8+ min ago (419+ words) Note: Part 2 of 2 - Adding infinite replayability to the security game Read Part 1 - how I built the initial version with specs, steering, hooks, and MCP. After building v1, I had a working game. But it had zero replayability. Once you played it, you knew exactly what to fix: The magic was gone after one playthrough. I needed every session to be unique. I told Kiro: "I need dynamic vulnerability generation." Kiro suggested: "Let's spec it out." Even for enhancements, specs provide structure. Kiro helped me design a template-based system. Each vulnerability = JSON file containing: 15 concrete steps from design to implementation. Having a roadmap helped me stay focused. I created the first template for code injection: This template contains everything needed to generate a unique vulnerability! I created templates for: Each with complete educational content and AWS recommendations. I tested it and immediately…...

9+ min ago (325+ words) In the early stages of learning Terraform, we often start by placing all configurations including... Tagged with terraform, 30dayschallenge, devops, aws. In the early stages of learning Terraform, we often start by placing all configurations including resources, variables, and providers into a single file, typically main.tf. While this approach is useful for showcasing basic principles, the goal is to continuously "get better". Today, we dive into Terraform file structure best practices to organize your root module, making your code readable and efficient. #moving-beyond-the-single-file Moving Beyond the Single File To improve our Terraform workflow, the key is to separate components into multiple files. This list of recommended files and naming conventions is based on general recommendations from HashiCorp, though the specific names are not strictly mandated. Here is the essential breakdown of files recommended for a clean Terraform project structure: " main....

9+ min ago (838+ words) In the early stages of learning Terraform, we often start by placing all configurations including resources, variables, and providers into a single file, typically main.tf. While this approach is useful for showcasing basic principles, the goal is to continuously "get better". Today, we dive into Terraform file structure best practices to organize your root module, making your code readable and efficient. Moving Beyond the Single File To improve our Terraform workflow, the key is to separate components into multiple files. This list of recommended files and naming conventions is based on general recommendations from HashiCorp, though the specific names are not strictly mandated. Here is the essential breakdown of files recommended for a clean Terraform project structure: [Recommendation project structure ] " main.tf: This file serves as the core of your module and holds the resource definitions for infrastructure components…...

11+ min ago (265+ words) Tired of your AI applications grinding to a halt under heavy load? Imagine trying to serve thousands of hungry customers from a single, overwhelmed food truck. That's what happens when your AI inference can't dynamically scale to meet demand. The core concept is to automatically adjust the computing resources allocated to AI inference based on real-time demand. We leverage a powerful combination: Kubernetes for container orchestration, Slurm for workload management on high-performance computing (HPC) clusters, and an optimized inference engine (like vLLM) to handle large language models (LLMs) with incredible speed. Think of it as having a fleet of food trucks that automatically appear and disappear based on the length of the line. When demand spikes, more trucks (compute resources) are deployed; when things quiet down, the extra trucks are put away, saving valuable resources. Benefits of Dynamic Inference Scaling: One…...

13+ min ago (526+ words) Note: Part 1 of 2 - My journey building a security game with Kiro I personally find security learning boring. You read about SQL injection, mentally note "never hardcode secrets," then immediately forget it all when racing to ship features. Problem: I'd never built anything like this before. I'm not a game designer. I haven't built game applications. But I gave Kiro a try to see how far I could get. Instead of diving into code (my usual "move fast and break things" approach), Kiro walked me through creating a proper spec. Turns out, specs aren't bureaucracy - they're clarity. Kiro introduced me to EARS patterns. Each requirement became crystal clear: "WHEN a user fixes a security vulnerability THEN the system SHALL reduce the corruption level by 33%" Here's where it got interesting. Kiro pushed me to define correctness properties - universal rules that should always…...

14+ min ago (182+ words) Many banks, government portals, and older enterprise systems still require uploads in the legacy .xls Excel format. Go makes it easy to generate modern .xlsx files, but generating real .xls content usually requires installing LibreOffice, Python scripts, COM automation, or external system binaries. This approach is slow, hard to deploy, and unsuitable for containers or microservice workflows. To solve this problem, I built RetroXL, a pure-Go library that generates legacy-compatible .xls files from .xlsx, .csv, .tsv, or in-memory data structures. If you work with banking integrations, you may have faced this issue: Most Go libraries output .xlsx. Meanwhile, generating .xls typically requires tools that are heavy, slow, and not ideal for production deployments. RetroXL addresses this directly. RetroXL generates .xls files using the SpreadsheetML 2003 (XML) format accepted by Excel as a valid .xls. Avoid RetroXL if you need: RetroXL provides a…...

17+ min ago (1761+ words) There's a lot of hype around coding agents and the discourse can be annoying. I've always been into new shiny tools though. I'm forever messing with editors, IDEs, CLIs and anything else that seemed useful. Many of which no longer exist. It started with GitHub copilot and fancy autocomplete. Then web chat interfaces, copying and pasting code back and forth like StackOverflow. Now we've got coding agents. Agents are a useful tool because you can give them work that you would otherwise have to do yourself and they'll just go and try to do it, with varying degrees of success. Using techniques I discuss here, I try to increase the frequency of success. Using the term "agents" in this context, I'm thinking about instances of a coding agent in one context window. A single LLM thread, primed with some context…...

26+ min ago (365+ words) This hands-on build guide is designed to complement the main article on securing SSH shell applications and works for a quick planning reference. This guide walks you through how to build a secure, restricted SSH shell application. It complements the full article on Securing SSH Shell Applications, and pairs with the Printable Checklist for quick reference. The goal? To give you a clear, practical pathway to assembling a safe SSH-based terminal application " while leaving the final implementation details up to you. Start by choosing where the application will live. Many administrators use a dedicated directory under /opt, keeping the application isolated from user home folders and system binaries. Create a clean, well-organized folder structure that separates application code, logs, and configuration files. Your application will become the user's entire SSH experience, so you must control how it reacts to input....

34+ min ago (268+ words) Sentiment polarity is one of the most commonly referenced outputs of a sentiment analysis model, yet it is often misunderstood. Polarity measures the direction and intensity of emotional tone within a piece of text. A high positive polarity indicates strong approval, satisfaction, or optimism, while a negative polarity reflects criticism, frustration, or concern. Values close to zero tend to represent neutral or balanced language. Polarity is valuable because it allows analysts and applications to quantify subjective language in a measurable way. This makes it easier to sort user feedback, analyze trends, and classify responses automatically. Even though polarity is a simple metric, it forms the foundation for more advanced sentiment and emotion modeling. Sentiment polarity is one of the most commonly referenced outputs of a sentiment analysis model, yet it is often misunderstood. Polarity measures the direction and intensity of…...

38+ min ago (576+ words) Real-time codebase indexing with CocoIndex lets you turn a messy, evolving repo into a live semantic API that your AI tools, editors, and SRE workflows can query in milliseconds. Once your repo is indexed, you get a universal "code context service" that many tools can plug into. Some examples: CocoIndex is not "yet another Python script around an embedding model." It gives you a flow definition that describes how data moves from raw files to vector storage, and it tracks enough metadata to support incremental recomputation. For a codebase index, the high-level flow looks like this: This flow is declared once in Python with @cocoindex.flow_def, and CocoIndex turns it into a reproducible pipeline that can be updated with cocoindex update main whenever your repo changes. The first step is teaching the flow where your code lives and which files to…...