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2,500 free AWS certification flashcards (built on AWS)

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2,500 free AWS certification flashcards (built on AWS)

I built a free study tool for AWS certifications: [AWSomecards]( https://awsomecards.com ). It’s a static-first app: pure HTML/CSS/vanilla JS on the frontend, with flip animations via CSS transforms and study modes (core concepts, comparisons, quick facts). Flashcard data lives in S3 as JSON, served through Lambda (Node.js 20) + API Gateway, cached globally at CloudFront. All infrastructure is managed via CloudFormation. The cards are immutable and cached aggressively at the edge. Rate limiting is enforced at both Lambda (30 req/min/IP) and API Gateway (50 rps, burst 100). Monitoring is wired up through CloudWatch alarms and SNS notifications. The learning model is simple: tiered flashcards mapped to AWS exam objectives, with a progressive mode that steps learners through increasing difficulty. The goal is to make high-quality certification prep available for free, without gatekeeping. There are currently 2,500+ cards across Cloud Practitioner, Solutions Architect Associate, Advanced Networking, and more. --- *Questions for HN:* - Which AWS certifications should be prioritized next? - Would there be interest in open-sourcing the flashcard data or the CloudFormation templates? - What sustainable monetization approaches have you seen work for free learning tools, without ads or paywalls? --- Feedback is welcome — both on the approach and on how to keep it sustainable long-term.

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
62%62% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
59%59% 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 · Missing: plus, platform, intuitive
37%37% 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
29%29% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: model, open · Missing: mac, agents, macos
25%25% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
17%17% 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.

Incorrect prediction on native model

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