> ## Documentation Index > Fetch the complete documentation index at: https://docs.farmgpu.com/llms.txt > Use this file to discover all available pages before exploring further. # Software Stack > TractorOS, control plane, and FarmGPU operational software ## Software Stack & Control Plane FarmGPU's software stack is designed to **operate AI infrastructure at scale with minimal human overhead**, while preserving performance, transparency, and control. Rather than relying on proprietary cloud control planes, FarmGPU builds on **open-source, Linux-native primitives**, extended with purpose-built systems for GPU operations. Together, these components form a **unified control plane** for provisioning, operating, observing, and optimizing AI clusters. *** ## TractorOS — The NeoCloud Operating System **TractorOS** is FarmGPU's minimal, immutable, container-native operating system optimized specifically for AI compute. TractorOS Architecture ### What TractorOS Does * Provides a hardened, reproducible OS image for GPU and storage nodes * Ships with **built-in GPU, networking, and storage drivers** * Enables **zero-touch provisioning and fleet-wide upgrades** * Eliminates configuration drift across clusters ### Key Characteristics * Linux-based (RHEL-derived) * Immutable image-based updates * Container-first runtime model * Designed for bare metal AI infrastructure, not VMs TractorOS allows FarmGPU to deploy and scale GPU fleets rapidly while maintaining **predictable behavior across thousands of nodes**. *** ## Homestead — Bare-Metal Provisioning & Lifecycle Management **Homestead** is the entry point for every FarmGPU server. ### What Homestead Does * Bare-metal provisioning via Redfish and Ansible * Hardware discovery and inventory * Initial OS deployment and configuration * Support for KVM VMs and LXC containers where needed Homestead ensures that servers move from **rack to production** with minimal manual intervention, forming the foundation for repeatable cluster deployments. *** ## Shepherd — System Health, Reliability & Diagnostics **Shepherd** is FarmGPU's system health evaluation platform, designed to make AI infrastructure **observable, debuggable, and predictable**. ### What Shepherd Monitors * GPU health and performance (via NVIDIA DCGM) * Network health and packet loss * Storage latency and throughput * Host-level metrics and anomalies ### Advanced Capabilities * Predictive failure detection * Agentic diagnostics and root-cause analysis * Automated incident summaries and reports * Integration with observability tools (Grafana, Prometheus, Loki, Alloy) Shepherd enables FarmGPU to move from **reactive monitoring** to **proactive reliability**, reducing downtime and improving SLA adherence. *** ## Silo — Storage Infrastructure & Benchmarking **Silo** is FarmGPU's storage evaluation and optimization platform. ### What Silo Does * Deploys and benchmarks block, file, and object storage systems * Evaluates storage performance under AI workloads * Performs hardware discovery and tuning * Validates storage configurations before production rollout Silo is used internally to benchmark platforms such as MinIO, VAST Data, Weka, and Ceph, ensuring that storage performance is **measured, repeatable, and workload-aware**. *** ## Haystack — AI Workload Profiling & Optimization **Haystack** provides workload-level visibility into how AI jobs consume infrastructure. ### What Haystack Measures * GPU utilization by workload * Storage I/O patterns * Network usage and contention * Differences between training, fine-tuning, and inference jobs This enables: * Per-workload optimization * Capacity planning based on real usage * Improved scheduling and cost efficiency * Better matching of workloads to hardware profiles Haystack helps FarmGPU optimize **goodput**, not just raw utilization. *** ## Automation, Observability & Drivers (Underlying Stack) Across all systems, FarmGPU standardizes on proven, open tooling: ### Automation * **Ansible** for configuration and orchestration ### Observability * **Grafana** * **Prometheus** * **Loki** * **Alloy** * **Node Exporter** * **NVIDIA DCGM** * **cAdvisor** ### Drivers & Acceleration * NVIDIA GPU drivers * SPDK for NVMe * NVIDIA DOCA / OFED for networking and DPU acceleration This approach keeps the stack **transparent, auditable, and extensible**, while avoiding vendor lock-in. *** ## Why This Software Stack Matters FarmGPU's software stack is not a SaaS product suite—it is **operational leverage**. It enables: * Faster cluster bring-up * Higher GPU utilization * Lower operational overhead * Predictable performance at scale * Rapid adoption of new hardware generations By building a Linux-native, hardware-aware control plane, FarmGPU achieves **hyperscaler-level operational maturity without hyperscaler complexity or cost**.