Fleet – Experimental build tool for Rust that’s up to 5x faster

Hacker News

Fleet is an experimental fast, lightweight, open-source, build tool for Rust. Builds with Fleet enabled are up-to 5x faster! For a production repository (infinyon/fluvio) which we tested, we were able to cut down our incremental build times from 29 seconds down to 9 seconds, boosted by Fleet. We saw even better results on dimensionhq/volt, with our build times cut down from 3 minutes to just 1 minute - a 3x speed improvement! How does fleet work? Fleet works by optimizing your builds using existing tooling available in the Rust ecosystem, including seamlessly integrating sccache, lld, zld, ramdisks (for those using WSL or HDD's) et al. You can get fleet at the official website. Check out fleet over at https://github.com/dimensionhq/fleet and our website at https://fleet.rs Looking forward to your feedback and thoughts!

Visit product View on Hacker NewsApr 23, 2022

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

80%80% 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: including · Missing: supports, reddit linkedin, podcasting

73%73% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

71%71% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

55%55% 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

47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

15%15% 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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