Featurevisor – Git-based feature flags and experiments management
Why? - Decouple application deployment from releases How it works: - Make changes to your features and segments (YAMLs) via Pull Requests - Generate datafile (JSON file) in CI/CD workflow and upload to your CDN - Fetch datafile in your application runtime and consume with SDKs Supports: - Feature flags: boolean flags - Experimentation: a/b tests - Segments: targeting traffic with conditions - Variables: namespaced under each feature and conditional - Gradual rollouts: avoid big bang releases, go from 0% to 100% - Consistent bucketing: same user sees same variation - Multiple…
In plain words
Featurevisor is a Git-based system for managing feature flags and A/B tests that decouples application deployment from feature releases. Teams define features and audience segments as YAML files through pull requests, which generate JSON datafiles stored on CDNs for applications to fetch at runtime. It supports boolean flags, gradual rollouts, consistent user bucketing across variations, audience targeting with conditions, environment-specific configurations, and analytics integrations. The approach allows teams to control feature availability and experiments without redeploying their applications.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
Why? - Decouple application deployment from releases How it works: - Make changes to your features and segments (YAMLs) via Pull Requests - Generate datafile (JSON file) in CI/CD workflow and upload to your CDN - Fetch datafile in your application runtime and consume with SDKs Supports: - Feature flags: boolean flags - Experimentation: a/b tests - Segments: targeting traffic with conditions - Variables: namespaced under each feature and conditional - Gradual rollouts: avoid big bang releases, go from 0% to 100% - Consistent bucketing: same user sees same variation - Multiple environments: prod, staging, test, and more - Force bucketing: allow testers to force enable/disable for themselves only - Tagging: resulting in smaller datafiles for your application(s) - Tracking: integration with any analytics tool - Status site generator: for human friendly status reporting - SDKs: for Node.js and browser environments, Kotlin/Swift planned for future
Does the same job
all alternatives →- FFFeature Flags Backed by Git2024 · flipt.io · ▲93
Hey all, I'm the founder of Flipt, an open-source (https://github.com/flipt-io/flipt) feature flag tool that I (and others) have been working on for the past few years. About a year or two ago we added support for serving flag state from various non-relational declarative stores like Git, OCI, Object Store, etc. Many of our users came to love the git-backed storage, as it allows them to keep their feature flags close to their code in there organization's repos. But they had one (rather large) ask, and that was the ability to use the UI to manage flag state changes and…
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Hi HN, Today we’re launching GPT-4 answers on Phind.com, a developer-focused search engine that uses generative AI to browse the web and answer technical questions, complete with code examples and detailed explanations. Unlike vanilla GPT-4, Phind feeds in relevant websites and technical documentation, reducing the model’s hallucination and keeping it up-to-date. To use it, simply enable the “Expert” toggle before doing a search. GPT-4 is making a night-and-day difference in terms of answer quality. For a question like “How can I RLHF a LLaMa model”, Phind in Expert mode delivers a…
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