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Intent Based Infrastructure on Top of Terraform

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Intent Based Infrastructure on Top of Terraform

Hey everyone! I built a platform that works on top of Terraform to expose high level constructs you want to create in your infrastructure (intent) rather than actually dealing with cloud resources (typical terraform modules). I am looking for other enthusiasts to work on this project, and gather feedback. The problem I am trying to solve is complexity. Typically you make infra by either asking AI, or dealing with very low level resources that other people on your team might not fully understand. If you expose a higher level construct, people will only typically deal with a well understood graph of intent which is much easier to understand and reason about, without worrying about low level resources. It works by declaring a model graph that consists of simple nodes like App, Region, Environment, Service, Server, etc that you show your intent with. E.g. My infrastructure consists of 3 AWS accounts (QA, Staging, Prod), with 2 Regions in each, and 1 Environment, under which my Service X resides. The Octo library then converts those intent to actual cloud resources using your instructions. E.g. it would convert a Region node into a vpc + internet-gateway. Or an Environment into an ECS Cluster. It will also generate the Terraform code for each of these cloud resources that your intent wanted. You can then run this Terraform code normally and get your infrastructure. There is a lot more depth, features, and roadmap items to this. Happy to go in more detail.

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Product HuntOn track for Day 1 leaderboard · Strong signals: model, using, code · Missing: mac, agents, macos
83%83% 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 · Missing: supports, reddit linkedin, podcasting
83%83% 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, io · Missing: https docs, excited, just released
54%54% 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
33%33% 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
30%30% 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
16%16% 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.

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