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Goldilocks Scraper – a scraper for Goldilocks (K8s VPA recommendations)

Hacker News

Goldilocks Scraper – a scraper for Goldilocks (K8s VPA recommendations)

I really like Goldilocks (https://goldilocks.docs.fairwinds.com/) for pod resource recommendations, but its CLI tool is scoped to a single namespace, and the dashboards don't have any option to export data. If you have a lot of SOAs across a lot of diverse clusters, that's a problem. So I built this: https://github.com/stephanGarland/goldilocks-scraper It scrapes each namespace's dashboard, grabs the code blocks with BeautifulSoup, throws them into Pandas, does some math, and dumps recommendations out into a YAML file. You can then take those and put them into your deployment. Disclaimer: I am not responsible if you use this and break prod. It's a decent baseline, nothing more.

Visit product View on Hacker NewsJul 2, 2021

Actual performance

1points

Did not reach leaderboard

Launch Intel predictions

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

57%57% 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

55%55% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

52%52% 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

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

40%40% 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

14%14% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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