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.
Imagine querying your domain using simple attribute filters, without building queries or learning a query language, and getting the result back as JSON.
SonarQube automatically detects bugs and security in Java applications through static code analysis to improve code quality and enforce secure coding practices.
Learn how sql-flex-query lets you write once, run anywhere — with full TypeScript support and zero runtime overhead. Support SQL queries for multiple databases
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