Deep dive into how Turbopack changed static export output in Next.js 16, why it impacts S3 upload times, and the simple fix that reduced upload time from 1m52s to 3s.
How to use Git sparse checkout with shallow clone to work with massive repos without waiting hours for a full clone.
What I learned about using npm ci --ignore-scripts in production, including which libraries need special handling and which ones work fine without postinstall scripts.
How I deployed a Python Flask app to GCP Cloud Run with GitHub Actions CI/CD, coming from an AWS background. Spoiler: easier than you think.
Embedded @font-face works in browsers but breaks in design tools. Here is how I used opentype.js to convert text to paths, making SVG exports compatible with Figma and Adobe Illustrator.
A deep dive into migrating from Pages Router to App Router, replacing next-mdx-remote with gray-matter and react-markdown. Includes analysis of markdown parsing libraries under the hood.
A comprehensive look at the challenges faced when upgrading multiple Next.js apps to version 16 with React 19 - from Recoil incompatibility to MDX issues and MUI updates.
A deep dive into how Jest and Vitest differ under the hood, from module systems and isolation to mock hoisting and timer APIs, plus practical migration tips.
Adding structured logging Python Slack bot, stream logs to BigQuery, and visualize usage with Looker Studio dashboards.
Fixing Slack retry duplicates with event deduplication, eliminating Cloud Run cold starts with min-instances, and dealing with cross-region Gemini API latency.
How I integrated Google Cloud Storage as a knowledge base for Gemini, allowing the bot to answer questions from markdown documentation without redeploying.
How I migrated from Google Sheets to BigQuery for analytics data in a Node.js application, including authentication, querying, and build-time data generation.
A deep dive into how JVM handles memory management through garbage collection, its types, and best practices.
Designing monitors that detect only your service’s own failures, filtering out upstream noise.
Refined Datadog queries for ALB metrics, latency, unit handling, and rate computations—mistakes learned and correct patterns.
