Dataflow has added the following features to tune horizontal

## Feature Feature Dataflow has added the following features to tune horizontal autoscaling for Streaming Engine jobs: * Latency tiers: You can configure the backlog threshold by choosing a latency tier (`low_latency`, `medium_latency`, or `high_latency`), allowing you to configure the autoscaler's sensitivity to backlog duration and balance latency requirements with resource costs. For more information, see[Set the latency tier](https://cloud.google.com/dataflow/docs/guides/tune-horizontal-autoscaling#latency-tier). * Autoscaling schedules: You can configure recurring autoscaling schedules to automatically apply parameter overrides—such as minimum and maximum workers, worker utilization hints, or latency tiers—during specific time windows. For more information, see[Schedule autoscaling changes](https://cloud.google.com/dataflow/docs/guides/tune-horizontal-autoscaling#scheduled-autoscaling). You can configure these features when you create a job or update them while the job is running.