Chamber is an AIOps platform for GPU infrastructure that deploys AI agents to autonomously monitor, root-cause, and remediate GPU workload issues across clouds and clusters. It provides a SaaS control plane with a lightweight agent installed via Helm into customers' Kubernetes or Slurm clusters, offering fleet-wide dashboards, cost forecasting, and cross-cloud orchestration. Its conversational AI agent, Chambie, answers infrastructure questions and takes remediation actions from Slack, CLI, or the web console.
What it's for
Features 15
- Advanced orchestration with fair-share scheduling and budget-based governance
- AI-powered root cause analysis for GPU failures
- Automatic fault detection and isolation of failing GPUs
- Automatic team dashboards generated from Kubernetes labels
- Autonomous remediation of infrastructure issues
- Chambie AI agent for natural-language infrastructure queries via Slack, CLI, or UI
- Cost forecasting based on historical usage patterns
- Cross-cloud GPU fleet monitoring and visibility
- Fleet-wide metrics, cost analytics, and utilization tracking
- Intelligent workload orchestration and scheduling
- One Helm command deployment
- Programmable API, CLI, and Python SDK for automation
- Weights & Biases and experiment tracker integration
- Workload Explorer with full history and advanced filtering
- Zero-config auto-discovery of GPUs, workloads, and teams
At a glance
Integrations
Complianceself-reported
Resources
Pricing
Pricing is tailored per customer (from startups to enterprises). A free GPU monitoring tier is available with no credit card required to start. Enterprise pricing applies for full platform access.
Described in llms.txt as 'Free GPU monitoring tier available'; no credit card required to start.
Free GPU monitoring tier
Quote-based; pricing page says 'Talk to us and we'll put together the right plan for your setup.' Enterprise pricing for full platform access per llms.txt.
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