytics servers running continuously. Results can be generated in near real time, even during massive data spikes. This makes serverless ideal for monitoring, fraud detection, and live dashboards.
Organizations gain faster insights from their data. Decisions can be made in real time.
This responsiveness enables smarter systems that adapt instantly to changing conditions.
Serverless functions can analyze streaming data as it arrives.
[Apache Kafka Documentation, kafka.apache.org]