I

I got tired of managing dev environments, so I built ServBay

Hacker News

I got tired of managing dev environments, so I built ServBay

Hey HN, For years, my local development setup has been a fragile mess of tools that never quite played nicely together. On my mac, it was a constant battle with Homebrew services starting (or not starting) on boot, conflicting PHP and Node versions managed by `asdf` or `nvm`, and a collection of `docker-compose.yml` files that I'd copy-paste and tweak for every single project. The cognitive load was just too high. Setting up SSL was another chore involving `mkcert`. Sharing a quick demo with a colleague meant firing up ngrok. And if I wanted to run two projects that needed different versions of PostgreSQL? Good luck. I’d have to stop one service to start another. I missed the simplicity of the MAMP/XAMPP era, but I needed something that could handle the diverse stack of a modern developer – not just PHP and MySQL, but Python, Go, Rust, Node.js, and various databases. That’s why I (along with my small team) built ServBay. It's our attempt to bring back simplicity and speed to local development without sacrificing power. It's a native app for macOS and Windows, not a wrapper around Docker or VMs. Here's what it does: One-Click Stacks: You can install and run multiple, isolated versions of languages like Python, Node.js, Go, Java, Rust, Ruby, and .NET. No more path conflicts or environment variable hell. Databases, Plural: This was a huge one for me. You can run multiple instances of MySQL, MariaDB, PostgreSQL, Redis, and MongoDB simultaneously. Project A can use Postgres 14 while Project B uses Postgres 16, both running at the same time on different ports. Automatic SSL: Any host you create gets a valid SSL certificate out of the box. No more browser privacy warnings for ` .test` or ` .localhost` domains. Built-in Tunneling: If you need to demo a feature or test a webhook, there's a one-click button to expose your local site to the internet via a secure tunnel. One-Click Local AI: This is something we're really excited about. We've added a feature to easily download and run models like Llama 3 or Stable Diffusion locally through a simple UI, so you can experiment without worrying about API keys or costs. Everything Else: It also handles one-click backups, has a clean, non-intrusive UI, and is designed to be as lightweight as possible. I know what many of you are thinking: "Why not just use Docker?" And that's a fair question. We use Docker for production and complex, multi-service architectures. But for quickly spinning up a single-service app, testing a new framework, or just general day-to-day development, the overhead of `Dockerfile`s, `docker-compose.yml`, slow file sync on macOS, and resource consumption often feels like overkill. ServBay is for those moments where you just want to get to the code. The project is still young, and we have a long roadmap ahead. I'm here all day to answer any questions, listen to your (brutally honest) feedback, and hear about what your own development workflows look like. You can check it out here: https://www.servbay.com Thanks for reading.

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, macos, model · Missing: agents, agent, cursor
95%95% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
93%93% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: excited, llama, io · Missing: https docs, just released, exist
58%58% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: host · Missing: plus, platform, intuitive
43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
35%35% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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