The most over-engineered URL shortener

Hacker News

Hey HN, Welcome to trimd.xyz, the most over-engineered URL shortener on the internet. I used this project to learn EKS and GitOps. The architecture is as follows: * Kuberenetes cluster deployed with terraform on EKS * ECR is used as the container registry * Prometheus / Grafana for monitoring and alerts * Argo CD for automated cluster deployments * Gitlab CI for continuous integration * DynamoDB for the storage layer * AWS Load Balancer Controller for ingress * FastAPI for the API Layer * React / Tailwind / Vite for the UI layer It's really going to be used as a sandbox type project for me to experiment with kubernetes related tools and learn different topics. If you like what you see, check out my website ayofishr.xyz, and If you know anyone that wants to hire a cheerful recently certified AWS/K8s engineer, my email is in my profile ^^ Cheers !

Visit product View on Hacker NewsSep 22, 2023

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Launch Intel predictions

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

56%56% 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 HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

41%41% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

40%40% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

35%35% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

21%21% predicted probability of success on AppSumo, 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.

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

12%12% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Correct prediction on native model

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