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I needed to roll out the same GitHub Actions workflow change across a bunch of repositories.
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I needed to track daily Twilio costs in a spreadsheet.
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I wanted to pull data from a Google Sheet using curl and my existing gcloud credentials.
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TLDR: Templating VPA minAllowed from deployment resource requests prevents VPA from reducing resources.
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For four years I thought kubectl required gcloud auth login.
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A few days ago I cleaned up 200GB from my Mac and deliberately kept my Claude Code history at 2.3GB.
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I was updating my about page and wanted to add a timeline of places I’ve travelled to.
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My Mac was close to 100% full. macOS was complaining and I couldn’t install updates.
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I was setting up automated version bumps for a Python project using bumpver and uv.
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We had a dedicated “bot” user account for GitHub automation - creating PRs, pushing commits, merging branches.
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I’ve accumulated hundreds of Claude Code sessions and kept losing track of where I solved specific problems.
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I’ve been using Neovim full-time for a couple of years now.
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I’ve overhauled my Python development setup over the past year.
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My Kubernetes workflow changed a lot this year.
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This is Part 2 covering plugin development.
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This guide covers deploying Magento 2.4.8 to Kubernetes with MariaDB and OpenSearch as sidecars.
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I use git worktrees constantly for parallel development, but typing git worktree list, copying the path, and cd-ing got tedious.
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My disk was filling up with old Docker images.
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I was deploying a SvelteKit app to Cloudflare Pages and wanted to do it from the command line rather than connecting to GitHub.
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I was doing planned maintenance on a Kubernetes cluster.
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After installing gcloud, the gcloud command wasn’t found.
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I was debugging why HTTPS requests to app.example.com were failing with certificate errors.
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Using gh for PR work is much faster than the web UI, and allows staying in the terminal.
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I started Advent of Code 2025.
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I needed to check what was in a GCP secret to debug why an application wasn’t starting.
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I left a container running over a long weekend and came back to find it had consumed 50GB of disk space with logs.
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I needed to find my public IP to add it to a firewall allowlist. curl ifconfig.me That’s it.
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At 2am, I got an alert: database disk usage at 85%.
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I needed to connect to a Cloud SQL instance to debug a data issue.
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I use Docker Compose for local multi-service environments because it keeps runtime config in one file and makes startup/teardown repeatable.
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I needed to find all the places in our GitHub org that were using a deprecated GitHub Actions runner label.
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I was debugging why a Kubernetes deployment wasn’t updating after merging a PR.
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I needed to scrape property listings from a real estate site that heavily relied on JavaScript to load content.
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I was setting up a new Python project with direnv to manage environment variables.
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TLDR: I built gkecc to generate cost-optimised GKE ComputeClass specs from live pricing data.
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TLDR: Start with default-src 'self' and add exceptions as needed.
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I was getting warnings about pytest-asyncio decorators.
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Pydantic v2 is a ground-up rewrite with a Rust core, and it shows - validation is noticeably faster.
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I was evaluating Docusaurus as a replacement for our Redocly docs site.
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FastAPI has a few defaults that make API services easier to maintain: request validation, typed contracts, and built-in docs.
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GKE has four layers of autoscaling that work together: HPA, VPA, cluster autoscaler, and NAP.
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I was setting up Sentry for a new Python service.
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I was trying to figure out why my Helm chart wasn’t rendering correctly.
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I’d been using HPAs for a while without really understanding them.
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Pods were stuck in Pending and I couldn’t figure out why. kubectl describe showed “0/12 nodes are available: 12 node(s) had taint that the pod didn’t tolerate.”
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I needed to search Cloud Logging for specific events from the command line.
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I hadn’t run brew upgrade in a couple of months and suddenly gh started failing with cryptic errors.
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I’d been working on a feature branch and accidentally committed a bug fix to it instead of main.
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When sharing quick Python scripts, the old workflow is usually: create a venv, install dependencies, and document setup steps. uv run replaces that with a single command and script-local metadata.
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TLDR: Certificate not ready?