Source connector

Harness connector

Harness integration for databases, warehouses and BI tools

Continuous delivery pipelines and deployment verification. Datrise captures Harness entities such as pipelines, deployments, services, environments, execution logs and approvals, then lands normalized and typed models for warehouse reporting, attribution, and AI workflows.

The Harness NextGen Platform API (REST, `/ng/api` and `/v1` Beta resources) authenticates with API key, personal access token, incremental runs key on lastModifiedAt / updated timestamp fields on pipeline, execution, and entity list responses (exact field name varies per resource).

Of the 6 objects, 5 sync as upserts keyed on the primary key and 1 as append-only streams, so each incremental run moves only what changed since the last watermark. Every object lands in its own table (for example `harness_pipelines`) with a schema derived from the Harness API rather than a flattened CSV, in any of the 43 supported destinations.

Datrise is in early access: pick a destination below to open the Harness pipeline page, and join the waitlist to get the Harness connector with guided onboarding.

Incremental syncSchema-aware mapping43 destinations available

What Harness data Datrise extracts

Each object lands in its own typed table. Sync mode is derived from the object: history-style objects append, everything else upserts.

Object	Landing table	Sync mode
pipelines	harness_pipelines	Upsert by primary key, incremental on updated-at
deployments	harness_deployments	Upsert by primary key, incremental on updated-at
services	harness_services	Upsert by primary key, incremental on updated-at
environments	harness_environments	Upsert by primary key, incremental on updated-at
execution logs	harness_execution_logs	Append-only, incremental by timestamp
approvals	harness_approvals	Upsert by primary key, incremental on updated-at

Harness API: setup facts for the connector

Verified against the vendor documentation on 2026-09-02. Unknown values are left blank rather than guessed.

API	Harness NextGen Platform API (REST, `/ng/api` and `/v1` Beta resources)
Authentication	API key, personal access token — Requests carry a Harness API key (Service Account token or Personal Access Token) in the `x-api-key` header; Service Account tokens are recommended for automation since PATs are tied to and invalidated with an individual user.
Pagination	page — List endpoints take `limit` (default 30, max 100) and `page` query parameters, with `X-Total-Elements`, `X-Page-Number`, and `X-Page-Size` returned as response headers.
Rate limit	Not published
Incremental cursor	lastModifiedAt / updated timestamp fields on pipeline, execution, and entity list responses (exact field name varies per resource)
Webhooks	Yes — Harness Triggers (inbound Git/custom webhook triggers) and outbound notification webhooks on pipeline events
Bulk export	No
Deletes detectable	No — Deleted pipelines/projects return HTTP 404 on a subsequent GET; there is no dedicated deleted-entity feed documented.

Official API reference

What bites when replicating Harness

Harness publishes no numeric API rate limit or rate-limit headers; back off on HTTP `429` with your own exponential-backoff schedule rather than relying on a documented ceiling.
List endpoint pagination defaults to `limit=30` and caps at `limit=100`; requesting more is silently clamped, so a full-table pull needs the `X-Total-Elements` header to know when to stop paging.
The API is split across a NextGen `/ng/api` path and newer v1 Beta resources versioned under `/v1`; the same entity (e.g. pipelines) can expose different fields depending on which path you call.
Personal Access Tokens are tied to the creating user and are immediately invalidated if that user is deactivated, which silently breaks any integration authenticated with a `PAT` instead of a Service Account token.

Compare this against every other documented API

Popular destinations for Harness

Choose a destination below to open the ready pipeline page.

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Airtable
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Amazon Athena
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Amazon QuickSight
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Amazon Redshift
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Amazon S3 Data Lake
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Apache Superset
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Azure Data Lake Storage
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Azure Synapse
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Harness connector FAQ

What Harness data does the connector extract?: 6 objects: pipelines, deployments, services, environments, execution logs and approvals. Each lands in its own table with types preserved; history-style objects (1: execution logs) load as append-only streams.
Is the Harness integration incremental?: Yes. After the initial full load, every run reads only records changed since the last watermark (updated-at or event timestamp) and applies an upsert or an append depending on the object.
Where can I load Harness data?: Into 43 destinations: relational databases, cloud warehouses, data lakes, spreadsheets and BI tools. Each Harness → destination pair has its own page with the object-to-table mapping.

Related sources

Other sources in the same category, each with its own connector page.

Early access

Launch your Harness pipeline with guided onboarding

Join the waitlist to get priority access for Harness integrations with guided setup, schema-aware mapping, and production-grade incremental sync.