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Holori- Automated Terraform Diagrams in Pull Requests

Hacker News

Holori- Automated Terraform Diagrams in Pull Requests

Hey HackerNews community! We're Antoine, Emeric, and Alexandre, the minds behind Holori. In our past lives, we dove deep into documenting complex infrastructures across various cloud providers for the Aerospace and Medical industries. Compliance was crucial, but spending endless hours on Draw.io felt like a drain on our productivity. Realizing we weren't alone in this struggle, we set out to build a solution. Introducing Holori, a tool that automatically generates infrastructure diagrams from your Terraform files. The magic happens right in your GitHub Pull Requests – the diagrams are seamlessly embedded in the comments. Click on the visual representation, and you'll be transported to our SaaS app, where you can explore all historical changes and drill down in the terraform attributes. Currently, Holori supports AWS, Azure, and GCP. Exciting plans are in the pipeline! We're gearing up to generate diff diagrams directly in the Pull Request to easily highlight changes with added, modified or deleted resources. We are also planning for integrations with GitLab and Bitbucket. We've poured our hearts into crafting an intuitive, user-friendly experience, but now we need your input. Try Holori today and share your thoughts – your feedback is key in shaping Holori's future. Calling all Cloud Architects, DevOps engineers, and Terraform enthusiasts! Give Holori a spin at https://app.holori.com/ . We can't wait to hear how Holori transforms infrastructure visualization and documentation for you. Thank you for your support!

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, new, visual · Missing: mac, agents, macos
82%82% 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 HackersFits the IH revenue-focused audience · Strong signals: supports · Missing: reddit linkedin, podcasting, created
73%73% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, pipe, io · Missing: https docs, excited, just released
60%60% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoStrong fit for a featured deal · Strong signals: intuitive, friendly · Missing: plus, platform, reviews
57%57% 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
23%23% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: saas · Missing: arr, mrr, revenue
12%12% 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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