You run a Java product and want to add an AI feature. There are two real framework choices. Here is the honest comparison across providers, RAG, tools, Spring fit, and the one thing that decides it for most teams.
Which password hash actually protects you, what the OWASP Password Storage Cheat Sheet recommends for Argon2id, scrypt and bcrypt, and measured numbers for tuning each one to a verification time your login path can absorb.
Do Java virtual threads make a Spring Boot app faster? I load-tested the same app both ways on real AWS hardware. The honest answer: below saturation they do nothing, on CPU-bound work they do nothing, and where they win on blocking I/O, a properly tuned platform pool matches the throughput. The real case for virtual threads is not raw speed, it is having no pool to tune and a cheaper thread.
AWS says Graviton gives up to 40 percent better price-performance. I put the same Spring app on same-rank Intel, AMD, and Graviton instances and measured it. It is true, I got 43 to 60 percent, but the reason is not that Graviton is faster. It is cheaper, and same vCPU does not mean same cores.
Most breaches are not a code bug. They are a public bucket or an over-broad role nobody reviewed. Here is how to use AI for an expert first pass over your cloud, identity, and infrastructure config, and the tools and guardrails that keep it honest.
The API price page says a few dollars per million tokens and looks cheap. That is not what your AI feature will cost. Here is the real formula, a worked example, the levers that cut the bill, and when self-hosting actually pays.
