Split (Harness FME)
by Harness
Feature flagging and experimentation, now Harness Feature Management & Experimentation.
- Category
- Developer Tools
- Type
- Feature flags
- Interface
- REST API
- Built with
- Connect Any API
- Credentials
- Access token
02Data
What you can sync.
- Feature flags
- Workspaces
- Environments
- Segments
- Change requests
Join Split (Harness FME) feature flags with product usage and revenue to see what each release changed.
Need more? Name any other Split (Harness FME) data the API returns, and the AI adds it to the connector.
03Credentials
Credentials you will need.
- An access token
Split (Harness FME) uses an access token. You add the credentials once, when the AI asks for them, and it tells you where to create them in Harness if you need help.
04How it works
How it works in DataMind.
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Pick Split (Harness FME).
Open Lake, pick Split (Harness FME) in the source picker and name the connection. Connect Any API opens with a ready prompt that points the AI at the Split (Harness FME) API docs.
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Answer a few questions.
The AI reads the Split (Harness FME) documentation, then asks which credentials you will use, which data to sync (for example feature flags and workspaces), whether you want a one-time load or a recurring sync, and which accounts or filters apply.
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Your data lands in Lake.
It builds the connector, tests it and shows you sample rows. Then Split (Harness FME) data loads into your Lake on your schedule, ready for the Warehouse, DataPrism BI and AI Minds.
