Four engineers built an open-source, self-hosted dashboard to manage Claude Code sessions across eight machines, saving 30 minutes daily. It provides a centralized view, session resuming, and a searchable archive of all Claude client interaction history.
Murali, a veteran in Linux and infrastructure, built AIllowpages, a self-hosted "Yellow Pages for AI tools." This platform features over 2500 curated AI tools across 32 categories, powered by a proprietary relevance engine and Groq AI, emphasizing zero ads and free access.
This guide details how to self-host Llama 2 on a $5/month DigitalOcean Droplet, offering significant cost savings compared to managed AI APIs for users making over 100 daily inference calls. It provides a complete setup for a working inference server, including API endpoints and monitoring.
This content details the construction of a self-hosted private cloud and AI assistants on a single server, focusing on long-term operational sustainability, security, and reliability. It aims to overcome the lack of structure that often leads to the failure of AI systems, explaining how to go beyond initial deployment.
This guide details how to deploy a production-grade Llama 2 inference server on DigitalOcean for just $5/month, offering a cost-effective alternative to AI APIs. The self-hosting solution is designed to run 24/7 with sub-second latency, ideal for inference at scale without excessive cloud vendor taxes.
This tutorial details how to deploy Llama 2 on DigitalOcean for just $5/month, offering a cost-effective alternative to expensive AI APIs. The article promises full control and unlimited requests, highlighting significant savings compared to per-token costs of existing APIs.
This guide details how to deploy a Llama 2 inference server on a $5/month DigitalOcean droplet to significantly reduce costs compared to AI API calls. It covers model quantization, Docker containerization, and horizontal scaling for production workloads.
This guide details how to self-host Llama 2 on a $5/month DigitalOcean Droplet, offering full control and significant savings compared to proprietary AI APIs. It aims to drastically reduce AI infrastructure costs for builders.
This article clarifies the ideal use cases for the Hermes AI Agent, moving beyond generic definitions to help users decide if it fits their specific workflow needs. It emphasizes Hermes's characteristics like being long-running, tool-using, and self-hosted, best suited for tasks such as remote coding, research, and scheduled reporting.
Mission Control assists teams in operating self-hosted LangSmith on Kubernetes. It provides features like in-cluster configuration, preflight checks, health views, releases, and diagnostics to streamline management.
This article details the best open-source models for the Hermes Agent, focusing on self-hosted setups to eliminate API costs. It highlights Llama 4 Maverick for overall quality, Qwen 3 8B for budget VPS, and Mistral Small as a lightweight option, all optimized for local function calling via Ollama.
The author investigated self-hosting AI agents like OpenClaw on a mini PC to save cloud costs, but concluded it would likely result in significant weekend operational work rather than actual savings. While technically feasible with tools like Node and Docker, maintaining a 24/7 agent box requires ongoing effort.
A user migrated from PostHog Cloud EU to a self-hosted solution on Hetzner to reduce costs from 180 EUR/month to 42 EUR/month, citing a cost crossover near 2M events/month. The migration, initially a "weekend project," took six days due to four key issues: a daily event cap, ClickHouse memory limits, reverse proxy persistence, and an outdated plugin.
This content presents 10 GitHub repositories to help users master self-hosting. It covers key modern infrastructure topics such as containers, reverse proxies, monitoring, backups, networking, and systems operations.
Risu Mail introduces a self-hostable, simplified email API built solely on MongoDB for data storage and processing, aiming to remove the complexity of systems using Redis and queues. This approach focuses on reducing infrastructure overhead for startups and small teams while maintaining scalability.