This blog provides a tutorial on how to integrate AI agents, specifically MCP agents, into your coding workflow using the DevoxxGenie plugin for JetBrains IDE.
Learn how to create a team chat application using Spring Boot and LangChain4j, featuring two AI assistants that communicate both with you and with each other.
This guide covers AI infrastructure, from hardware acceleration and model serving to monitoring and security, with tools, patterns, and strategies proven in production.
October 2, 2025
by Vidyasagar (Sarath Chandra) Machupalli FBCS
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Treat your security rules and compliance like tests that run every time you perform Terraform Plan. Learn how Policy-as-Code (PaC) allows you to do that.
This article demonstrates how we can run vLLM on Kubernetes for a centralized LLM serving engine that is production-ready and can be used by multiple applications.
From database bottlenecks to lightning-fast APIs, improve your app’s performance by implementing caching in Spring Boot with Redis and ElastiCache for microservices.
Build real-time, serverless dashboards by streaming events with EventBridge, OpenSearch, WebSockets, eliminating polling and delivering instant updates at scale.
Learn in this guide how we migrated to a GitOps workflow with Helm, OpenShift, and ArgoCD — lessons, pitfalls, and wins from real-world Kubernetes deployments.
Help shape our next research! Share your experiences with database types, cloud migration, security and observability practices, real-time analytics, and more.
Create a ReactJS component to match webcam faces to ID photos using AI, all client-side. Great for fast prototyping of secure apps like banking or event check-ins.
Build serverless WebSockets with Cloudflare Workers for routing and Durable Objects for state. This creates a scalable, low-latency real-time app at the edge.
In this guide, learn how to simplify data tasks with AI in Databricks SQL — summarize, translate, analyze sentiment, and mask PII with one-liner queries.
Build a real-time data mesh using Apache Iceberg for scalable, versioned table storage and Apache Flink for continuous stream processing across domains.
The focus of this article is to talk about the fast pace of change in models and the consequent updates we need to make to our LLM-powered solution design.
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