In-depth technical analysis, architecture blueprints, and deployment guides for private AI infrastructure.
Architecture guide for configuring an all-in-one sovereign AI server running virtualized OPNsense, Docker containers, databases, and GPU passthrough.
Read Deep Dive →Architecture guide for configuring an all-in-one sovereign AI server running virtualized OPNsense, Docker containers, databases, and GPU passthrough.
Read Article →Production guide for deploying autonomous AI agents on a Linux VPS. Configure Ollama, LiteLLM proxy, and self-hosted n8n with secure Docker networking.
Read Article →Step-by-step production guide for deploying vLLM on a GPU VPS using Docker Compose, NVIDIA Container Toolkit, API authentication, and reverse proxy security.
Read Article →Comparison of free and low-cost GPU hosting for LLM inference and fine-tuning. Evaluates free tiers, spot pricing, VRAM, and persistence.
Read Article →Detailed comparison of RunPod vs AWS EC2 GPU instances for AI model inference and training. Compare pricing, egress fees, provisioning, and VRAM efficiency.
Read Article →Comparison of RunPod and Vast.ai for private AI workloads. Evaluate pricing, security, node reliability, network storage, and Docker workflow efficiency.
Read Article →Build a production-ready, sovereign MLOps stack using Docker Compose. Integrates MLflow for experiment tracking, MinIO for S3 artifacts, and Ollama for LLMs.
Read Article →Comparing Performance VPS (shared vCPU) and Virtual Dedicated Servers (VDS) for self-hosted analytics, ClickHouse, and steady AI workloads.
Read Article →Resolving Docker container outbound HTTPS timeouts when the host works. Fixes for MTU size mismatch on docker0 bridge, overlay networks, and DNS resolution.
Read Article →Architecture blueprint for hardening private Qdrant vector database instances with VLAN isolation and mTLS.
Read Article →In-depth benchmark of Ollama vs vLLM. Compare token throughput, Time-To-First-Token (TTFT), PagedAttention, and multi-user concurrency on RTX 4090 and A100.
Read Article →Step-by-step technical guide to exposing AMD GPU devices (/dev/kfd and /dev/dri) to Docker containers using ROCm.
Read Article →Hardening containerized GPU access, preventing VRAM leaks, restricting privileged access, and securing host CUDA drivers.
Read Article →Multi-stage builds, runtime vs devel image selection, wheel caching, and slimming PyTorch CUDA container images.
Read Article →Practical guide for fine-grained GPU resource reservations using deploy.resources in Docker Compose v2.
Read Article →Diagnosing and resolving SIGBUS crashes and VRAM OOM errors caused by POSIX shared memory (/dev/shm) limits in Docker.
Read Article →Monitoring GPU VRAM, utilization, wattage, and ECC errors per Docker container using DCGM Exporter and Prometheus.
Read Article →Step-by-step guide to resolving profiling permissions, capabilities, and tracing CUDA kernels in Docker using Nsight Systems.
Read Article →Technical guide for migrating from legacy nvidia-docker2 to OCI Container Device Interface (CDI) on Docker 25+.
Read Article →Hardware partitioning with NVIDIA MIG and assigning isolated GPU instances to Docker containers on A100/H100.
Read Article →Maximizing GPU utilization and throughput for lightweight inference containers using NVIDIA Multi-Process Service (MPS).
Read Article →An engineering comparison of Make.com and n8n for automating private AI workflows, RAG ingestion, and infrastructure alerting.
Read Article →An engineering comparison of RunPod and Paperspace for renting GPUs. Evaluate persistent inference workloads, storage, and networking limits.
Read Article →An infrastructure engineering comparison of Vultr and DigitalOcean for self-hosting private AI pipelines, RAG, and managed Kubernetes.
Read Article →Technical comparison of VPS and GPU cloud providers for self-hosted AI agents, LLM inference, and Ollama. Compare CPU vs GPU nodes, VRAM, RAM, and costs.
Read Article →The fastest way to run local LLMs. Step-by-step guide to deploying Ollama and Open WebUI with Docker Compose and NVIDIA Container Toolkit.
Read Article →Resolving Cloudflare Tunnel 502 Bad Gateway, host errors, and connection refused issues with Open WebUI and Ollama in Docker. Full configuration fix.
Read Article →Resolving 'could not select device driver with capabilities: gpu'. Root cause analysis and fix for the NVIDIA Container Toolkit on Docker.
Read Article →Resolving Ollama falling back to CPU mode in Docker. Learn how to configure compose-spec GPU reservations, verify NVIDIA drivers, and check if GPU is used.
Read Article →Resolving CUDA memory fragmentation and Out Of Memory (OOM) errors during LLM quantization processes like AWQ or GPTQ.
Read Article →Fix Open WebUI 'Connection Refused', 'Ollama Not Found', and OpenAI network errors in Docker. Step-by-step fix for network bridges and OLLAMA_BASE_URL.
Read Article →Resolving connectivity issues in hardened AI networks. How to fix 'Default Deny' rules blocking internal Docker API traffic.
Read Article →Resolving VRAM allocation crashes in vLLM. Learn how to calculate KV cache requirements, tune gpu_memory_utilization, and configure AWQ quantization.
Read Article →Hardware requirements for running Llama 3 70B. Comprehensive VRAM calculator for FP16, Q8_0, Q4_K_M, INT4 AWQ, single-GPU vs multi-GPU setups.
Read Article →Detailed comparison of vLLM and NVIDIA Triton Inference Server. Compare token throughput, PagedAttention, TensorRT-LLM, latency, and operational complexity.
Read Article →Harden an AI inference server with OPNsense VLANs. Prevent data exfiltration and isolate Docker workloads with strict firewall rules.
Read Article →A technical guide to sovereign AI infrastructure. Learn why engineering teams are moving from public APIs to self-hosted LLMs using Docker, vLLM, and OPNsense.
Read Article →When running continuous batching, vLLM drastically outperforms Triton on 4090s.
May 1, 2026A minimum of 48GB VRAM is required for 4-bit quantization with reasonable context windows.
April 28, 2026