Guides

Console Reference

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The NVIDIA Brev console at brev.nvidia.com provides a web interface for managing your GPU resources, deployments, and team.

The console sidebar organizes features into these main sections:

SectionPurpose
GPUsCreate and manage GPU instances.
DeploymentsManage serverless NIM deployments.
BlueprintsPreconfigured environments for common workflows.
LaunchablesQuick-start templates for specific use cases.
TeamManage organization members and permissions.
BillingView usage, invoices, and payment methods.

GPU Instances

The GPUs section displays all instances in your organization.

Creating an Instance

1

Click Create Instance

From the GPUs page, click the Create Instance button.

2

Select GPU Type

Choose from available GPU types (L40S, A100, H100, etc.) based on your workload needs.

3

Configure Instance

  • Enter an instance name
  • Select a base image or Launchable
  • Choose disk size
  • Optionally configure environment variables
4

Launch

Click Create to provision your instance. Setup typically takes 1-2 minutes.

Instance Details

Click any instance to view its details page with:

  • Status: Current state (Running, Stopped, Starting, etc.)
  • GPU: Type and count of attached GPUs
  • Uptime: How long the instance has been running
  • Disk Usage: Current storage utilization

Access Tab

The Access tab provides connection information:

SSH Connection

  • Instance hostname for direct SSH access
  • Command to copy: ssh <instance-name>

Using Tunnels Expose ports with publicly accessible URLs:

  1. Enter a port number (e.g., 8888 for Jupyter)
  2. Click Add
  3. Copy the generated URL

Tunnels route through Cloudflare and require browser authentication on first access. For direct API access without browser redirects, use brev port-forward from the CLI instead.

Port Exposure View and manage which ports are exposed on your instance.

Deployments

The Deployments section manages serverless NVIDIA Inference Microservices (NIMs).

Deployment List

View all deployments with:

  • Deployment name and model
  • Status (Active, Deploying, Stopped)
  • Worker count (current / max)
  • Endpoint URL

Deployment Details

Click a deployment to access:

  • Metrics: Invocation counts, latency percentiles, error rates
  • Logs: Real-time deployment logs
  • Settings: Min/max workers, GPU configuration

Refer to Serverless Deployments for detailed deployment management.

Blueprints & Launchables

Blueprints

Blueprints are preconfigured environment templates that include:

  • Base container image
  • Preinstalled packages and dependencies
  • Environment configuration

Common blueprints include PyTorch, TensorFlow, and RAPIDS environments.

Launchables

Launchables are quick-start templates for specific use cases:

  • JupyterLab: Ready-to-use notebook environment
  • VS Code Server: Browser-based VS Code
  • LLM Fine-tuning: Preconfigured for model training

Select a Launchable when creating an instance to start with everything preconfigured.

Team Management

Manage your organization’s members and permissions.

Inviting Members

2

Click Invite

Click the Invite Member button.

3

Enter Email

Enter the email address of the person to invite.

4

Set Role

Choose their role:

  • Member: Can create and manage their own instances
  • Admin: Full organization management access

Managing Members

From the Team page you can:

  • View all organization members
  • Change member roles
  • Remove members from the organization

Billing & Usage

Track costs and manage payment.

Usage Dashboard

View:

  • Current billing period spend
  • Breakdown by instance and GPU type
  • Historical usage trends

Payment Methods

Add and manage credit cards for billing. Usage is charged at the end of each billing cycle.

Invoices

Access and download past invoices for accounting and reimbursement.

What’s Next

Quickstart

Create your first GPU instance in minutes.

CLI Reference

Manage resources from the command line.