Product

How Jentic Works

From API assessment to production deployment in four simple steps.

Product Overview

PLATFORM

Jentic OneSelf-hosted, open-source control plane between your agents and any APIAPI DirectoryBrowse 10,000+ APIs ready for AI agent integrationAPI ScorecardAssess your APIs for AI-readiness with automated scoringAgentic SandboxSafely simulate AI agents with your production APIsJenticSign in to the Jentic web app

CAPABILITIES

IntegrationConnect AI agents to your existing systemsWorkflowsDiscover and capture successful agent workflowsGovernanceDefine, observe, and enforce AI policies

TOOLS

Arazzo UIVisualize Arazzo workflows as interactive documentationArazzo EditorBuild and edit multi-step API workflows visually
Pricing
Developers

GET STARTED

DocumentationGuides and API referenceQuickstartGet up and running in minutes

COMMUNITY

GitHubOpen source projects and examples
Resources
BlogLatest articles and insightsPress & MediaBrand assets and press contactOpen StandardsBuilt on open specs. Never locked in.NewsletterAPIs, AI agents, mixed with architecture and strategy.
Company
About UsOur mission and teamCareersJoin our teamContactGet in touch
Install Jentic OneBook a Demo
How Jentic WorksJentic OneAPI DirectoryAPI ScorecardAgentic SandboxJenticIntegrationWorkflowsGovernanceArazzo UIArazzo Editor
Pricing
DocumentationQuickstartGitHub
BlogPress & MediaOpen StandardsNewsletter
About UsCareersContact
Request a demoInstall Jentic One
Jentic
For Enterprises
  • Product Overview
  • Agentic Sandbox
  • Book a Demo
For Developers
  • Jentic One
  • Documentation
  • GitHub
Company
  • About Jentic
  • Careers
  • Contact Us
ISO/IEC 27001:2022 certification badge issued by Prescient Security

Information Security Management System

Certified to ISO/IEC 27001:2022 by Prescient Security

Terms & Conditions•Privacy Policy•
© 2026 Jentic. All rights reserved.
APIs / Analytics / Google / Dataflow API
Dataflow API logo

Google Dataflow API

Browse all Google APIs
✓ Official Vendor SpecAnalyticsData Pipelinesoauth241 EndpointsREST

For Agents

Launch Apache Beam pipelines from templates, monitor job state and worker metrics, and drain streaming jobs so an agent can run and govern Dataflow workloads.

Use for: I need to launch a Dataflow job from a Flex Template, List all currently running streaming jobs in europe-west1, Retrieve the state and metrics of a specific job, Drain a streaming job before redeploying it

Not supported: Does not author Apache Beam code, store data, or schedule recurring runs — use only to launch, monitor, drain, and snapshot Dataflow jobs.

Google Cloud Dataflow API is the control plane for streaming and batch Apache Beam pipelines on Google Cloud. It exposes endpoints to launch jobs from Flex or classic templates, list and inspect jobs and their workers, drain or cancel running streaming jobs, and update the parameters of in-flight pipelines. The API also surfaces job metrics, debug snapshots, and template metadata so platform teams can build dashboards and self-service launchers without bespoke Beam code. Jobs run on managed worker VMs in the chosen region, with autoscaling controlled per job.

Jentic One on GithubView OpenAPI Document

Install Jentic One Beta

Connect the Dataflow API to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Dataflow API, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.

Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.

1

Step 1: Jentic One Host machine

# On the machine that will host your Jentic One instance:
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh
2

Step 2: Agent machine

# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh
jentic register       # connects your agent to your Jentic One instance

Jentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.

Capabilities

What an agent can do with Dataflow API.

Launch a Dataflow job from a Flex Template or classic template with custom parameters

List jobs in a project and region with filters by state and creation time

Retrieve job graph, current state, and per-stage metrics

Drain or cancel a running streaming job to release resources gracefully

Update parameters or transformation graph of an in-flight pipeline

Snapshot a streaming job for replay or rollback

List supported Flex Templates and inspect their input parameter metadata

Use Cases

Patterns agents use Dataflow API for, with concrete tasks.

★ Self-Service Pipeline Launch

A data platform team publishes Flex Templates for common ETL shapes and a portal calls the Dataflow API to launch them with user-supplied parameters. Each launch returns a job ID and immediate state, then the portal polls the job for progress. End users start a pipeline without touching gcloud or Beam code.

Launch the Flex Template at gs://templates/etl-template-spec.json in us-central1 with parameters input='gs://raw/2026-06-10' and output='bq:proj.ds.facts'.

Streaming Job Lifecycle Management

A SRE runbook drains a streaming job, deploys a new version, and snapshots the previous state for rollback. The Dataflow API exposes drain and snapshot operations so the runbook completes without manual Console steps. Drains preserve in-flight messages instead of dropping them.

Drain streaming job 'jid-2026-06-10-abc' in us-central1 and create a snapshot named 'pre-deploy-snap' before launching the new version.

Failed Job Triage Bot

A Slack bot monitors Dataflow for jobs entering JOB_STATE_FAILED and posts the job ID, error log link, and last successful checkpoint. The Dataflow API supplies job state, current workers, and error messages so the bot can surface high-signal context. Engineers click through to logs only when needed.

