Integrate AI into Java apps with Jakarta EE, CDI, MicroProfile Config, and LangChain4j. Build AI services from simple prompts to type-safe domain-driven interactions.
My goal here is to experiment with an alternative approach leveraging Java's tried-and-tested, robust functionalities that have been available since JDK 1.5.
Jakarta EE 12 introduces the Data Age of Enterprise Java with Jakarta Query, improved data access, and a unified model for cloud-native and polyglot systems.
Achieve zero-downtime deployments for Java applications on Kubernetes using rolling updates, readiness/liveness probes, and graceful shutdown strategies.
An AI-native analytics agent sits between users and the data warehouse, translating natural-language questions into governed SQL or Python workflows and dashboards.
CV data issues keep recurring. I built cv-quality — a toolkit to audit datasets, catch annotation errors, find mislabeled samples, and streamline labeling.
Delta often performs better for Spark workloads, while Iceberg tends to be stronger for a multi-engine environment. The right choice depends on your platform use case.
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