Here is short info about post: The rapid adoption of Arm64 (also known as AArch64) architecture in cloud environments has changed how Java applications are built, deployed, and optimized. Major cloud providers now offer Arm-based instances that promise lower costs, better energy efficiency, and impressive performance per watt. However, simply running an existing Java application on Arm64 does not guarantee optimal performance. Java applications require deliberate tuning at multiple layers—JVM configuration, garbage collection, JIT compilation, container images, and application code itself—to fully leverage Arm64’s strengths. This ... How To Optimize Java Applications For Arm64 In The Cloud

Here is short info about post: Enterprise Resource Planning (ERP) systems sit at the heart of most large organizations. Decades-old SAP, Oracle, PeopleSoft, JD Edwards, and custom-built ERPs still manage finance, supply chain, HR, and manufacturing workflows. While these systems are mission-critical, they were never designed to interact natively with modern AI-driven cloud platforms, microservices, or orchestration layers. At the same time, enterprises are aggressively adopting cloud-native architectures, generative AI, and automation platforms to improve decision-making, reduce operational overhead, and enable real-time intelligence. The challenge lies ... Hybrid RAG Architecture for Secure Integration of Legacy ERPs with Cloud Orchestration

Here is short info about post: Site Reliability Engineering (SRE) has traditionally focused on keeping software systems reliable, available, and performant. Concepts such as Service Level Indicators (SLIs), Service Level Objectives (SLOs), and error budgets are well understood for classic web services: uptime, latency, and error rates. However, AI/ML-powered systems introduce an entirely new reliability dimension. A model can be up and responding with low latency, yet still be unreliable because its predictions are inaccurate, stale, biased, or based on outdated data. In AI/ML systems, reliability ... How To Build SRE Error Budgets For AI/ML Model Accuracy, Data Freshness, Uptime, And Fairness

Here is short info about post: The arrival of virtual threads in Java has fundamentally changed how Spring Boot applications can approach concurrency. With Project Loom, developers can now create millions of lightweight threads without the crippling overhead traditionally associated with platform threads. This shift promises simpler mental models, cleaner code, and dramatically improved scalability. However, this new power introduces a subtle and dangerous misconception: virtual threads eliminate the need for concurrency limits. They don’t. Virtual threads make thread creation cheap, but they do not make ... How AI Can Help Set Safe Concurrency Limits for Spring Boot Virtual Threads

Here is short info about post: Static Application Security Testing (SAST) has long been a cornerstone of secure software development. By analyzing source code without executing it, SAST tools can identify vulnerabilities early in the development lifecycle. However, traditional SAST solutions are notorious for producing a large number of false positives—warnings that flag code as vulnerable even when it is safe in real execution contexts. These false positives slow down development, erode trust in security tools, and distract engineers from real risks. Recent advances in program ... How Graph Neural Networks and Code Property Graphs Analyze True Data Flow to Eliminate SAST False Positives

Here is short info about post: Scaling a Software-as-a-Service (SaaS) application is one of the most critical and complex challenges engineering teams face. Unlike traditional software, SaaS platforms must support continuous growth in users, data, traffic, and feature complexity—all while maintaining performance, reliability, and security. Poor scaling decisions can lead to outages, slow response times, ballooning infrastructure costs, and unhappy customers. This article explores the best technical strategies for scaling SaaS applications, focusing on architecture, infrastructure, data management, and code-level practices. Each strategy is explained with ... The Best Technical Strategies for Scaling SaaS Applications

Here is short info about post: Building intelligent systems today is less about inventing entirely new algorithms and more about orchestrating intelligence—combining models, tools, decision logic, and architectural patterns into systems that can reason, adapt, and scale. This article dives deep into how you can design such systems by exploring ToolOrchestra, Mixture of Experts (MoE), and other proven AI patterns. The goal is practical understanding. We will look at why these patterns exist, how they work together, and how to implement them using clear coding examples. ... How To Build Intelligent Systems By Exploring ToolOrchestra, Mixture Of Experts (MoE), And Other AI Patterns

Here is short info about post: Serverless architectures have evolved far beyond simple stateless compute. Modern workloads demand elastic scaling, predictable database performance, and minimal operational overhead. AWS Lambda, when combined with Aurora and its newer Limitless Database capabilities, offers massive scalability — but only when the components are aligned correctly. This article explores how AWS Lambda, RDS Proxy, and the Aurora Limitless Router can be composed into a cohesive, scalable, and resilient architecture. We will go beyond surface-level integration and focus on connection management, routing ... How To Align AWS Lambda, RDS Proxy, And Aurora Limitless Router Into A Cohesive Architecture

Here is short info about post: Optical Character Recognition (OCR) has quietly moved from a niche technology used for digitizing books into a foundational component of modern data platforms. Invoices, contracts, forms, reports, medical records, receipts, and handwritten notes are increasingly scanned or photographed before being processed by software systems. The challenge is no longer how to extract text, but how to treat OCR-derived text as a reliable, repeatable, and governable data source. Unlike traditional structured sources such as databases or APIs, OCR text is inherently ... Treating OCR Text As A First-class Data Source

Here is short info about post: In modern identity systems, Verifiable Presentations (VPs) are a core building block for secure, privacy-preserving interactions between a holder (often a mobile wallet) and a verifier (typically a backend service). When these interactions involve sensitive claims, the security bar becomes significantly higher. Plain JSON over HTTPS is no longer enough. To address replay attacks, payload tampering, verifier impersonation, and data leakage, production-grade VP flows often combine: JAR (JWT Authorization Request) signed requests Encrypted VP responses Certificate-based verifier identity validation This ... How To Approach JAR Signed Requests, Encrypted Responses, And Certificate-Based Verifier Identity For VP Flows With Spring And Android

Here is short info about post: Artificial Intelligence agents are no longer theoretical constructs confined to research labs. They are now practical, deployable systems capable of reasoning, planning, interacting with tools, and executing tasks autonomously. When combined with containerization technologies like Docker, AI agents become portable, scalable, reproducible, and production-ready. This article walks through how to build an AI agent using Docker Cagent, explains the core components that power modern AI agents, and demonstrates practical coding examples to help you design, package, and deploy an intelligent ... How To Build an AI Agent With Docker Cagent

Here is short info about post: Scaling read traffic in PostgreSQL is a common challenge for growing systems. As applications evolve, read-heavy workloads often become the bottleneck long before write throughput is exhausted. The typical solution—adding read replicas—works well until application correctness enters the picture. One of the hardest problems when scaling reads is maintaining read-your-write consistency: ensuring that a client can immediately read data it has just written, even when reads are served from replicas. PostgreSQL’s asynchronous replication model introduces replication lag, making naïve read ... How To Scale PostgreSQL Reads by Implementing Read-Your-Write Consistency Using WAL-Based Replica Routing