Dataflow has updated and expanded its pipeline update features for

## Feature Feature 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](https://cloud.google.com/dataflow/docs/guides/upgrade-guide#automated-stop-replace), [Automated parallel pipeline updates](https://cloud.google.com/dataflow/docs/guides/upgrade-guide#automated-parallel-updates), and[Automatic create or update (upsert) for templates](https://cloud.google.com/dataflow/docs/guides/upgrade-guide#templates-create-or-update).