Data export & management
The edges of a project: what leaves it, and who reaches it.
Exports, external access and permissions
Exporting folders with a custom date builds export paths that carry the run date, which is what downstream systems and archives usually expect. Setting role conditions on one bucket narrows an IAM role to a single bucket rather than the whole Lakehouse, using CEL conditions. Custom event handling actions let an outside system trigger a workflow with a payload, which is the inbound half of the same integration problem.
Accessing buckets with S31-compatible tools covers the other direction, reading and writing project buckets from the AWS CLI, Rclone, NodeJS or Python instead of from the interface.
Together they cover data lifecycle work: scheduling exports, shaping their layout, reaching data from outside, and keeping permissions tight around all of it.
Export folders with a custom date→
Export paths that carry the run date.
Set role conditions on one bucket→
Narrow an IAM role to a single bucket with CEL.
Custom event handling action→
Let an outside system trigger a workflow with a payload.
Access your buckets with S3-compatible tools→
AWS CLI, Rclone, NodeJS and Python against a project bucket.
Go further
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