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Upstream - Easily create dynamic configs

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Upstream - Easily create dynamic configs

Hi HN! I built a tool that allows developers to easily create and manage dynamic configurations with a web UI. At my last team I spent a lot of time managing config files. We had configs to do things like turning on/off training ML models or dynamic feature flags that helped us test new features in real-world settings. I noticed a few things: * Often these configs were pointing to the same information and over time they would drift which caused inconsistencies in the system. * Internal tools had different interfaces to create configs and they would be instrumented differently. For example, some had version control and permissions while others were simple YAMLs. * There was significant time lost waiting to stamp, land and redeploy low risk config changes. So I had this idea, what if there was an API to easily create and manage configs with a consistent and well instrumented interface? So far these are the main features: * Create JSON formatted configs and access them with an api call. * Dynamic retrieval. In the request body, users can pass context variables which the tool will evaluate against user defined rules and return a value. For example, give me X config given I am user Y. * A dashboard to monitor config usage. Potential use cases: * Feature flags: On/Off * Feature flags with context: eg. turn flag on for users in X city. * General purpose configuration store with access from anywhere. I'll be happy to receive your feedback!

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Product HuntOn track for Day 1 leaderboard · Strong signals: model, user, new · Missing: mac, agents, macos
89%89% 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
80%80% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: lua, ide, io · Missing: https docs, excited, just released
72%72% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: users · Missing: mobile apps, ios, personal
51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: interface, users · Missing: plus, platform, intuitive
35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: training · 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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