Harness to GoodData Integration
AI-first ETL from Harness into GoodData. Governed entities, incremental sync, typed landing tables.
How Datrise loads Harness into GoodData
Datrise syncs Harness's pipelines, deployments, services, environments, execution logs, and approvals into GoodData as warehouse tables GoodData maps into its logical data model. Flexible or custom fields land in flattened columns, and timestamps such as created, updated, and status changes are typed as date dimensions.
Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts. GoodData's LDM maps datasets by keys, so Datrise lands stable primary and foreign id columns to keep the model valid.
Ideal for embedded, multi-tenant analytics.
Endpoints
Harness: Continuous delivery pipelines and deployment verification.
GoodData: Composable analytics platform with headless BI and embedded dashboards.
How Harness entities map to GoodData
| Harness entity | GoodData object | Notes |
|---|---|---|
| pipelines | harness_pipelines | id PK · custom fields → flattened columns |
| deployments | harness_deployments | id PK · linked to harness_pipelines |
| services | harness_services | id PK · linked to harness_pipelines |
| environments | harness_environments | id PK · linked to harness_pipelines |
FAQ
How does Datrise handle Harness's custom fields in GoodData?
Flexible values are stored as flattened columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native GoodData types.
How does the Harness to GoodData sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
Related pipelines
More destinations for Harness
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