Bugsink – A self-hosted alternative to Sentry

Hacker News

Bugsink is a error tracking tool with a focus on self-hosting and simplicity. Features: an excellent UI for the stacktraces (I believe: the best). Sentry-SDK compatible. Very scalable. The usual stuff: notifications/alerts, issue-grouping. Self-hosting may be important for privacy, security and legal reasons, or just because you have good taste. A focus on self-hosting should be contrasted with the "Self Hosted In Name Only" approach of «coughs loudly». Bugsink is in beta now, with the Python SDK being the most tested, but others reportedly working just fine. Installation is basically `docker run` or `pip install` (there are some details, click the big "Try it!" button to see them). --- I’m Klaas, the solo founder ("solo everything") at Bugsink. I built this because I wanted a self-hostable solution for error tracking (stacktrace-first, no APM). As per "Show HN" guidelines, I’m happy to answer any questions/feedback you might have.

Visit product View on Hacker NewsOct 16, 2024

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Indie HackersFits the IH revenue-focused audience · Strong signals: compatible · Missing: supports, reddit linkedin, podcasting

76%76% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

64%64% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

57%57% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: host · Missing: plus, platform, intuitive

39%39% 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

13%13% 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.

Incorrect prediction on native model

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