Cross-region disaster recovery for Azure dedicated clusters is generally available
Self-service cross-region disaster recovery (DR) for Azure dedicated clusters is now generally available, which means DR is now available on all three cloud providers. You can configure a primary and a secondary dedicated cluster in different Azure regions, and fail over with minimal downtime and data loss.
Also shipped Aug 27, 2026Astronomer in August 2026 →
You can now train models using XGBoost version 2.1 by using the XGBOOST_VERSION option
You can now train models using XGBoost version 2.1 by using the XGBOOST_VERSION option. BigQuery uses the XGBoost 3.1.0 library to load and make predictions on XGBoost models. This feature is generally available .
CoCo in the Snowflake Extension for Visual Studio Code (General availability)
CoCo in the Snowflake Extension for Visual Studio Code is now generally available. CoCo runs in a side panel next to the extension's existing SQL and Snowpark Python workflows, so you can work locally while you stay connected to your Snowflake account.
Lakeflow Designer August Release
The Lakeflow Designer August release adds the Unique operator, expands the Aggregate, Select, and Python operators, and improves the canvas, preview, and version-history experience.
Genie Code is now available as a Lakeflow Jobs task (Beta)
You can now run prompts with Genie Code as a task in a Lakeflow Job. Genie Code runs your prompt autonomously. It can read upstream task outputs and call tools as needed. The task returns a link to the resulting Genie Code conversation with its response. See Genie Code task for jobs .
Genie Code for AI Runtime (Public Preview)
Use Genie Code to develop and troubleshoot deep learning workloads in notebooks connected to AI Runtime. Now in Public Preview , it generates distributed training code, resolves environment and dependency issues, and debugs GPU and distributed workload failures. See Use Genie Code with AI Runtime .
Share foreign Delta tables with OpenSharing (Public Preview)
You can now use OpenSharing to share foreign Delta tables, which are Delta-format tables registered in a foreign catalog such as OneLake, a Hive metastore, or AWS Glue. Providers add foreign Delta tables to a share, and recipients access the shared data in read-only format.
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Additional improvements
- Updated Astro infrastructure to improve stability and reliability.
Billing API added to the Astro v1 Labs API
Enterprise+ Organizations can now query Astro cost and usage data programmatically through the new List daily usage endpoint on the Astro v1 Labs API , which returns per-Deployment resource cost data with a FOCUS-formatted response option.
Improved hibernation schedule management
Hibernation schedules now display as a visual weekly chart instead of a list of cards or a CRON table. The chart shows every schedule on one week-long timeline, in both UTC and your local time zone, so you can see at a glance when a Deployment will be awake or hibernating.
Additional improvements
- Ask Otto can now read, edit, save, deploy, and run tasks for an open Astro IDE session.
Export infrastructure metrics to Datadog
You can now create a Datadog (infrastructure metrics) metrics export to send Deployment infrastructure metrics directly to Datadog, in addition to the existing Prometheus Remote Write export type.
Proxy-aware IP allowlisting
If you route Astro traffic through a forward proxy or secure tunnel, such as Zscaler, you can now turn on Proxy-Aware IP Allowlisting on the IP Access List page to also accept the egress IP address of that proxy or tunnel as a valid match.
Cross-region disaster recovery for GCP dedicated clusters is generally available
Self-service cross-region disaster recovery (DR) for GCP dedicated clusters is now generally available. You can configure a primary and a secondary dedicated cluster in different GCP regions, and fail over with minimal downtime and data loss.
Task-level utilization metrics
Astro now shows CPU and memory utilization at the Dag, task, and task instance level in a new Resource Metrics tab in the Airflow UI, with task-to-worker mapping that ties resource use back to the Dag, task, task run, and time window.