We

We Put Chromium on a Unikernel (OSS Apache 2.0)

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We Put Chromium on a Unikernel (OSS Apache 2.0)

We’ve been building infrastructure to spin up browsers for AI agents. Originally, we built[0] it as a pool of warm Docker containers running Chromium, exposing: - Chrome DevTools Protocol (for Playwright/Puppeteer) - noVNC (for live view) We’ve been following the unikernel space for a while, so we decided to see if we could get our image on one. We went with Unikraft Cloud[1]. Here’s how it did: - Boot-up time: 10–20ms (vs. ~5s for Docker containers) - Near 0 CPU/memory consumption when idle - Still ~8GB RAM when active (headful Chromium) Potential use cases: - Standby mode during long-running jobs: unikernels can sleep after X sec of inactivity, reducing clock time costs - Session reuse: auth/session cookies persist for hours/days. Basically as long as the cookies are valid - Cold start speed: good for low-latency, event-based handling We open sourced it with Apache 2.0! Feel free to fork or submit an issue / PR. Open to feedback or suggestions. www.github.com/onkernel/kernel-images == [0] https://github.com/onkernel/kernel-images [1] https://unikraft.cloud/ [2] Thanks to the Unikraft Cloud team @fhuici @nderjung @razvandeax for helping us figure this out (we're not affiliated) [3] (OPs) @rgarcia @juecd

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
66%66% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: open source, ide, io · Missing: https docs, excited, just released
64%64% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, dock · Missing: mac, macos, cursor
58%58% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue
18%18% 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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