List jobs in us-central1 with stateFilter=ACTIVE created in the last 24 hours, return any whose currentState is JOB_STATE_FAILED with their error messages.

Capacity and Cost Telemetry

A FinOps dashboard collects per-job worker counts, vCPU hours, and shuffled data from the Dataflow API metrics endpoint and aggregates them per team. Teams see cost drivers without opening individual job pages. Decisions to right-size workers are grounded in actual Dataflow telemetry.

Get the metrics for job 'jid-2026-06-10-xyz' and return totalVcpuTime and currentNumWorkers.

AI Agent Pipeline Operator

An on-call AI agent gets a 'job lagging' alert, asks Jentic for the Dataflow API operations needed, retrieves current watermark and worker count, and drains/relaunches the job with more workers. Jentic isolates the Google service account credential so raw keys never enter the agent context.

For job 'jid-2026-06-10-zzz', get its watermark and worker count, drain if watermark lag exceeds 5 minutes, and relaunch the same Flex Template with maxWorkers doubled.

Key Endpoints

41 endpoints — google cloud dataflow api is the control plane for streaming and batch apache beam pipelines on google cloud.

METHOD

PATH

DESCRIPTION

GET

/v1b3/projects/{projectId}/jobs

List jobs in a project

GET

/v1b3/projects/{projectId}/jobs/{jobId}

Get a specific job's state and graph

POST

/v1b3/projects/{projectId}/locations/{location}/flexTemplates:launch

Launch a job from a Flex Template

POST

/v1b3/projects/{projectId}/jobs/{jobId}/debug/sendCapture

Send a debug capture for a job

GET

/v1b3/projects/{projectId}/jobs/{jobId}/debug/getConfig

Get the debug config for a job

GET

/v1b3/projects/{projectId}/jobs

List jobs in a project

GET

/v1b3/projects/{projectId}/jobs/{jobId}

Get a specific job's state and graph

POST

/v1b3/projects/{projectId}/locations/{location}/flexTemplates:launch

Launch a job from a Flex Template

POST

/v1b3/projects/{projectId}/jobs/{jobId}/debug/sendCapture

Send a debug capture for a job

GET

/v1b3/projects/{projectId}/jobs/{jobId}/debug/getConfig

Get the debug config for a job

Why Jentic?

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

Credential management

Credential isolation

Google service account credentials are stored encrypted in the Jentic vault. Agents call dataflow.googleapis.com with short-lived OAuth access tokens with the cloud-platform scope, never the underlying JSON key.

Intent-based discovery

Intent-based discovery

Agents search Jentic for 'launch dataflow pipeline' and Jentic returns the flexTemplates.launch and jobs.update operations with their full request schemas, including parameter maps and requestedState values.

Time to first call

Time to first call

Direct integration: 2-3 days to handle OAuth, regional endpoints, Flex Template parameter validation, and long-running operation polling. Through Jentic: under 1 hour for the same scope of pipeline orchestration.

Related APIs

Alternatives and complements available in the Jentic catalogue.

Complementary

Google BigQuery API

→

Common sink and source for Dataflow pipelines

Pair with Dataflow when the pipeline reads from or writes to BigQuery tables

Complementary

Google Cloud Pub/Sub API

→

Streaming source for low-latency Dataflow jobs

Use Pub/Sub topics as the input to streaming Dataflow pipelines

Alternative

Google Cloud Dataproc API

→

Managed Spark and Hadoop alternative for batch data processing

Choose Dataproc when teams already use Spark/Hadoop; choose Dataflow for Beam unified streaming and batch

Alternative

Google Cloud Data Fusion API

→

Visual pipeline builder that compiles to Dataflow under the hood

Choose Data Fusion when low-code authoring is preferred; choose Dataflow when full Beam control is required

FAQs

Specific to using Dataflow API through Jentic.

What authentication does the Google Cloud Dataflow API use?

The Dataflow API uses Google OAuth 2.0 with the cloud-platform scope. Through Jentic the service account credentials are stored encrypted in the Jentic vault and the agent receives scoped, short-lived access tokens per request.

Can I launch a Dataflow job from a Flex Template using only the Dataflow API?

Yes. Call /v1b3/projects/{projectId}/locations/{location}/flexTemplates:launch with the template GCS spec URI and a parameters map. The response contains the new job's ID and current state, and you can poll the job endpoint until it reaches JOB_STATE_RUNNING.

What are the rate limits for the Google Cloud Dataflow API?

Dataflow applies per-project quotas on jobs.create and jobs.list, plus per-region worker and vCPU quotas that limit how many concurrent jobs can run. Inspect the Cloud Console Quotas page for the precise limits in your project.

How do I drain a streaming job through Jentic?

Run pip install jentic, search Jentic for 'drain dataflow streaming job', load the schema for jobs.update on dataflow.googleapis.com, and execute it with the job ID and requestedState=JOB_STATE_DRAINED.

Does the Dataflow API let me write or compile Apache Beam code?

No. This API is a control plane: launching, monitoring, draining, and snapshotting jobs whose Beam graph is supplied as a template or compiled artifact. Beam pipeline development happens locally with the Beam SDK before publishing a template.

GET STARTED

Start building with Dataflow API

Explore with Jentic
View OpenAPI Document