When you automate backups, you eventually discover the backup was not the hard part. The hard part was everything around it. This week I got a nice little reminder from my self-hosted agent setup: the backup job can be logically correct, authenticated, scheduled, and still fail because of two very boring constraints: Docker-owned files are not always readable by the user running cron. GitHub Relea
An opinionated list of Python frameworks, libraries, tools, and resources
We're all learning how to ship more side projects. If you're "in the bubble" it can feel like everyone is repo-maxxing. Shipping weekly. Spinning up agents to scaffold full apps overnight. New OSS dropped every Friday. The reality I see with most developers is much more normal: They have six or seven repos sitting in various states of half-attention. A side project from last year that still gets a
Hey dev.to community! I just launched CodeLens AI — an AI-powered code review tool that automatically reviews every pull request. Connect your GitHub repo Open a PR AI automatically reviews the code Detailed review comment posted on PR Bugs and logic errors SQL injection and security vulnerabilities Performance issues Code quality improvements Next.js + TypeScript NextAuth + GitHub OAuth Supabase
很多团队的网络监控并不算差。 链路可用率有、接口带宽有、CPU 和内存有、异常告警也接进了企业微信、飞书和短信。但真正出了事，复盘时还是会出现同一句话：当时知道出问题了，但没有把现场留住。 这就是为什么越来越多团队开始关注网络回溯分析系统。 它解决的不是“能不能看到告警”这个初级问题，而是更关键的两个问题： 告警发生时，能不能快速还原到底是哪一段流量、哪一条路径、哪一种会话出了问题 事故结束后，能不能基于证据复盘，而不是靠聊天记录和印象拼凑过程 对云上和混合云场景来说，这件事尤其重要。因为链路更长、设备更多、路径更动态，很多故障不是“持续坏”，而是短时抖动、瞬时拥塞、路径切换、策略误命中。如果没有回溯能力，排障就很容易沦为赛后猜谜。 这篇文章不讲空洞概念，直接从一线运维视角拆清楚：云上网络回溯分析系统到底该怎么建，应该覆盖哪些能力，落地时最容易踩哪些坑。 先说结论： 传统监控擅长发现“异常
Why We Open-Sourced Our AI Safety Layer When we built the AI safety layer for As You Wish (AYW), we faced a choice: keep it proprietary or open-source it to help the community. Here's why we chose the latter (and why it made our platform stronger). If you're building AI-assisted development tools, you need: Input validation (sanitizing prompts, preventing injection) Output filtering (catching u
If you want to Automate GitHub PRs, the real goal is not just adding another bot comment to a pull request. The goal is to give reviewers the context they usually have to gather manually: who owns the service, whether it is deployed, whether basic repository standards are in place, and whether the change looks safe to merge. A useful AI pull request workflow can do exactly that. When a PR opens, i
How I Used GitHub Actions to Auto-Publish to AMO on Every Release Manually uploading extension files to AMO (Mozilla's Add-On Observatory) is tedious. After the fifth time forgetting to increment the version number, I automated it with GitHub Actions. Here's exactly how I set up the pipeline for the Weather & Clock Dashboard extension. Trigger on new GitHub release Validate the manifest version