Introduction
Fleak is a managed data workflow platform for building, deploying, and running distributed data workflows. Users design workflows in the DAG builder UI by configuring source connectors, adding processing nodes, and defining sink destinations. Once deployed to Fleak's compute cluster, workflows run asynchronously for high-throughput distributed processing.
Create, Test, and Deploy a Workflow
End-to-end guide to creating a workflow in Fleak's DAG builder, testing it with sample data, publishing a version, and deploying it to a compute cluster.
Field Inspector
The Field Inspector samples production data from a data asset, runs it through the workflow up to a node you choose, and shows every field and value as it leaves that node with its record count and by
Connection Profiles
Connection Profiles store the credentials and endpoint for one external platform, so source and sink nodes authenticate without credentials being entered on each node.
Data Assets
Data Assets name a single location on an external platform — a queue, topic, table, folder, or endpoint — so workflows reference it by name instead of repeating paths and connection settings on every
Delivery Guarantees and Write Failures
What happens to records when a deployed workflow cannot write them to a destination: a sink may retry first, and records that still fail are counted as errors and dropped. Fleak does not guarantee exa
Nodes
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MCP setup
To connect an MCP client to Fleak Data Workflow, open Settings → Account settings in Fleak and find Connect an MCP client.