Sahara Documentation
User Guide: AI Developer Platform
User Guide: AI Developer Platform
  • Dataset Registry & Tokenization
  • Troubleshooting
  • API Documentation
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On this page
  • Overview
  • Features
  • Instance Details Page
  • Info Tab
  • Metrics Tab
  • Logs Tab
  • Deployed Models Tab
  • Create Instance Workflow
  • Common Use Cases
  • Tips and Best Practices

Compute Hub

Last updated 28 days ago

Overview

The Compute Hub provides a user-friendly interface to manage compute instances for AI workloads. Users can view, create, and manage instances, as well as deploy models with ease.

Features

Instance List:

  • Displays all running, stopped, or terminated instances.

Status indicators:

  • Running: Green.

  • Stopped: Red.

Each instance card shows:

  • Instance Name

  • Compute Provider

  • Model used for Endpoint

  • Machine type

  • Price/Token

Actions:

  • View Details: Click the eye icon to access detailed information.

  • Start/Stop: Toggle an instance's operational state.

  • Delete: Permanently remove an instance.

Create Instance:

  • Click the Create Endpoint button to configure a new instance that provides a general use model endpoint.

Workflow

  • Navigation: Use the search bar or filters (status, provider, model) to locate specific instances quickly.

  • Quick Actions: Start, stop, or delete instances directly from the instance list.

Instance Details Page

When an instance is selected, the user is directed to a detailed page with the following tabs:

Info Tab

Endpoint Information:

  • Instance Name

  • Compute Provider

  • Model used for Endpoint

  • Machine type

  • Price/Token

Actions:

  • Edit Instance: Modify instance parameters.

  • Stop Instance: Shut down the instance.

  • Delete Instance: Remove the instance permanently.

Metrics Tab

Displays real-time metrics:

  • CPU Usage: Current usage in percentage.

  • Memory Usage: Real-time memory utilization.

  • GPU Usage: GPU processing load percentage.

Logs Tab

Activity Logs:

  • Timestamped logs of instance activity (e.g., initialization, model loading, errors).

  • Enables debugging and instance health monitoring.

Deployed Models Tab

Model Overview:

  • Lists all models deployed on the instance.

Details include:

  • Model name.

  • Deployment date.

  • Model status (e.g., running or stopped).

Actions:

  • View model details or stop/start specific models.

Create Instance Workflow

Steps

  1. Initiate: click the New Endpoint button on the Compute Hub home page.

  2. Configuration

Fill out the form with the following details:

  • Select Provider: Select Provider from list (Lepton, Predibase, Sagemaker, Bedrock, OpenAI)

  • Select Model: Opens a popup and allows users to select from available models on platform. Search and press “Select” when you have chosen a model.

  • Name: Assign a unique name to the instance.

  1. Review and Create:

  • Review the configuration.

  • Click Create Instance to launch the instance.

Common Use Cases

1. Viewing Instance Metrics

  • Navigate to the Compute Hub home page.

  • Select an instance and click the Metrics Tab to monitor performance.

2. Deploying a Model

  • From the Deployed Models Tab, click Deploy Model.

  • Follow the prompts to configure the deployment.

3. Deleting an Instance

  • Locate the instance in the Compute Hub.

  • Click the trash icon to delete it.

  • Confirm the deletion in the pop-up dialog.

Tips and Best Practices

  • Regularly monitor metrics to optimize instance usage.

  • Use the Logs Tab for quick troubleshooting.

  • Organize instances with meaningful names for easier navigation.

  • Always confirm configurations during instance creation to avoid unnecessary costs.