Stand up an organization, get a team productive inside it, and keep compute spend predictable.
You are responsible for the environment other people work in. This path is about structure and stewardship rather than writing distributed code: organizations, workspaces, roles, plans, usage, and the activity trail that tells you who changed what.
Work through these in order.
What Eugo is, what problem it solves, and how to run your first workload on a cluster.
A full tour of the platform: sessions, clusters, workspaces, organizations, and how they fit together.
Set up an organization, invite people, allocate compute, and keep spend predictable.
Creating workspaces and inviting members requires an owner or admin role on the organization. A member cannot follow the second half of this path.
Plan limits govern concurrency as well as capacity. The billing lesson covers which limits bite first as a team grows.
Go from a single-machine notebook to distributed analysis over datasets that no longer fit in memory.
Train and serve models across GPU compute nodes, and understand what the runtime is doing on your behalf.