Infra Orchestrator
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Orchestrates multi-cloud resource deployments, autoscaling, and telemetry reporting through an extensible platform server.
About
This tool provides a robust, extensible reference implementation for a Multi-Cloud Platform (MCP) server. It simplifies the deployment and management of computing resources, particularly GPUs for AI/ML workloads, across various cloud providers like RunPod and Vast.ai. Featuring a multi-agent architecture, it intelligently selects and provisions resources, automates scaling, and offers comprehensive observability through integrations with AI Envoy and Phoenix. The platform uses Redis for task queuing and ClickHouse for collecting and analyzing telemetry data, enabling efficient resource orchestration and monitoring.
Key Features
- Pluggable LLM client for intelligent resource planning and decision-making.
- Multi-agent architecture supporting evaluation, SkyPilot, and on-prem deployments.
- Comprehensive telemetry and observability with AI Envoy and Phoenix integration.
- 0 GitHub stars
- SkyPilot integration for dynamic autoscaling and cloud resource provisioning.
- GPU Rules Management API for intelligent resource selection based on workload types.
Use Cases
- Centralized management and monitoring of resource lifecycles across diverse cloud providers.
- Automating multi-cloud GPU resource deployment for AI/ML inference and training workloads.
- Optimizing resource allocation and cost by intelligently selecting GPUs based on workload requirements and custom rules.
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