es

estela, a modern elastic web scraping cluster

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estela, a modern elastic web scraping cluster

estela is an elastic web scraping cluster running on Kubernetes. It provides mechanisms to deploy, run and scale web scraping spiders via a REST API and a web interface. It is a modern alternative to the few OSS projects available for such needs, like scrapyd and gerapy. estela aims to help web scraping teams and individuals that are considering moving away from proprietary scraping clouds, or who are in the process of designing their on-premise scraping architecture, so as not to needlessly reinvent the wheel, and to benefit from the get-go from features such as built-in scalability and elasticity, among others. estela has been recently published as OSS under the MIT license: https://github.com/bitmakerla/estela More details about it can be found in the release blog post and the official documentation: https://bitmaker.la/blog/2022/06/24/estela-oss-release.html https://estela.bitmaker.la/docs/ estela supports Scrapy spiders for the moment being, but additional frameworks/languages are on the roadmap. All kinds of feedback and contributions are welcome! Disclaimer: I'm part of the development team behind estela :-)

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Indie HackersFits the IH revenue-focused audience · Strong signals: supports · Missing: reddit linkedin, podcasting, created
82%82% 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.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
62%62% 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 · Missing: mac, agents, macos
59%59% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: interface · Missing: plus, platform, intuitive
35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
32%32% 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
16%16% 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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