Self-Hosting

Oh My Opencode turns OpenCode into a multi-agent coding harness: an orchestrator delegates work to specialist agents that run in parallel.

LLM inference looks like “just another API” — until latency spikes, queues back up, and your GPUs sit at 95% memory with no obvious explanation.

OpenClaw is a self-hosted AI assistant designed to run with local LLM runtimes like Ollama or with cloud-based models such as Claude Sonnet.

AWS S3 remains the “default” baseline for object storage: it is fully managed, strongly consistent, and designed for extremely high durability and availability.
Garage and MinIO are self-hosted, S3-compatible alternatives: Garage is designed for lightweight, geo-distributed small-to-medium clusters, while MinIO emphasises broad S3 API feature coverage and high performance in larger deployments.

Garage is an open-source, self-hosted, S3-compatible object storage system designed for small-to-medium deployments, with a strong emphasis on resilience and geo-distribution.

Strategic guide to hosting large language models locally with Ollama, llama.cpp, vLLM, or in the cloud. Compare tools, performance trade-offs, and cost considerations.

Self-hosting LLMs keeps data, models, and inference under your control-a practical path to AI sovereignty for teams, enterprises, nations.

Running large language models locally gives you privacy, offline capability, and zero API costs. This benchmark reveals exactly what one can expect from 14 popular LLMs on Ollama on an RTX 4080.

The Go ecosystem continues to thrive with innovative projects spanning AI tooling, self-hosted applications, and developer infrastructure. This overview analyzes the top trending Go repositories on GitHub this month.

Today we are looking at the top-level consumer GPUs, and RAM modules. Specifically I’m looking at RTX-5080 and RTX-5090 prices, and 32GB (2x16GB) DDR5 6000.

Open WebUI is a powerful, extensible, and feature-rich self-hosted web interface for interacting with large language models.

vLLM is a high-throughput, memory-efficient inference and serving engine for Large Language Models (LLMs) developed by UC Berkeley’s Sky Computing Lab.

The NVIDIA DGX Spark (GB10 Grace Blackwell) is now available in Australia at major PC retailers with local stock. If you’ve been following the global DGX Spark pricing and availability, you’ll be interested to know that Australian pricing ranges from $6,249 to $7,999 AUD depending on storage configuration and retailer.

Cognee is a Python framework for building knowledge graphs from documents using LLMs. But does it work with self-hosted models?

Choosing the Best LLM for Cognee demands balancing graph-building quality, hallucination rates, and hardware constraints. Cognee excels with larger, low-hallucination models (32B+) via Ollama but mid-size options work for lighter setups.

Ollama’s Python library now includes native OLlama web search capabilities. With just a few lines of code, you can augment your local LLMs with real-time information from the web, reducing hallucinations and improving accuracy.