Dataflow has updated and expanded its pipeline update features for streaming jobs:

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 explicitly choose between a parallel update (update_strategy_parallel_job_update) and a standard in-place update (update_strategy_in_place_update) while keeping all other configuration the same. • Template upsert functionality: When launching pipelines from classic templates, flex templates, Terraform, or Config Connector, you can use the create_or_update_job experiment to enable automatic create-or-update (upsert) behavior. If an active job with the specified name already exists, it is updated. Otherwise, a new job is created.

For more information, see Automated stop and replace, Automated parallel pipeline updates, and Automatic create or update (upsert) for templates.