# Apache Airflow 2.10.0 is here

DevFeed: [Apache Airflow 2.10.0 is here](<https://devfeed.tech/articles/apache-airflow-2-10-0-is-here-32531.md>)

Original publisher: [Read original article](<https://airflow.apache.org/blog/airflow-2.10.0/>)

Author: Apache Airflow

Published: 2024-08-08T00:00:00Z

Content type: release

Language: en

Sources: [Apache Airflow Blog](<https://devfeed.tech/sources/apache-airflow-blog.md>)

Topics: [airflow](<https://devfeed.tech/topics/airflow.md>), [releases](<https://devfeed.tech/topics/releases.md>), [telemetry](<https://devfeed.tech/topics/telemetry.md>), [configuration](<https://devfeed.tech/topics/configuration.md>), [data](<https://devfeed.tech/topics/data.md>), [PyPI](<https://devfeed.tech/topics/pypi.md>), [Docker Image](<https://devfeed.tech/topics/docker-image.md>)

Tags: [airflow](<https://devfeed.tech/tags/airflow.md>), [apache-airflow](<https://devfeed.tech/tags/apache-airflow.md>), [configuration](<https://devfeed.tech/tags/configuration.md>), [docker-image](<https://devfeed.tech/tags/docker-image.md>), [pypi](<https://devfeed.tech/tags/pypi.md>), [release](<https://devfeed.tech/tags/release.md>), [release-notes](<https://devfeed.tech/tags/release-notes.md>), [releases](<https://devfeed.tech/tags/releases.md>), [telemetry](<https://devfeed.tech/tags/telemetry.md>)

## AI overview

Apache Airflow 2.10.0 is available with default basic telemetry collection, support for multiple executors in one environment, and dynamic dataset scheduling through DatasetAlias. Deployments can opt out of telemetry collection.

## Source excerpt

I'm happy to announce that Apache Airflow 2.10.0 is now available, bringing an array of noteworthy enhancements and new features that will greatly serve our community. Details: 📦 PyPI: https://pypi.org/project/apache-airflow/2.10.0/ 📚 Docs: https://airflow.apache.org/docs/apache-airflow/2.10.0/ 🛠 Release Notes: https://airflow.apache.org/docs/apache-airflow/2.10.0/release_notes.html 🐳 Docker Image: "docker pull apache/airflow:2.10.0" 🚏 Constraints: https://github.com/apache/airflow/tree/constraints-2.10.0 Airflow now collects Telemetry data by default With the release of Airflow 2.10.0, we've introduced the collection of basic telemetry data, as outlined here. This data will play a crucial role in helping Airflow maintainers gain a deeper understanding of how Airflow is utilized across various deployments. The insights derived from this information are invaluable in guiding the prioritization of patches, minor releases, and security fixes. Moreover, this data will inform key decisions regarding the development roadmap, ensuring that Airflow continues to evolve in line with community needs. For those who prefer not to participate in data collection, deployments can easily opt out by setting the [usage_data_collection] enabled option to False or by using the SCARF_ANALYTICS=false environment variable. Multiple Executor Configuration (formerly "Hybrid Execution") Each executor comes with its unique set of strengths and weaknesses, typically balancing latency, isolation, and compute efficiency. Traditionally, an Airflow environment is limited to a single executor, requiring users to make trade-offs, as no single executor is perfectly suited for all types of tasks. We are introducing a new feature that allows for the concurrent use of multiple executors within a single Airflow environment. This flexibility enables users to take advantage of the specific strengths of different executors for various tasks, improving overall efficiency and mitigating weaknesses. Users can s