Ylem – an open-source orchestrator for real-time data streaming

Hacker News

Ylem is an open-source platform for real-time data streaming orchestration built on top of Apache Kafka. Main differences between Ylem and existing orchestrators: - Microservice architecture, which makes it easily scalable. - Written on Golang for better performance and extendability. - No-code/Low-code approach saves tons of time usually spent on programming pipelines with Python or configuring with YAML/XML. Although programming is still supported if necessary. - Self-scaling and self-healing mechanism that identifies the "slow" and "fast" pipelines and manages them for the best performance. - Containerized by default for an easy installation process with Kubernetes or Docker. - Cost-effective and cost-transparent in the cloud due to its architecture. Our documentation: https://docs.ylem.co/open-source-edition/task-processing-arc... . Please have a look, try to install it and run it, give us a star, and send me your feedback. Any feedback is appreciated.

Visit product View on Hacker NewsNov 18, 2024

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

86%86% 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 · Strong signals: dock, code, open · Missing: mac, agents, macos

75%75% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

68%68% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

49%49% 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

49%49% 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

18%18% 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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