Dataflow enhances streaming pipeline updates
Dataflow has expanded its streaming pipeline update capabilities with features like automated stop-and-replace, parallel updates under the same job name, and auto-cancellation of draining jobs. These enhancements allow for more robust and flexible management of streaming jobs, impacting engineers and architects responsible for data pipelines. The update strategy configuration and template upsert functionality offer improved control and automation for pipeline deployments.
Features (1) ›
- Dataflow
Dataflow has updated and expanded its pipeline update features for streaming jobs: Automated stop-and-replace updates : You can perform automated, declarative stop-and-replace updates to streaming jobs. Parallel updates with the same job name : When you perform automated parallel updates, you can use the same job name for the new replacement job. Auto-cancel draining jobs : When performing parallel or stop-and-replace updates, you can configure Dataflow to automatically cancel the old job if it does not finish draining after a timeout you specify. Update strategy configuration : You can explic
https://docs.cloud.google.com/release-notes#June_15_2026