Im

Img-Dash – Centralised Dashboard for Virtual Machine Images

Hacker News

Img-Dash – Centralised Dashboard for Virtual Machine Images

Hi HN, I built this project because I wanted an easier way to visualise all Virtual Machine Images. It can be very inconvenient to view and manage all VM images especially across multiple cloud platforms. Img-Dash is a simple dashboard for VM images across AWS, GCP and Azure that you can run locally. Features:- Consolidated view of all VM images and their data - View, Attach or Delete contextual information (IaC code, Event Data, Compliance Scripts) - Even displays which VMs are using which Image - Simple search and list of images in the dashboard I was also just very sick of people not following naming conventions and keeping track of images in spreadsheets. As a DevOps engineer, it has been ages since I've developed a full stack application so feedback is much appreciated! Repo: https://github.com/shaozae/Img-Dash

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
77%77% 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: mac, context, visual · Missing: agents, macos, agent
61%61% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
53%53% 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 · Strong signals: way · Missing: mobile apps, ios, personal
44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews
43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
14%14% 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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