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A dotenv file on steroïd for Devs, SysAdmins and DevOps

Hacker News

A dotenv file on steroïd for Devs, SysAdmins and DevOps

Hello HN :) I made a kind of dotenv file on steroïd. It helps developers, sysadmins and DevOps load and source secrets / configs as env vars and files seamlessly from various providers (e.g. Hashicorp Vault, Clouders, etc.) without having to maintain .env files manually. Having worked in tech for 10+ years through various positions I consistently hit the same problem: setting up local environment is hard. Situation got better thanks to Docker, Nix and alike but it's still difficult to manage secrets & some configs locally as they're often not versioned for good reasons. This hits pretty hard when you have to play with Infra as Code / GitOps projects and/or multi-environment contexts (e.g. Terraform, Ansible, Pulumi...) Most often the issue is not "My company does not allow access to environment X", but more something like "CI is configured with a bunch of secrets / env vars and there's no way I reproduce all of that voodoo magic locally. I'll just commit and wait for my changes to be executed on CI." Tired of this situation, I developed Novops: it helps manage and share secrets/configs safely so it can be used both locally and by CI/CD. Secrets can be referenced from various sources (e.g. Hashicorp Vault, AWS, GCloud, Azure...) and loaded as files or environment variables. It also handle multi-environments setup along with various helper features (such as automatically impersonate AWS IAM Role). Novops just needs a YAML file referencing your secret sources so it can load them in your environment.

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
81%81% 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: dock, context, code · Missing: mac, agents, macos
75%75% predicted probability of success on Product Hunt, 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
45%45% 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 · Missing: plus, platform, intuitive
25%25% 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
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.

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