Opal – run GitLab pipelines locally using Apple container

Hacker News

Opal is a CLI that provides a TUI to run Gitlab pipelines locally. It tries to achieve as much compatibility with Gitlab pipelines as it makes sense to help developers get a fast feedback loop by running their jobs locally. On MacOS it uses the Apple Container CLI to spin up fast containers - you can customize the VM specs for this, but it's also compatible with Docker and Podman. On Linux it works with Podman, Docker or Nerdctl. You can use a local Ollama AI Agent or Codex to troubleshoot a failing job right in the job window. The prompt that gets sent to the AI agent for troubleshooting can also be customized. Claude code support is going to land some time this week. Right now it's used to run its own Gitlab pipeline and a few other projects that i'm working on. The tool is in its infancy so it might be rough around the edges. An MCP feature is going to land somewhere today or tomorrow that would allow you to hook it up to your AI agent of choice, which might provide more value for people using AI agents as their daily driver.

Visit product View on Hacker NewsMar 31, 2026

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, agents, macos · Missing: cursor, model, agentic

94%94% 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 · Strong signals: compatible · Missing: supports, reddit linkedin, podcasting

70%70% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: llama, ide, pipe · Missing: https docs, excited, just released

33%33% 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 · Missing: plus, platform, intuitive

23%23% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

20%20% 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.

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