Elasti, a K8s based scale to zero solution that works with keda

Hacker News

Elasti is a solution to enable kubernetes to safely scale services back from zero when traffic arrives. It relies on kubernetes built in resources only to perform this without any external dependencies. Elasti has first class integration with keda and plans to work with plain HorizontalPodAutoscaler resources in the future. Features: - Works for both north-south and east-west traffic within the cluster - Both kubernetes deployment and argo rollouts are supported as scaling targets Any feedback would be much appreciated

Visit product View on Hacker NewsJan 28, 2025

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Actual performance

3points

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Did not reach leaderboard

Launch Intel predictions

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

72%72% 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.

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

56%56% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

48%48% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

47%47% 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

39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

22%22% 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

13%13% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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