A Ray cluster on Vertex AI is a managed collection of compute nodes for running distributed Python and machine learning workloads. It provides scalable infrastructure for parallel processing, long-running distributed tasks, and capacity-controlled ML workflows within Vertex AI.
A Ray cluster on Vertex AI is a managed cluster of compute nodes that can be used to run distributed machine learning (ML) and Python applications. It provides the infrastructure to perform distributed computing and parallel processing for your ML workflow. Ray clusters are built into Vertex AI to ensure capacity availability for critical ML workloads or during peak seasons. Unlike custom jobs, where the training service releases the resource after job completion, Ray clusters remain available until deleted. For more information, see Ray on Vertex AI overview.