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Chamber

Compute Optimization

GPU infrastructure optimization platform that shows ML teams where GPUs are idle, auto-schedules jobs, and detects hardware failures before they impact training.

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At a Glance

Pricing

Free tier available

GPU utilization monitoring with no time limits

Enterprise: Custom/contact

Engagement

Available On

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API

Resources

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Topics

Compute OptimizationAI InfrastructureMonitoring Tools

About Chamber

Chamber is a GPU infrastructure optimization platform designed for AI/ML teams to maximize GPU utilization and reduce wasted compute resources. The platform provides real-time visibility into GPU usage across clusters, intelligent job scheduling to fill idle capacity, and proactive hardware fault detection to prevent training run failures. Built by engineers from Amazon, Meta, Microsoft, and other tech companies, Chamber addresses the common problem of 40-60% average GPU utilization in AI/ML workloads.

  • Real-time Visibility provides comprehensive dashboards showing GPU utilization, idle time, queue depth, and cluster efficiency across your entire fleet, enabling teams to identify exactly where resources are being wasted.

  • Intelligent Scheduling automatically discovers idle GPUs across teams and schedules work to maximize utilization, with high-priority jobs able to preempt lower-priority ones and resume automatically when resources free up.

  • Fault Detection continuously monitors hardware health and automatically isolates failing GPUs before they corrupt training runs, preventing silent failures that can waste weeks of compute time.

  • Preemptive Queue allows high-priority jobs to pause lower-priority workloads, which automatically resume upon completion, ensuring critical work gets resources immediately.

  • Team Fair-Share enables setting budgets and quotas across teams, with unused allocation automatically lending to others, eliminating GPU hoarding while ensuring fair access.

  • Fleet Metrics monitors GPU usage, costs, and performance across your entire infrastructure with AI-powered metric insights and automated usage reports.

To get started, deploy Chamber to your Kubernetes cluster with a single helm command. The platform supports any Kubernetes-based GPU cluster including on-prem, cloud (AWS, GCP, Azure), and hybrid setups with NVIDIA GPUs. Chamber runs within your infrastructure, collecting only anonymized telemetry while keeping your models, datasets, and code secure in your environment. The free tier provides immediate GPU utilization visibility with no time limits or credit card required.

Chamber

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Pricing

FREE

Free Plan Available

GPU utilization monitoring with no time limits

  • GPU utilization monitoring
  • Automatic resource discovery
  • Cluster level utilization dashboard
  • Real time view of unused GPUs & workload queues
  • AI Metric Insights

Enterprise

Full GPU orchestration platform with advanced features

Custom
contact sales
  • Everything in Free
  • Team management
  • Automated resource allocations
  • Intelligent workload scheduling
  • Slack integration
  • PagerDuty integration
  • Custom webhooks
  • Priority support
  • Custom SLA
View official pricing

Capabilities

Key Features

  • Real-time GPU utilization monitoring
  • Automatic resource discovery
  • Cluster-level utilization dashboard
  • Intelligent workload scheduling
  • Preemptive queue system
  • Hardware fault detection and isolation
  • Team fair-share resource allocation
  • Fleet metrics and performance monitoring
  • AI metric insights
  • Email usage reports
  • Team management
  • Automated resource allocations
  • Custom webhooks

Integrations

Kubernetes
AWS
GCP
Azure
Slack
PagerDuty
NVIDIA GPUs
API Available
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Demo Video

Chamber Demo Video
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Reviews & Ratings

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Developer

Chamber Team

Chamber builds GPU infrastructure optimization software for AI/ML teams. Founded by engineers from Amazon, Meta, Microsoft, Flexport, and Optimizely who experienced firsthand the challenges of GPU utilization and capacity management. Backed by Y Combinator (W26 batch), the company operates from San Francisco and helps teams run more experiments on existing GPU infrastructure through intelligent scheduling and real-time visibility.

Read more about Chamber Team
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