Dhaval Shah
Cloud Native Architect | Fintech Platforms at Scale
Vadodara, India
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I design and scale high-throughput, low-latency fintech platforms in highly regulated environments. With 21+ years, I've built cloud-native systems on Azure and Kubernetes using Java 21, Spring Boot, Reactive Programming, Kafka, and Redis - with a strong focus on event-driven architecture. I combine deep hands-on engineering with technical leadership to help teams build platforms that are fast, resilient, and compliant.
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From REST APIs to AI Agents: Designing AI-Native Enterprise Systems in Java
Track - Enterprise Java
Duration - 45 mins
Abstract -
So far we have been building enterprise Java based systems that assumed one thing - client already knows exactly what to ask for and that too in exactly what order. REST allowed us to have clean contracts, predictable calls, and a REST client did the orchestration of the workflow. But with AI, enterprise workflow doesn't fit that mold anymore.
This talk explains what an "AI agent" actually is - a reasoning engine, a set of tools, memory, and a plan-act-observe loop with due respect to architectural standards that we as Java community members hold ourself responsible for.
Key Takeaways -
- What an AI agent exactly is and how it differs from a REST endpoint
- Reference architecture for building AI native systems on JVM
- Non-negotiable architectural considerations for running agents in real enterprise systems
Beyond Throughput : Parallel Processing in Java - Reactor vs. JDK with Virtual Threads
For high-concurrency Java applications, choosing the right concurrency model is pivotal. This talk delves into a comparative analysis of traditional multi-threading, reactive programming using Spring Reactor and Project Loom's virtual threads. By examining real-world scenarios involving IO-intensive operations, we'll explore the performance trade-offs and resource utilization of each approach.
Dhaval Shah
Cloud Native Architect | Fintech Platforms at Scale
Vadodara, India
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