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Chamber is a GPU capacity control plane that helps organizations maximize utilization of their AI infrastructure. It provides visibility, scheduling, and capacity management across GPU clusters. Chamber Dashboard

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What Chamber Does

Capacity Management

Allocate GPU resources through hierarchical teams with guaranteed reservations

Intelligent Scheduling

Two-phase scheduling with reserved and elastic workload classes for optimal resource utilization

Real-time Visibility

Dashboard with GPU utilization metrics, workload status, and team performance insights

Multi-Cluster Support

Manage capacity across multiple Kubernetes clusters from a single control plane

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How It Works

Chamber operates as a SaaS control plane with a lightweight agent deployed in your Kubernetes clusters:
1

Deploy the Agent

Install the Chamber agent in your GPU clusters via Helm chart. The agent syncs workload state with the control plane.
2

Model Your Organization

Create teams in a hierarchy that reflects your organization structure.
3

Allocate Capacity

Assign GPU reservations from your capacity pools to teams. Teams get guaranteed access to their reserved capacity.
4

Submit Workloads

Workloads submitted to your cluster are scheduled by Chamber. Reserved workloads get guaranteed resources; elastic workloads use idle capacity.

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Key Concepts

ConceptDescription
TeamHierarchical unit representing a team or project. Teams can have projects. (aka child teams )
Capacity PoolA GPU resource pool, typically a Kubernetes cluster with GPU nodes.
ReservationLinks a team to a capacity pool with guaranteed GPU allocation.
Reserved WorkloadWorkload that runs on reserved capacity. Cannot be preempted.
Elastic WorkloadWorkload that uses idle capacity. Can be preempted when reserved workloads need resources.

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Getting Started

Quickstart

Get up and running with Chamber in minutes

Core Concepts

Deep dive into how Chamber works