Harnessing Real‑Time Data Streams for AI & Analytics with Java Spring Boot & Apache Kafka

About the Session

In a landscape where timely insights can make or break business decisions, many organizations struggle to feed AI models and analytics dashboards with fresh, reliable data. In this talk, I will present an approach to building a real‑time event‑driven platform using Java Spring Boot microservices and Apache Kafka. I will walk through on exploring how to design Spring Boot services that produce and consume Kafka topics at scale, enforce data quality via schema registries, and automate deployments with Helm charts, Terraform modules, and GitOps on Kubernetes/OpenShift. You’ll also see how to embed robust security at every layer leveraging HashiCorp Vault for dynamic secrets, OAuth2/Azure AD for authentication, and RBAC for zero‑trust governance. By session’s end, you will be able to understand the best practices for monitoring, scaling, and tuning low‑latency data streams so your teams can power AI and analytics projects from day one.

Speaker

Aravind Raghu

HYR Global Source