DatriseAI-first ETL

Harness to Redash Integration

AI-first ETL from Harness into Redash. Governed entities, incremental sync, typed landing tables.

How Datrise loads Harness into Redash

Datrise syncs Harness's pipelines, deployments, services, environments, execution logs, and approvals into Redash as SQL tables Redash queries and visualizes. Flexible or custom fields land in flattened columns for query results, and timestamps such as created, updated, and status changes are typed as temporal columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts for scheduled queries. Redash caches query results on a schedule, so Datrise keeps tables incrementally fresh so cached dashboards reflect reality.

Ideal for lightweight, query-driven dashboards.

Endpoints

Harness: Continuous delivery pipelines and deployment verification.

Redash: Open-source SQL client for queries, visualizations, and dashboards.

How Harness entities map to Redash

Harness entityRedash objectNotes
pipelinesharness_pipelinesid PK · custom fields → flattened columns for query results
deploymentsharness_deploymentsid PK · linked to harness_pipelines
servicesharness_servicesid PK · linked to harness_pipelines
environmentsharness_environmentsid PK · linked to harness_pipelines

FAQ

How does Datrise handle Harness's custom fields in Redash?

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

How does the Harness to Redash sync stay up to date?

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

Related pipelines

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