This course helps developers kick-start their work on Anyscale.
Learn what Anyscale Workspaces are and how they simplify building Ray applications by managing compute, dependencies, storage, and IDE integration. You’ll also launch and configure a workspace by selecting cloud resources, sizing worker nodes, and enabling autoscaling.
Learn how to develop and run Ray applications in an Anyscale Workspace using the hosted VS Code editor and built-in JupyterLab. You’ll also see how to integrate a local IDE workflow—coding locally and executing remotely on an Anyscale cluster.
Learn how to build and register container images in Anyscale to standardize dependencies and runtime settings, then create compute configs that define instance types and autoscaling behavior for Ray clusters. You’ll apply these settings by updating an Anyscale Workspace and validating the environment with a simple runtime test.
Learn how to choose and use Anyscale’s storage options for AI workloads—cloud object storage, shared file storage, local cluster storage, and workspace-local persistence. You’ll practice accessing each option via environment variables and mount paths and perform basic tasks like uploading, listing, and cleaning up files.
Learn how to monitor and troubleshoot Ray applications on Anyscale by using the Log Viewer, Metrics tab, and Ray Dashboard. You’ll run a sample π-estimation workload and practice locating, querying, and downloading logs and interpreting cluster/workload metrics.
Learn how to productionize batch and training workloads with Anyscale Jobs by creating and submitting your first Ray job from a workspace using the Anyscale CLI. You’ll also automate job submission and scheduling with the Anyscale SDK/API while Anyscale manages cluster lifecycle and execution.
Learn how Anyscale Services uses Ray Serve to deploy scalable, reliable APIs on dedicated Ray clusters. You’ll create a workspace, update a simple Serve app and `service.yaml`, deploy with the Anyscale CLI, monitor the rollout, and clean up resources.
Learn how to collaborate in Anyscale by organizing work into shareable projects with granular access controls. You’ll also practice cloning jobs, services, and workspaces to quickly duplicate identical environments for your team.
Learn how to set up and structure an Anyscale organization for a team, including how organizations, clouds, projects, and workloads relate. You’ll also understand key terminology and best practices for managing multi-cloud environments, user roles/RBAC, and billing-ready governance.
