Posts

Showing posts from April, 2025

New York, Through My Eyes: A Journey into the Heart of the City That Never Sleeps

Image
There are cities that impress you. And then there’s New York—bold enough to shake you, embrace you, and leave you a little breathless, all in a single day. From the moment I stepped onto its busy streets, I felt something different. It’s not just the skyline or the lights or the sheer size of it all. It’s the rhythm—the unapologetic, nonstop, beautiful chaos that pulses through every borough and alley. New York isn’t a city you just visit. You feel it. You live it. You walk faster, you think quicker, you speak louder. It doesn’t matter where you’re from—once you're here, you’re part of the energy. It’s intimidating, inspiring, and oddly addictive. I came to New York hoping to see the sights, maybe eat a bagel, take some photos. What I didn’t expect was how deeply the city would get under my skin. This blog post is my way of capturing that feeling—not through a checklist, but through moments. Moments that made me pause, laugh, reflect, and occasionally just stop and stare. So if...

Getting Started with PlantUML: A Beginner’s Guide to Diagramming with Code

Image
 Diagramming is an essential tool in software development and system design. Whether you are modeling relationships, visualizing processes, or illustrating architectural components, diagrams enhance communication and clarity. Unlike graphical tools such as Visio or Draw.io, PlantUML allows developers to generate diagrams from plain text, providing a code-first approach that is reproducible, version-controllable, and easy to maintain. This guide will walk you through everything you need to start using PlantUML, from installation to creating your first diagrams. What is PlantUML? PlantUML is an open-source tool that uses a concise, human-readable language to describe diagrams. Rather than dragging shapes and connecting them manually, you write text files that are rendered into images such as PNG, SVG, or ASCII art. PlantUML supports a variety of diagrams, including: Class Diagrams Sequence Diagrams Activity Diagrams Component Diagrams State Diagrams Object Diagrams ...

Security Best Practices for Multi-Tenant Kubernetes Clusters

  Kubernetes has rapidly become the de facto standard for container orchestration, providing powerful features for deploying, managing, and scaling applications. As enterprises increasingly adopt Kubernetes for hosting multi-tenant environments, ensuring robust security becomes paramount. Multi-tenancy refers to the practice of sharing a Kubernetes cluster across multiple tenants—typically different teams, applications, or even customers. Each tenant requires a degree of isolation and protection against malicious or accidental breaches from other tenants. This guide explores the best practices for securing multi-tenant Kubernetes clusters. Understanding Multi-Tenancy in Kubernetes Multi-tenancy in Kubernetes can take various forms: Soft Multi-Tenancy: Tenants share namespaces within a cluster but are isolated using policies. Hard Multi-Tenancy: Tenants are isolated at the cluster level, typically through Virtual Clusters or separate Kubernetes clusters. The focus of thi...

Transitioning from Docker Compose to Kubernetes: A Practical Guide

  Docker Compose and Kubernetes are two of the most popular tools used to manage containerized applications. While Docker Compose is ideal for local development and simpler projects, Kubernetes shines in production environments where scalability, resilience, and orchestration are critical. As your application grows, you may find yourself needing to migrate from Docker Compose to Kubernetes to take advantage of Kubernetes' robust features. This guide will help you understand the motivations, challenges, and practical steps involved in making this transition. Why Transition from Docker Compose to Kubernetes? Docker Compose is a fantastic tool for defining and running multi-container Docker applications. It uses a simple YAML file to configure application services, making it approachable and convenient. However, as applications scale or require high availability, Docker Compose may fall short. Here’s why you might consider moving to Kubernetes: Scalability: Kubernetes provides ...

Global Satellite Internet Providers in 2025

  The push for global internet coverage has accelerated in recent years, with numerous companies deploying ambitious satellite networks aimed at providing reliable high-speed internet to underserved and remote areas. Here’s a breakdown of some of the most promising projects currently available or in progress, from the perspective of a customer looking for high-speed, reliable, and affordable internet access. Starlink Starlink, the satellite internet service from SpaceX, was among the first major global satellite internet projects to launch. It began its public beta phase, known as the “Better Than Nothing Beta,” in late 2020 and has since expanded services globally. Target Audience: Starlink primarily targets rural and remote users who have limited or no access to traditional broadband services. Additionally, it serves mobile users such as RV travelers and boaters through its mobile-specific hardware. Service Availability: Operational globally, including the U.S., Canada, ...

Top 10 Essential Python Libraries for Data Science in 2025

  Python remains the go-to language for data science in 2025. Its versatility, ease of use, and an ever-growing ecosystem of powerful libraries make it a natural choice for professionals and beginners alike. As the field of data science evolves, so do the tools developers rely on. In this article, we will explore the top 10 essential Python libraries for data science in 2025. 1. NumPy NumPy continues to be a fundamental package for numerical computing in Python. Its support for arrays, matrices, and a vast collection of mathematical functions makes it the backbone of most data science projects. In 2025, NumPy’s capabilities have been enhanced with improved GPU support, enabling faster computations for large-scale datasets. NumPy’s array processing capabilities provide the foundation for many higher-level tools, including Pandas, Scikit-Learn, and TensorFlow. With Python 3.12’s performance improvements, NumPy has adapted to take full advantage of these enhancements. 2. Pandas ...