Airflow API (Stable)

Name: Airflow API (Stable) API
Brand: Airflow API (Stable)
Availability: InStock

✓ Official Vendor SpecDeveloper ToolsCi Cdbasic, openIdConnect, http89 EndpointsREST

For Agents

Trigger DAG runs, inspect task instances, and manage Airflow connections, variables, and datasets across an Apache Airflow deployment.

Connect the Airflow API (Stable) to your agent

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

Install Jentic One Beta (Self-Hosted)

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

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 Airflow API (Stable) API.

Trigger a new DAG run with a custom configuration payload and capture the run id

Inspect the state of a DAG run and its task instances, including logs and try numbers

Pause, unpause, and update DAGs, including retrieving the parsed source

Manage Airflow connections, variables, and pools used by tasks at runtime

GET STARTED

Start building with Airflow API (Stable) API

Explore with Jentic

View OpenAPI Document

Apache Airflow is the open-source workflow orchestration platform used to schedule and monitor data pipelines, ML training runs, and ETL jobs. The stable REST API exposes DAGs, DAG runs, task instances, connections, variables, datasets, pools, and XComs so external systems can trigger runs, inspect state, and manage Airflow's metadata without going through the web UI. Authentication options include HTTP basic, Google OpenID Connect, and Kerberos, configured per Airflow deployment. The base URL is the /api/v1 path on whichever host runs the Airflow webserver.

Use Cases

Patterns agents use Airflow API (Stable) API for, with concrete tasks.

★ Trigger a pipeline from an external system

Kick off an Airflow DAG run from a service outside Airflow, for example a webhook from a SaaS app or an event from a message broker. The agent posts to /dags/{dag_id}/dagRuns with a config payload, then polls /dags/{dag_id}/dagRuns/{dag_run_id} for state until it reaches success or failure. This avoids hard-wiring schedules and keeps the trigger event observable in Airflow's UI.

POST to /dags/sales_etl/dagRuns with {"conf": {"date": "2026-06-09"}} and then GET /dags/sales_etl/dagRuns/{dag_run_id} every 30 seconds until state is success or failed

Operational dashboard over Airflow state

Build a custom dashboard that surfaces DAG and task health beyond what the Airflow UI offers, for example aggregated SLA misses or per-team DAG ownership. The agent calls /dags to list DAGs, /dags/{dag_id}/dagRuns for run history, and /dags/{dag_id}/dagRuns/{dag_run_id}/taskInstances for fine-grained task state.

GET /dags, then for each dag GET /dags/{dag_id}/dagRuns?limit=20 and aggregate failed-run counts per team for a Slack digest

Recover failed task instances

When a downstream service was briefly down, recover failed task instances by clearing them so Airflow reschedules. The agent identifies failed task instances via /dags/{dag_id}/dagRuns/{dag_run_id}/taskInstances and POSTs to /dags/{dag_id}/clearTaskInstances to reset them, optionally including downstream tasks.

GET /dags/{dag_id}/dagRuns/{dag_run_id}/taskInstances filtered to state=failed, then POST to /dags/{dag_id}/clearTaskInstances with the failed task ids and include_downstream=true

Manage connections and variables programmatically

Manage Airflow connections (database URLs, API tokens, cloud credentials) and variables from automation rather than the web UI. Useful for environment promotion or rotating credentials. The agent uses /connections and /variables endpoints to create, update, and test entries, and POSTs /connections/test to validate before saving.

POST /connections/test with the new connection payload, then PATCH /connections/{connection_id} once the test returns success

AI agent integration via Jentic

An agent that needs to operate an Airflow deployment from natural language can search Jentic for 'trigger an Airflow DAG' and Jentic returns the schema for /dags/{dag_id}/dagRuns. Jentic stores the deployment's auth (basic, OIDC, or Kerberos) and base URL so the agent does not handle credentials or hostnames.

Search Jentic for 'trigger an Airflow DAG', load the /dags/{dag_id}/dagRuns schema, and execute it for the user-named DAG

Key Endpoints

89 endpoints — apache airflow is the open-source workflow orchestration platform used to schedule and monitor data pipelines, ml training runs, and etl jobs.

