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DigitalOcean vs Vultr: The AWS Alternatives Small Businesses Actually Need

A quick note on the links below. The DigitalOcean and Vultr links in this article are referral links. If you sign up via them, you get a free credit on your new account (currently $200 over 60 days for DigitalOcean and up to $300 for Vultr) and the author of this article gets a small referral credit too, at no extra cost to you. AWS does not run an equivalent referral program, so the AWS links are normal links. The review below is the author's own evaluation; the credits do not change the recommendations. If you have ever spent a workday watching your website refuse to load, you are not alone. In a recent outage , a single building in Northern Virginia hosting one of Amazon's availability zones (the cloud-industry term for one campus's worth of servers in one region ) got too hot. The hardware shut itself down. AWS calls this a thermal event. Customers around the world have other names for it. Big enterprises ride out outages like this. They have multi-region setups, dedicated SRE teams, and SLA credits that will refund a small fraction of their monthly bill. Small and mid-size businesses do not. They lose a day of revenue, scramble to reassure customers, and then read a post-mortem in a few weeks that explains what went wrong in language that does not help them recover the lost revenue. The cloud was supposed to make small businesses look big. After each new outage, it is fair to ask: is AWS actually the right cloud for small businesses at all? Two providers worth a serious look, DigitalOcean and Vultr , are simpler, cheaper at the entry level, and built around use cases that more closely match what a small business actually needs. Here is what each one does, where AWS is still the right answer, and how to decide. Why AWS hits small businesses harder than big ones When a giant company has an AWS outage, three teams kick into gear. There is the engineering team that fails workloads over to a backup region. There is the customer-success team that updates the status p

2026-06-13 原文 →
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I Added an AI Gate Before Every git push with no-mistakes 🛡️

We are all using AI to write code now. Whether it's Claude Code, Aider, or Copilot, the speed is incredible. But there is a glaring bottleneck we don't talk about enough: AI code is often just slightly broken. 🤖💥 It forgets an import, misses a type definition, or fails a test. Usually, you only find out after you push to GitHub. Your CI/CD pipeline turns red 🔴, and you end up polluting your Git history with a dozen commits titled fix: linting or fix: missing test variable . I recently found a repository called no-mistakes that solves this brilliantly. It acts as a local proxy between your terminal and GitHub, forcing AI to test and fix its own code before anyone else sees it. Here is why it's worth a look. 👇 😩 The Problem With Traditional Workflows Right now, developers handle broken code in two ways: The CI/CD Walk of Shame 🚶: You push code, wait 5 minutes for GitHub Actions to fail, pull the error locally, fix it, and push again. Pre-commit Hooks (Husky) 🐶: You set up local hooks. When you try to commit, it yells at you about formatting and blocks the commit until you manually fix it. Both methods are passive . They tell you something is broken, but they leave the cleanup to you. When you're using an AI coding agent to generate the code in the first place, manually babysitting its output defeats the purpose. 🚀 Enter no-mistakes no-mistakes is a CLI tool that intercepts your git push . Instead of sending your code straight to origin, it routes it through a localized validation pipeline. ⚙️ How it actually works: 🧱 The Hidden Sandbox: When you trigger it, it creates a temporary git worktree in the background. Your active editor stays completely undisturbed. ✅ Validation: It runs your tests, linter, and build steps inside that isolated sandbox. 🔁 The AI Feedback Loop: If a test fails, it captures the error log and hands it back to an AI agent, essentially saying: "You broke this test. Fix it." 🟢 The Clean Push: Once the AI patches the code and all tests pass, it push

2026-06-12 原文 →
AI 资讯

I Built a Git Sync Tool for My Obsidian Vault

I Built a Git Sync Tool for My Obsidian Vault You write notes, you save them, you forget to push to GitHub. Then your laptop dies, and your notes are gone. I built a single Bash script that automates the entire sync workflow, and it works with any Git repo. If you use Obsidian (or any plain-text note-taking system) and sync via Git, you know the drill: write notes, stage changes, commit, fetch, check status, pull, push. Every time. It's 6 repetitive commands that you will inevitably skip until disaster strikes. I got tired of this and built git-sync , a single Bash script that does everything in one go. What It Does git-sync is a terminal-based Git sync tool that: Auto-commits all changes with a timestamp Fetches remote state Detects divergence (ahead/behind) Shows you only the relevant sync options Executes your choice with safety guard rails How It Works Run it from inside any Git repo: ./git-sync Phase 1 - Auto-commit: Staged or unstaged changes are committed automatically with a message like "Last Sync: Jun-12 (Arch)" . The device name is configurable. Phase 2 - Fetch & Detect: It fetches from remote, counts how many commits ahead and behind you are, and categorises the state: ahead, behind, diverged, or in-sync. Phase 3 - Smart Menu: Only relevant options are shown: State Options Ahead only Upload, Sync, Force push, Cancel Behind only Download, Sync, Hard reset, Cancel Diverged All six options Phase 4 - Execute: The chosen action runs with a spinner and status messages. Destructive operations (force push, hard reset) require explicit confirmation. Why It's Useful for Notes Syncing Obsidian + Git is a powerful combo. Your notes are plain markdown, version-controlled, accessible from any device. The friction is the sync ritual. git-sync removes it. Multi-device workflows: I run this on my Arch desktop (DEVICE_NAME="Arch") and my work laptop (DEVICE_NAME="Laptop"). The auto-commit message tells me exactly which machine made each sync, so I can trace conflicts back

2026-06-12 原文 →
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