AI Workflows with Kafka and Modern Architectures
summary
Shows a working stack: Apache Kafka with Streams API and ksql handling millions of messages with end to end latencies claimed under 10 ms, Kafka Connect moving data into models and reporting up to 50% scalability improvement, secure proxies enforcing encryption and access control with negligible added latency, a zero trust pattern applied to every data call, and a concrete case where realtime inventory ML reduces stockouts and excess inventory so the pipeline actually delivers live decisions.
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chapters (9)
- 0:00Introduction to AI and Network Security
- 1:32The Growing Need for Real-Time AI
- 4:40Key Features of Apache Kafka for AI Workloads
- 8:19Real-Time AI Use Cases with Kafka
- 11:52Securing AI Data Pipelines with Secure Proxies
- 13:42Integrating AI Workloads with Kafka Connect
- 15:35Implementing Zero Trust Architecture with Kafka
- 17:05Best Practices for Building Secure AI Pipelines
- 18:18Conclusion: Enhancing AI Systems with Kafka
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