Tech News, AI, Software Development & Innovation Explained Simply
Overview Kubernetes has become the industry standard for container orchestration in modern cloud-native applications. As organizations move toward microservices, containers, and DevOps practices, managing applications at scale has become increasingly complex. Kubernetes solves this problem by providing a reliable, scalable, and automated platform to deploy, manage, and operate containerized applications…
If you’re a developer, there’s a good chance you’ve spent hours in Visual Studio Code (VS Code). It’s fast, sleek, and packed with features. But have you ever wondered what VS Code is actually made of? Everyone uses it, but hardly anyone knows the magic happening behind the scenes. Let’s…
Overview As Kubernetes application deployment becomes more complex, teams need a reliable and automated way to manage releases across environments. Manual deployments, custom scripts, and CI-driven push models often introduce errors, configuration drift, and operational risk. Argo CD solves this by enabling GitOps-based continuous delivery for Kubernetes, where Git acts…
🌐 Overview Generative AI is no longer just an experiment — it’s becoming a core part of modern applications. From smart chatbots to automated content creation and intelligent search systems, companies want AI that is powerful, secure, and easy to scale. This is where Amazon Bedrock comes in. Amazon Bedrock…
Artificial Intelligence has moved far beyond simple prompt-and-response systems. Today’s applications require memory, tool usage, workflow orchestration, and even decision-making logic. This growing complexity is exactly why Microsoft introduced Semantic Kernel. Semantic Kernel is a modern AI orchestration framework designed to help developers build scalable, maintainable, and production-ready AI-powered applications.…
Modern applications are no longer built as one massive block of code. Instead, they are broken into smaller, independent services that work together — a concept known as microservices architecture. While microservices bring flexibility and scalability, they also introduce new challenges such as service communication, observability, security, and configuration management.…
Overview As AI models continue to improve, expectations from them are also increasing. Today, AI is expected not only to answer questions but to take action, integrate with systems, and operate within real business workflows. However, large language models are isolated by design — they don’t naturally know how to…
Introduction: Understanding the AI Revolution We Are Living In Artificial Intelligence is no longer an experimental technology hidden inside research labs. It has become part of everyday digital life—quietly powering search engines, recommendation systems, voice assistants, customer support chats, image generators, video tools, and even software development workflows. What makes…
Overview Generative AI has made huge progress, but even the most advanced Large Language Models (LLMs) still face a major challenge: they don’t have access to real-time or private data. This often leads to outdated answers or AI hallucinations. This is where Retrieval-Augmented Generation (RAG) plays a critical role. RAG…
Learn what vector databases are, why traditional databases fall short, and how vector databases power modern AI applications like chatbots, semantic search, and recommendation systems. Overview In recent years, Artificial Intelligence has moved far beyond simple rule-based systems. Modern AI applications aim to understand meaning, context, and similarity, not just…