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I built open-source suite of tools to streamline Microservices

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I built open-source suite of tools to streamline Microservices

I have been dedicating my time and efforts to a project in the world of Node.js development. This project simplifies and streamlines the creation of microservice architecture, utilizing NestJS as its main backend framework. It is packed with a plethora of tools and features, including code generators for services and libraries, a user-friendly CLI for seamless local deployment, Terraform code generation to effortlessly set up the infrastructure on AWS, an NX monorepo solution that keeps all services organized in one place, a Github CI generator that streamlines the deployment process to AWS, and enforces event-driven design through the reliable RabbitMQ message broker. Additionally, strict folder structure is imposed to maintain a clean and well-organized monorepo. The entire project is open-sourced, accompanied by extensive documentation and a demo project to provide a hands-on experience. The purpose of this project is to empower developers by guiding them towards the right approach when building their applications and eliminating the fear of the perceived complexity associated with microservice architecture through the use of powerful code generators.

Visit productView on Hacker NewsFeb 3, 2023
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Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: including · Missing: supports, reddit linkedin, podcasting
91%91% 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.
Product HuntOn track for Day 1 leaderboard · Strong signals: user, code, open · Missing: mac, agents, macos
73%73% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io, including · Missing: https docs, excited, just released
63%63% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: friendly · Missing: plus, platform, intuitive
46%46% 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
29%29% 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
6%6% 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
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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