apache-airflow-providers-opsgenie
Provider package apache-airflow-providers-opsgenie for Apache Airflow
Decision gist · record as of 2026-08-14
Yes. This is a production-stable, actively maintained provider package with low install friction and no known vulnerabilities. Install it if you run Apache Airflow and use Opsgenie for incident management and want to integrate workflow alerts into your on-call system. The Apache 2.0 license poses no restrictions.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires an existing Apache Airflow installation (>=2.11.0) and Opsgenie API credentials configured in Airflow connections.
- Low install friction; pure Python wheel.
- Actively maintained with recent release (68 days old).
License · maintenance · safety
Apache-2.0 (permissive) — Apache License 2.0 (permissive) — you may use, modify, and distribute this package freely in commercial and open-source projects with minimal restrictions.
last release 2026-06-07 (68 days) · last repo commit 2026-08-14 · 46,490 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 969,022 downloads/mo, #4,614 on PyPI
Alternatives
Verify before relying
pip install apache-airflow-providers-opsgenie
from airflow.providers.opsgenie.operators.opsgenie import OpsgenieAlertOperator
task = OpsgenieAlertOperator(
task_id='send_alert',
message='Workflow alert',
conn_id='opsgenie_default'
)- Specific operator and hook classes available in this version beyond basic alert sending.
- Whether the package supports Opsgenie features like escalation policies, on-call schedules, or custom fields.
- Integration with Airflow's sensor framework for monitoring Opsgenie incidents.
What it is and what it does
This is an Apache Airflow provider package that bridges Airflow workflows with Opsgenie, Atlassian's incident management platform. It enables Airflow DAGs to send alerts and notifications to Opsgenie, allowing you to route workflow failures and custom events into your incident management system. The package is built on top of the opsgenie-sdk and integrates with Airflow's operator and hook framework.
The package is actively maintained as part of the Apache Airflow ecosystem, supports Python 3.10 through 3.14, and requires Apache Airflow >=2.11.0. It installs as a pure Python wheel with low friction and depends on apache-airflow, apache-airflow-providers-common-compat, and opsgenie-sdk. No known security vulnerabilities are recorded.
Use it for
- Send Airflow task failure alerts to Opsgenie to trigger incident response workflows.
- Route custom workflow events and metrics to Opsgenie for centralized alerting.
- Integrate Airflow monitoring into an existing Opsgenie-based on-call rotation.
- Automate incident creation in Opsgenie when specific DAG conditions are met.
- Combine Airflow orchestration with Opsgenie escalation policies for critical jobs.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
This is a production-stable, actively maintained provider package with low install friction and no known vulnerabilities. Install it if you run Apache Airflow and use Opsgenie for incident management and want to integrate workflow alerts into your on-call system. The Apache 2.0 license poses no restrictions.
Install
apache-airflow-providers-opsgenie on PyPI
Before you install
Low install friction; pure Python wheel. Actively maintained with recent release (68 days old). Requires Apache Airflow >=2.11.0 and opsgenie-sdk >=2.1.5 as runtime dependencies.
Requires an existing Apache Airflow installation (>=2.11.0) and Opsgenie API credentials configured in Airflow connections.
License in practice
Apache License 2.0 (permissive) — you may use, modify, and distribute this package freely in commercial and open-source projects with minimal restrictions.
Quickstart
pip install apache-airflow-providers-opsgenie
from airflow.providers.opsgenie.operators.opsgenie import OpsgenieAlertOperator
task = OpsgenieAlertOperator(
task_id='send_alert',
message='Workflow alert',
conn_id='opsgenie_default'
)
Verify before relying
- Specific operator and hook classes available in this version beyond basic alert sending.
- Whether the package supports Opsgenie features like escalation policies, on-call schedules, or custom fields.
- Integration with Airflow's sensor framework for monitoring Opsgenie incidents.
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 3 packagesapache-airflowapache-airflow-providers-common-compatopsgenie-sdk |
| Maintenance | Actively maintained 68 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 969,022 / month, #4,614 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableEnvironment :: ConsoleEnvironment :: Web EnvironmentFramework :: Apache AirflowFramework :: Apache Airflow :: ProviderIntended Audience :: DevelopersIntended Audience :: System AdministratorsProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: System :: Monitoring |
Evidence: apache_airflow_providers_opsgenie-5.10.4-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “airflow opsgenie integration”
- apache-airflow-providers-opsgenieIntegrates Apache Airflow with Opsgenie to send alerts and…
- opsgenie-sdkPython client library for the Opsgenie REST API, enabling…
- apache-airflow-providers-cloudantProvides Apache Airflow operators and hooks to integrate IBM Cloudant…
Give your agent the search over MCP, or paste the wish link into any chat.
More Monitoring packages
Wraps any iterable to display a real-time progress bar in the terminal or Jupyter notebook, showing iteration count, elapsed time, and estimated time remaining.
Provides generated Python code for OpenTelemetry semantic conventions, enabling standardized attribute naming and constant definitions for instrumentation and telemetry collection.
Install it if you are using OpenTelemetry and want to follow semantic conventions correctly.
Provides the reference implementation of the OpenTelemetry API for collecting and exporting traces, metrics, and logs from Python applications.
Provides the abstract API and interfaces for OpenTelemetry instrumentation in Python, defining how to emit traces, metrics, and logs without tying code to a specific SDK implementation.
Exports OpenTelemetry observability data to an OpenTelemetry Collector using Protobuf-encoded messages over HTTP.
Install it if you are using OpenTelemetry in Python and need to send data to a Collector over HTTP.
Provides automatic instrumentation commands and programmatic APIs to inject distributed tracing into Python applications without code changes, detecting and instrumenting packages used by your program.
Install it if you need distributed tracing without code changes and have compatible instrumented packages in your environment.
See also apache-airflow-providers-pagerduty · opsgenie-sdk · apache-airflow-providers-datadog · apache-airflow-providers-apprise · apache-airflow-providers-discord · apache-airflow-providers-asana · apache-airflow-providers-segment · apache-airflow-providers-jenkins · apache-airflow-providers-zendesk · apache-airflow-providers-sendgrid