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Pramod Kumar
Pramod Kumar

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🚀 Building Production-Ready AI Systems with Spring Boot 4 + JDK 21 (Part 2)

#springboot #ai #systemdesign #java

Most AI backends work… until they don’t.

You ship a simple API:

POST /ai → returns response
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Everything looks fine — until:

  • 💸 costs explode (same prompts repeated)
  • 🐢 responses feel slow
  • 🚨 bots spam your API
  • 🤖 answers lack real context

In Part 1, we built a scalable backend.

In this post, we turn it into a real AI system using:

  • 🔴 Redis (distributed cache)
  • 🌊 Streaming (SSE)
  • 🚦 Rate limiting
  • 🧠 RAG (context-aware AI)

🔗 Full Detailed Guide (Medium)

👉 Read the full 6-min deep dive with diagrams & full code:
👉 [Add your Medium link here]

🧱 1. Redis — Stop Burning Money 

@Cacheable("ai-cache")
public String generate(String prompt) {
    return aiClient.generate(prompt);
}
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👉 Shared cache across instances → massive cost reduction

🌊 2. Streaming — Real-Time UX 

@GetMapping(value = "/stream", produces = MediaType.TEXT_EVENT_STREAM_VALUE)
public Flux<String> stream(String prompt) {
    return Flux.create(sink -> {
        Thread.startVirtualThread(() -> {
            String response = aiService.generate(prompt);
            for (String token : response.split(" ")) {
                sink.next(token);
            }
            sink.complete();
        });
    });
}
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👉 ChatGPT-like experience ⚡

🚦 3. Rate Limiting — Protect Your API 

if (bucket.tryConsume(1)) {
    chain.doFilter(request, response);
} else {
    response.setStatus(429);
}
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👉 Prevent abuse + control cost

🧠 4. RAG — Context-Aware AI 

String prompt = """
Answer using context:
%s

Question: %s
""".formatted(context, question);
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👉 AI becomes smarter, not just reactive

🔁 Final Architecture 

Client
  ↓
Rate Limiter
  ↓
Service
  ↓
Redis + RAG + Streaming
  ↓
AI Client
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🔥 What You Built

✔ Distributed cache
✔ Streaming API
✔ Rate-limited system
✔ Context-aware AI

🏁 Final Thought

Most developers build:

Controller → AI API
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You’re building:
👉 AI systems that scale

🔗 Full Article (Recommended)

👉 Part 1: https://medium.com/stackademic/production-ready-ai-with-spring-boot-4-jdk-21-using-webclient-part-1-b609dda54d8c

👉 Part 2: https://medium.com/@pramod.er90/scalable-ai-systems-with-redis-streaming-rag-spring-boot-4-jdk-21-part-2-983e505b16da

💬 Follow for Part 3: Kafka + Observability + Multi-Tenant AI Systems

Top comments (1)

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pramod_kumar_0820 profile image
Pramod Kumar •

“What’s the biggest challenge you’re facing while scaling AI APIs — cost, latency, or architecture?”