DatriseAI-first ETL

AWS CloudTrail to Metabase Integration

AI-first ETL from AWS CloudTrail into Metabase. Governed entities, incremental sync, typed landing tables.

How Datrise loads AWS CloudTrail into Metabase

Datrise syncs AWS CloudTrail's API events, identities, resources, event sources, error codes, and request parameters into Metabase as clean SQL tables Metabase auto-discovers. Flexible or custom fields land in flattened columns for the question builder, and timestamps such as created, updated, and status changes are typed as temporal columns for trends.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts for large questions. Metabase auto-scans schemas, so Datrise uses readable table and column names so the no-code UI stays self-explanatory.

Ideal for self-serve questions and dashboards for whole teams.

Endpoints

AWS CloudTrail: AWS account activity and API audit logging.

Metabase: Open-source analytics with questions, dashboards, and embedded insights.

How AWS CloudTrail entities map to Metabase

AWS CloudTrail entityMetabase objectNotes
API eventsaws_cloudtrail_api_eventstemporal columns for trends events
identitiesaws_cloudtrail_identitiesid PK · linked to aws_cloudtrail_api_events
resourcesaws_cloudtrail_resourcesid PK · linked to aws_cloudtrail_api_events
event sourcesaws_cloudtrail_event_sourcestemporal columns for trends events

FAQ

How does Datrise handle AWS CloudTrail's custom fields in Metabase?

Flexible values are stored as flattened columns for the question builder, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Metabase types.

How does the AWS CloudTrail to Metabase sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables.

Related pipelines

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