Frequently Asked Questions

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Statsig FAQs
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GENERAL

How can I generate types from a dynamic config schema in Statsig?

Date of slack thread: 5/31/24

Anonymous: If I create a dynamic config with a defined schema, is there a way for me to pull that schema in order to generate types that match the schema in my application?

Anonymous: I’d like to avoid needing to manually manage things. I don’t think there’s currently a way to define JSON schemas via the Statsig API, or else we could maybe define it on our end and push it to Statsig.

Brian (Statsig): Hi <@U074LJMJF44>, to answer your questions separately:

is there a way … to generate types that match the schema in my application? We support JSON Schema in our console, so if you use a JSON Schema validator in your own application, you could reuse it that way. Let me know if I’m misunderstanding here.

… a way to define JSON schemas via the Statsig API We actually do support this use case - you can send a POST or PATCH request to respectively fully- or partially-update a dynamic config, and include schema or schemaJson5 in your request to update the config’s schema. Let me know if this answers your questions! https://docs.statsig.com/console-api/dynamic_configs#patch-/dynamic_configs/-dynamic_config_id-

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OpenAI OpenAI
Brex Brex
Notion Notion
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At OpenAI, we want to iterate as fast as possible. Statsig enables us to grow, scale, and learn efficiently. Integrating experimentation with product analytics and feature flagging has been crucial for quickly understanding and addressing our users' top priorities.
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Dave Cummings
Engineering Manager, ChatGPT
Brex's mission is to help businesses move fast. Statsig is now helping our engineers move fast. It has been a game changer to automate the manual lift typical to running experiments and has helped product teams ship the right features to their users quickly.
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Karandeep Anand
President
At Notion, we're continuously learning what our users value and want every team to run experiments to learn more. It’s also critical to maintain speed as a habit. Statsig's experimentation platform enables both this speed and learning for us.
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Mengying Li
Data Science Manager
We evaluated Optimizely, LaunchDarkly, Split, and Eppo, but ultimately selected Statsig due to its comprehensive end-to-end integration. We wanted a complete solution rather than a partial one, including everything from the stats engine to data ingestion.
SoundCloud
Don Browning
SVP, Data & Platform Engineering
We only had so many analysts. Statsig provided the necessary tools to remove the bottleneck. I know that we are able to impact our key business metrics in a positive way with Statsig. We are definitely heading in the right direction with Statsig.
Ancestry
Partha Sarathi
Director of Engineering
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