Jakarta Data in Jakarta EE 12 M2 extends the EE 11 repository model with stateful operations, unified querying, and SQL/NoSQL alignment for domain-centric data access.
This article explains how to build a self-healing observability system with AWS Bedrock AgentCore using AI agents to analyze and remediate infrastructure issues.
MCP is production-ready for LLM-to-tool integration; A2A enables emerging multi-agent collaboration. They complement, not compete, and neither replaces Spark or Airflow.
The blog introduces you to the four pillars of observability, AWS and Azure cloud-native services, and ROI to help in architects and engineer's quest for system clarity.
This article examines how integrating AI into the software development lifecycle (SDLC) is enabling teams to move from MVPs to large, resilient systems.
AI Agents perceive, reason, plan, and act autonomously using LLMs. This article breaks down the core components that power every agent and shows you how to build one.
How cloud-native microservices transform insurance analytics by enabling scalability, real-time processing, and seamless modernization of legacy platforms.
Feature flags and safe rollouts with Azure App Configuration for large SPA teams, hands-on setup, core principles, TypeScript code for backend and frontend.
AI enhances Workday integrations by improving mapping, testing, and monitoring, but it fails when used without human oversight, domain expertise, and strong governance.
Build long-running workflows by separating orchestration from execution, persisting state, and using events or callbacks to pause and resume without holding compute.