Tensor One Clusters
Tensor One clusters are containerized instances intended for application execution. Note: To guarantee compatibility across supported architectures when building container images for Tensor One, use the following build flag:Comprehending Cluster Configuration and Components
You can create a Cluster, which is a containerized server instance, to utilize specific hardware resources. Each Cluster is assigned a unique, dynamically generated identifier (e.g.,2s56cp0pof1rmt).
A typical Cluster includes:
Container Volume
- Holds the operating system and temporary storage
- This storage is volatile and will be lost upon Cluster shutdown or reboot
Disk Volume
- Provides persistent storage, preserved throughout the Cluster’s lifespan
- Storage remains available even after a Cluster restart or shutdown
Ubuntu Linux Container
- Runs any software compatible with Ubuntu Linux
Resource Allocation
- Dedicated vCPU and RAM for container processes
Optional GPUs or CPUs
- Attach specialized resources like CUDA-enabled GPUs for AI/ML workloads
Pre-configured Templates
- Automatically installs common tools and settings on creation
- Enables one-click access to frequently used environments
Proxy Connection for Web Access
- Accessible via proxy URLs
Customizing Your Cluster
When creating a Cluster, you can customize the following options:- GPU Type and Quantity
- System Disk Size
- Start Commands
- Environment Variables
- HTTP/TCP Port Exposure
- Persistent Storage Options