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RAID, or Redundant Array of Independent Disks, is a core technology that powers everything from personal NAS drives to enterprise-grade data centers. It enables you to combine multiple physical hard drives into a single system that improves performance, enhances data redundancy, or balances both. This blog post breaks down what RAID is, how the most common RAID levels work, and what their strengths and trade-offs are. Whether you are setting up your first home server or architecting high-availability infrastructure, understanding RAID is essential.
RAID: Why Everyone Should Care?
RAID, or Redundant Array of Independent Disks, is a core technology that powers...
Takeaways on ChatGPT Codex
This article explores how software developers can integrate ChatGPT Codex into their development...
Beyond the Buzzwords: What Is Machine Learning, Really?
Machine learning is transforming industries, but at its core, it remains a field...
Non-Relational Databases and the Design Dilemma: Single Table or Multi Table?
Non-relational databases have changed how developers think about data modeling. Among them, Amazon...
From Idea to App: Going Serverless with AWS
Startups and solo developers are often faced with the same challenge: how to...
Takeaways on ChatGPT Codex
This article explores how software developers can integrate ChatGPT Codex into their development workflows, from initial code generation to pull request creation. Codex is OpenAI’s code-focused large language model, capable of reading and writing code, generating test cases, and interacting with GitHub repositories. We explain how to get the most out of Codex by combining it with unit tests and test-driven development (TDD), ensuring reliable and verifiable results. Drawing on real-world advice from Simon Willison, we emphasize why automated testing is not just a complement but a critical enabler of safe and effective AI-assisted software engineering.
Beyond the Buzzwords: What Is Machine Learning, Really?
Machine learning is transforming industries, but at its core, it remains a field built on mathematics, logic, and structured data modeling. This article walks through the foundational principles of machine learning, stripping away the modern layers of abstraction to focus on its original essence. No libraries, no black boxes, just math and reasoning. Whether you’re a beginner with a math background or a curious technologist aiming to understand what actually powers intelligent systems, this is a ground-up journey into how machines learn.
Non-Relational Databases and the Design Dilemma: Single Table or Multi Table?
Non-relational databases have changed how developers think about data modeling. Among them, Amazon DynamoDB stands out for its speed, scalability, and serverless simplicity. This post explores the core ideas behind non-relational databases, explains the philosophies and tradeoffs of single-table versus multi-table designs in DynamoDB, and offers clear conventions and examples to guide implementation.
From Idea to App: Going Serverless with AWS
Startups and solo developers are often faced with the same challenge: how to build robust, scalable systems without draining their limited resources. Traditional cloud services offer power, but can be overkill — both in terms of complexity and cost. This is where serverless technology shines. In this post, we’ll look at how combining the Serverless Framework, AWS Lambda, and DynamoDB creates a lean, efficient stack. We’ll also examine why Aurora Serverless (particularly v2) may not be the best fit for budget-conscious builders, and when a cheap VPS still makes sense for relational workloads.