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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.

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What Chamber Does

AI Ops Agent (Beta)

Autonomous agent that monitors, diagnoses, and resolves GPU workload issues 24/7

Real-time Visibility

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

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

Multi-Cluster Support

Manage capacity across multiple Kubernetes clusters from a single control plane
See Chamber AI Ops agent in action

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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

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.
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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Getting Started

Quickstart

Get up and running with Chamber in minutes

Core Concepts

Deep dive into how Chamber works