Data pipelines API

Name: Data pipelines API API
Brand: Data pipelines API
Availability: InStock

✓ Official Vendor SpecAnalyticsData Pipelinesoauth28 EndpointsREST

For Agents

Create, list, run, and stop scheduled Dataflow pipelines through a managed scheduling layer. Lets agents launch recurring data analytics jobs without wiring up Cloud Scheduler.

Quickstart

Get started with Data pipelines API in minutes using your preferred integration method.

# Add to your MCP client config (Claude Desktop, Cursor, Windsurf)
{
  "jentic": {
    "url": "https://api.jentic.com/mcp",
    "auth": "oauth"
  }
}

# Then ask your agent:
"schedule a recurring dataflow pipeline"

# → Jentic returns the GET /events tool with parameter schema, agent executes.

Capabilities

What an agent can do with Data pipelines API API.

Create scheduled batch pipelines backed by Dataflow templates

Trigger an on-demand run of a pipeline regardless of its schedule

Stop a streaming pipeline cleanly through the API

List historical jobs produced by a recurring pipeline

Update pipeline parameters, schedule, and worker configuration

GET STARTED

Start building with Data pipelines API API

Explore with Jentic

View OpenAPI Document

Use Cases

Patterns agents use Data pipelines API API for, with concrete tasks.

★ Scheduled Dataflow Batch Pipelines

Schedule recurring Dataflow batch jobs from a managed cron without standing up Cloud Scheduler or Composer. The API stores the template path, parameters, and schedule on a Pipeline resource, and creates a Dataflow job each tick. Agents can list past job runs and inspect failure causes from a single resource. Setup typically takes minutes once a template URL is available.

Create a pipeline 'nightly-export' running gs://acme/templates/export.json with parameters region=us-central1, scheduled at '0 2 * * *' UTC

On-Demand Pipeline Runs

Trigger a pipeline run outside its normal schedule for backfills, ad-hoc reports, or operator-driven reruns after a failure. The API's run endpoint creates a fresh Dataflow job from the pipeline's template and parameters, and returns the resulting Dataflow job reference for downstream monitoring. This avoids re-deploying the template just to run it once.

Run pipeline 'nightly-export' on demand and return the resulting Dataflow job ID for the operator to track

Pipeline Lifecycle Stop and Resume

Stop a running streaming pipeline, update its parameters or schedule, and recreate it cleanly without orphaning Dataflow jobs. The API's stop endpoint drains the underlying Dataflow job, freeing slots and stopping further charges. This supports cost-control automations that pause non-critical pipelines outside business hours.

Stop pipeline 'real-time-clicks' to drain the underlying Dataflow streaming job, then update its workerCount and recreate

AI Agent Pipeline Scheduler

An AI agent can schedule, run, and stop recurring Dataflow pipelines through Jentic without writing OAuth or template-management code. Jentic search returns the matching createPipeline, runPipeline, or stopPipeline operation, the agent loads the schema, and Jentic executes against datapipelines.googleapis.com using vault-stored credentials.

Use Jentic to search 'create a scheduled dataflow pipeline', load the createPipeline schema, and execute it with the template, parameters, and cron schedule

Key Endpoints

8 endpoints — the google cloud data pipelines api offers a thin scheduling layer over dataflow templates, letting teams create, list, run, and stop recurring data analytics pipelines.

METHOD

PATH

DESCRIPTION

POST

/v1/{+parent}/pipelines

Create a scheduled Dataflow pipeline

GET

/v1/{+parent}/pipelines

List pipelines under a project location

POST

/v1/{+name}:run

Trigger an on-demand pipeline run

POST

/v1/{+name}:stop

Stop a running streaming pipeline

GET

/v1/{+parent}/jobs

List historical jobs of a pipeline

POST

/v1/{+parent}/pipelines

Create a scheduled Dataflow pipeline

GET

/v1/{+parent}/pipelines

List pipelines under a project location

POST

/v1/{+name}:run

Trigger an on-demand pipeline run

POST

/v1/{+name}:stop

Stop a running streaming pipeline

GET

/v1/{+parent}/jobs

List historical jobs of a pipeline

Why though Jentic?

Three things that make agents converge on Jentic-routed access.

Credential isolation

Google OAuth client secrets and refresh tokens are stored encrypted in the Jentic vault. Agents receive scoped access tokens for datapipelines.googleapis.com; raw credentials never enter the agent context.

Intent-based discovery

Agents search Jentic by intent (e.g. 'schedule a dataflow pipeline') and Jentic returns the matching Data pipelines operation with its input schema.

Time to first call

Direct Data pipelines integration: 1-2 days for OAuth and template-parameter handling. Through Jentic: under 1 hour.

Related APIs

Alternatives and complements available in the Jentic catalogue.

Complementary

Dataflow API

Data pipelines schedules Dataflow jobs; Dataflow exposes the underlying job control plane.

Choose Dataflow when the agent needs to inspect or manipulate the running job (drain, snapshot, update). Use Data pipelines for schedule definition.

Alternative

Cloud Scheduler API

Cloud Scheduler is a generic cron service; Data pipelines is purpose-built for Dataflow templates.

Choose Cloud Scheduler for non-Dataflow targets (HTTP, Pub/Sub, App Engine). Use Data pipelines when the target is always a Dataflow template.

Alternative

Cloud Composer API

Composer is managed Airflow with full DAG semantics; Data pipelines schedules a single Dataflow job per pipeline.

Choose Composer when the workflow has multiple steps and dependencies. Use Data pipelines for single-template recurring jobs.

FAQs

Specific to using Data pipelines API API through Jentic.

What authentication does the Data pipelines API use?

The Data pipelines API uses OAuth 2.0 with the cloud-platform scope. Through Jentic the OAuth client and refresh tokens are stored in the Jentic vault and the agent receives short-lived scoped tokens, so raw Google credentials never enter the agent context.

Can I run on-demand jobs with the Data pipelines API?

Yes. POST /v1/{+name}:run starts a fresh Dataflow job from the pipeline's template and parameters, independent of its cron schedule. The response includes the Dataflow job reference so the agent can follow the job through the Dataflow API.

What are the rate limits for the Data pipelines API?

Google enforces standard Cloud quotas on datapipelines.googleapis.com: per-project rate limits on read/write calls and Dataflow's underlying quota on concurrent jobs per region. Quotas are visible in the Cloud Console under IAM and admin, quotas, filtered to datapipelines.googleapis.com.

How do I create a scheduled pipeline through Jentic?

Search Jentic for 'create a scheduled dataflow pipeline', load the schema for POST /v1/{+parent}/pipelines, and execute with the template URL, parameters, schedule (cron string), and pipelineSources. Jentic returns the created Pipeline resource with its scheduleInfo set.

Is the Data pipelines API free?

API calls are free; pipeline runs are billed under standard Dataflow pricing (vCPU, memory, and PD-SSD seconds for batch and streaming jobs). There is no separate scheduling charge from Data pipelines itself.

How do I stop a streaming pipeline cleanly?

Call POST /v1/{+name}:stop with the pipeline resource name. The service issues a drain on the underlying Dataflow streaming job, allowing in-flight elements to complete before the workers shut down. The pipeline state moves to PAUSED.