Default Workspace Configuration
A workspace provides compute and storage that can be tailored to meet researchers' requirements. Workspaces can scale up or down by request, allowing for multiple configurations and support for use cases from structured data analysis using in-built tooling, to large-scale model training using Azure Machine Learning services.
Storage
Default | |
|---|---|
Shared File System | 5TB |
Each workspace has an allocated default 5TB shared file system.
Virtual Machines
CPU | RAM | Storage | |
|---|---|---|---|
Windows | 4 | 14GB | 30GB |
Linux | 4 | 14GB | 30GB |
Should dedicated compute be required, Virtual Machines (VM) can be provided. The default VM configuration provides 4 CPU and 14GB of RAM and 30GB storage. Furthermore, in a Linux VM, each user benefits from 16GB allocation for home directories, divided among each user.
To ensure compute resources are being utilized diligently, VMs are configured to auto-shutdown overnight based on the hub the VM is deployed in.
Tooling
CPU | RAM | |
|---|---|---|
Kubernetes cluster | 8 | 16GB |
Workspaces provide in-built tooling that provides access to R-Studio and Jupyter Notebook. These tools run on a dedicated Kubernetes cluster. The default node configuration is 8 CPU and 16GB of RAM. This cluster is shared across all workspaces.