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Optimize your AI infrastructure, reduce costs, and gain deep visibility with AgentaFlow SRO Community Edition.
Optimize your AI infrastructure, reduce costs, and gain deep visibility with AgentaFlow SRO Community Edition.
AgentaFlow provides a suite of tools designed to help you deploy and manage AI infrastructure more efficiently. Whether you're running training clusters or deploying inference services, AgentaFlow offers intelligent GPU orchestration, model serving optimization, and comprehensive observability.
Key Features
Key Features
1. Intelligent GPU Orchestration & Scheduling
* Smart Scheduling: Multiple strategies including least-utilized, best-fit, priority, and round-robin.
* Kubernetes Integration: Native Kubernetes GPU scheduling with Custom Resource Definitions (CRDs) like GPUWorkload and GPUNode.
* Workload Management: Efficient queuing and distribution across GPU clusters.
* Real-time Monitoring: Track GPU utilization, memory, temperature, and power.
* CLI Management: Command-line tools for managing GPU workloads and monitoring clusters.
2. AI Model Serving Optimization
* Request Batching: Intelligent batching improves throughput.
* Smart Caching: TTL-based caching reduces latency.
* Load Balancing: Multiple routing strategies (least-latency, least-load, round-robin) for optimal distribution.
3. Comprehensive Observability Tools
* Prometheus Integration: Production-ready metrics export (20+ GPU & cost metrics).
* Grafana Dashboards: Pre-built visual analytics for GPU clusters and cost optimization.
* Real-time Alerting: Automatic threshold monitoring and notification system.
* Detailed Cost Tracking: Track GPU hours, tokens, and operational costs.
* OpenTelemetry Distributed Tracing: Full request tracing across components with rich attributes (GPU IDs, workload details, costs) and support for Jaeger, OTLP, and stdout exporters.
* Debug Utilities: Multi-level logging and performance analysis tools.
4. Production-Ready Web Dashboard
* Real-time Monitoring: Live GPU metrics with WebSocket updates.
* Interactive Charts: GPU utilization, temperature, and cost analytics.
* System Overview: Total GPUs, efficiency scoring, and cost tracking.
* Alert Management: Real-time notifications and resolution options.
* Responsive Design: Optimized for various screen sizes.
* API Integration: REST endpoints for custom integrations.
5. Containerized Deployment
* Optimized Docker Images: Small (~20MB), secure (distroless, non-root) images for dashboard, scheduler, and demos.
* Docker Compose Stack: Easy setup for the complete monitoring stack (Dashboard + Prometheus + Grafana).
* Multi-Architecture Builds: Support for AMD64 and ARM64 platforms.
* CI/CD Pipeline: Automated builds, tests, security scans, and publishing via GitHub Actions.
* GitHub Container Registry: Images published to ghcr.io for easy access.
Key Benefits
Key Benefits
Maximize GPU ROI: Significantly reduce GPU idle time (up to 40%) through intelligent scheduling, ensuring your expensive hardware is always productive.
Slash Inference Costs: Improve model serving throughput (3-5x) and reduce latency (up to 50%) using smart batching and caching, lowering per-inference costs.
Gain Full Visibility: Understand exactly how your AI infrastructure is performing and where costs are accumulating with comprehensive, real-time metrics, dashboards, tracing, and alerts.
Seamless Kubernetes Integration: Deploy and manage GPU workloads effortlessly within your existing Kubernetes environment using native CRDs and scheduling plugins.
Easy Deployment: Get started quickly with production-ready, secure, and lightweight Docker containers and Docker Compose setups.
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