A common problem with a familiar shape: a process can dial outbound to the internet, but nothing on the internet can dial it back. Your dev server on a laptop. A service in a private VPC. A homelab app behind your router. A container in a pod with no ingress. Same shape every time — outbound works, inbound doesn't. rift is a small Go binary I built to solve that. Run it as a server on a VPS you ow
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The Problem If you're like me, you live in your terminal. You've got Docker containers running for databases, Redis instances for caching, microservices doing their thing — and you're constantly context-switching to check on them. # The old way: docker ps docker logs my-app -n 50 docker stats docker inspect some_container # ... back and forth, breaking your flow Now imagine you're working with
If your team works with geospatial data, sooner or later you need a place where maps, layers, users, and edits live together. There are many capable SaaS platforms and proprietary solutions you can deploy on your own infrastructure, but there is another path: self-hosting an open-source Web GIS server. In this tutorial, we will deploy NextGIS Web on a low-cost VPS using Docker, and then configure
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
Exemplo mínimo de uso com Bun (baseado na documentação oficial) Aviso: Este exemplo é puramente acadêmico, baseado na documentação oficial do Next.js. Para um ambiente de produção real, ajustes adicionais de segurança, performance e monitoramento são necessários. 1 - Ajustar o next.config.ts para "Standalone": import type { NextConfig } from "next"; const nextConfig: NextConfig = { output: "
Yesterday, my Jenkins pipeline could install dependencies and build the frontend. But there was a missing piece: Docker. Without it, I couldn't package my applications into containers — the whole point of this challenge! Today, I fixed that. I configured Jenkins to build Docker images for both my backend and frontend, turning my CI pipeline into a complete build system. The pipeline could: Pull co