> ## Documentation Index
> Fetch the complete documentation index at: https://docs.usechamber.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Introduction

> The AI Ops agent for ML teams

Chamber is the AI Ops agent for ML teams. Chamber helps teams monitor, debug, root cause, and resolve GPU workload issues automatically without manual intervention. Gain out of the box insights into your GPU cluster resources, utilization, cost and team/workload level breakdowns automatically. Use AI-powered insights and autonomous agents to resolve failures, and optimize usage to accelerate development, reduce costs, and ship faster.

## What Chamber Does

<CardGroup cols={2}>
  <Card title="AI Ops Agent (Beta)" icon="robot" href="/ai-ops/overview">
    Autonomous agent that monitors, diagnoses, and resolves GPU workload issues 24/7
  </Card>

  <Card title="Real-time Visibility" icon="chart-line">
    Dashboard with GPU utilization metrics, workload status, and team performance insights
  </Card>

  <Card title="Capacity Management" icon="microchip">
    Allocate GPU resources through hierarchical teams with guaranteed reservations
  </Card>

  <Card title="Intelligent Scheduling" icon="clock">
    Two-phase scheduling with reserved and elastic workload classes for optimal resource utilization
  </Card>

  <Card title="Multi-Cluster Support" icon="server">
    Manage capacity across multiple Kubernetes clusters from a single control plane
  </Card>
</CardGroup>

*See Chamber AI Ops agent in action*

<iframe width="100%" style={{ aspectRatio: '16/9', borderRadius: '8px' }} src="https://www.youtube.com/embed/zwdEF7cW21A?rel=0&modestbranding=1" title="Meet Chambie" frameBorder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowFullScreen />

## How It Works

Chamber operates as a SaaS control plane with a lightweight agent deployed in your Kubernetes clusters:

<Steps>
  <Step title="Deploy the Agent">
    Install the Chamber agent in your GPU clusters via Helm chart. The agent syncs workload state with the control plane.
  </Step>

  <Step title="View resources, cost, and utilization metrics — automatically">
    Chamber automatically discovers cluster resources and running workloads, collects infrastructure and application metrics, and surfaces AI-powered insights on the dashboard — with no manual configuration.
  </Step>

  <Step title="Allocate Capacity">
    Assign GPU reservations from your capacity pools to teams. Teams get guaranteed access to their reserved capacity.
  </Step>

  <Step title="Submit Workloads">
    Workloads submitted to your cluster are scheduled by Chamber. Reserved workloads get guaranteed resources; elastic workloads use idle capacity.
  </Step>
</Steps>

## Getting Started

<CardGroup cols={2}>
  <Card title="Quickstart" icon="rocket" href="/quickstart">
    Get up and running with Chamber in minutes
  </Card>

  <Card title="Core Concepts" icon="book" href="/concepts/overview">
    Deep dive into how Chamber works
  </Card>
</CardGroup>