METHOD

PATH

DESCRIPTION

POST

/dags/{dag_id}/dagRuns

Trigger a new DAG run

GET

/dags/{dag_id}/dagRuns/{dag_run_id}

Get a DAG run by id

GET

/dags

List all DAGs registered in the deployment

GET

/dags/{dag_id}

Fetch a single DAG's metadata

POST

/dags/{dag_id}/clearTaskInstances

Clear task instances to reschedule failed runs

GET

/connections

List Airflow connections

POST

/connections/test

Test a connection definition before saving

GET

/variables

List Airflow variables

POST

/dags/{dag_id}/dagRuns

Trigger a new DAG run

GET

/dags/{dag_id}/dagRuns/{dag_run_id}

Get a DAG run by id

GET

/dags

List all DAGs registered in the deployment

GET

/dags/{dag_id}

Fetch a single DAG's metadata

POST

/dags/{dag_id}/clearTaskInstances

Clear task instances to reschedule failed runs

Why though Jentic?

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

Credential isolation

Airflow auth (basic, OIDC, or Kerberos) is stored encrypted in the Jentic vault (MAXsystem). The agent receives a scoped context, while the actual Authorization header is attached server-side per call.

Intent-based discovery

Agents search Jentic by intent ('trigger an Airflow DAG', 'list failed task instances') and Jentic returns the matching Airflow operation with its parameter schema, removing the need to consult the Airflow REST docs.

Time to first call

Direct integration: half a day to a day depending on auth backend (Kerberos in particular needs ticket setup). Through Jentic: under an hour - search, load, execute.

Related APIs

Alternatives and complements available in the Jentic catalogue.

Alternative

Prefect API

Workflow orchestration with a hosted control plane and Python-first flow definitions.

Pick Prefect for hosted orchestration with a hosted UI; pick Airflow when running self-hosted DAGs in Python with the existing operator ecosystem.

Alternative

Temporal API

Durable workflow execution with code-defined workflows and signals.

Pick Temporal for long-running stateful workflows with strong replay semantics; pick Airflow for batch and ETL DAGs scheduled by cron.

Complementary

GitHub API

Source the DAGs from a GitHub repo and react to commits.

Use GitHub to manage DAG source and CI; use Airflow API to trigger or inspect runs after merges.

FAQs

Specific to using Airflow API (Stable) API through Jentic.

What authentication does the Airflow API use?

The spec declares three options: HTTP Basic, Google OpenID Connect, and Kerberos (negotiate). Which one is active depends on the deployment's auth backend in airflow.cfg. Through Jentic the chosen credential is stored in the encrypted MAXsystem vault and attached server-side, so the agent never sees the raw secret.

Can I trigger a DAG run with a custom config through the API?

Yes. POST to /dags/{dag_id}/dagRuns with a JSON body including a conf object that the DAG code reads via context['dag_run'].conf. The response returns the new dag_run_id which can be polled via GET /dags/{dag_id}/dagRuns/{dag_run_id} for state.

How do I trigger an Airflow DAG through Jentic?

Search Jentic for 'trigger an Airflow DAG', load the schema for POST /dags/{dag_id}/dagRuns, and execute it with the dag id and the conf payload. Jentic injects the configured auth and base URL for your Airflow deployment.

What are the rate limits for the Airflow API?

Apache Airflow itself does not enforce a global rate limit; throughput is bounded by the webserver's worker pool and the underlying metadata database. In practice deployments sit behind a reverse proxy that may add request limits.

Can I clear failed task instances to retry them?

Yes. POST to /dags/{dag_id}/clearTaskInstances with a list of task ids and optional include_downstream and reset_dag_runs flags, and Airflow re-queues the cleared tasks. This is the API equivalent of the UI's clear button.

Is the Airflow API free to use?

Apache Airflow is open source under the Apache 2.0 license, so the API itself is free. Cost is the infrastructure that runs the webserver, scheduler, and workers - or a managed offering such as Astronomer or AWS MWAA.