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Nimbus – AI Agent to control cloud costs

Hacker News

Nimbus – AI Agent to control cloud costs

Hi HN! I built Nimbus, an AI agent that helps companies reduce their cloud costs by automatically analyzing their infrastructure and recommending specific optimization actions. What it does: - Continuously monitors AWS, GCP, and Azure resources - Sends daily actionable recommendations via email - Identifies underutilized dev/test VMs and over-provisioned - Kubernetes clusters - Estimates potential savings for each recommendation - Provides one-click approval for implementing changes - Tracks savings over time with detailed analytics Future Plans: - Support for DigitalOcean and Oracle Cloud - ML-powered resource right-sizing recommendations - Automated implementation of approved changes - Cost anomaly detection with real-time alerts What else should I build? Link: https://atrium.st/agent/nimbus-cloud-cost-optimizer--mbel9uh...

Visit product View on Hacker NewsJan 17, 2025

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

78%78% 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.

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

44%44% 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

43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

38%38% 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: ide, io · Missing: https docs, excited, just released

36%36% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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