Self-hosted deployments | LiveKit Documentation
Guide to running LiveKit agents on your own infrastructure.
Explains how to turn an AI model into a REST API straight from a Docker container. Guides you through setting up the model server within a container and exposing endpoints, making it accessible for in...
HOME / Deploying AIAPI on the Server - BlazingFast Photonics
Guide to running LiveKit agents on your own infrastructure.
We''re going to walk through deploying AI applications using FastAPI and Docker,two tools that, when combined, make your AI services portable, production-ready, and a joy to work with.
Explains how to turn an AI model into a REST API straight from a Docker container. Guides you through setting up the model server within a
Deploying with Docker is the easiest and fastest method of getting started. No prerequisites are required other than a modern version of Docker.
This guide walks you through the 15 best n8n practices for deploying production-ready AI Agents. Choose the best infrastructure, scale queue mode,
Deploy a AI APIs MCP server on IOX Cloud and connect it to Claude, ChatGPT, Cursor, or any AI client. Your AI assistant gets direct access to AI APIs through these tools: Describe what you need, AI
In this post I will describe how I use Docker Compose to set up an LLM experimentation environment where I can connect tools and chat to cloud-based
Learn about Azure API Management''s policies and features to manage, secure, scale, monitor, and govern LLM deployments, AI APIs, and MCP servers accessed by your AI apps and
This Hands-on lab focuses on integrating AI Foundry into Snowflake Cortex through the Snowflake managed MCP Server. Using the two services together allows
Learn to set up and use your local AI server with this comprehensive guide. Enhance your projects today—read the article for step-by-step instructions!
Learn how to build applications with AI capabilities using Azure OpenAI, local small language models (SLMs), and other AI features in different programming languages and frameworks.
Note The AI gateway, including MCP server capabilities, extends API Management''s existing API gateway; it''s not a separate offering. Related
A complete guide to OpenAI Codex CLI, the open-source terminal-based AI coding agent. Learn how to install, configure authentication, choose approval modes, and extend with MCP servers
Every development team has unique requirements that can make implementing an efficient deployment pipeline difficult on any cloud service. This
Deploying and managing self-hosted AI with DeployHQ Once your AI stack is running, you need a way to manage configuration changes, model updates, and Nginx rules without SSH-ing
I am trying to deploy an ASP application. I have deployed the site to IIS, but when visiting it with the browser, it shows me this: Server Error 500 - Internal
DeepSeek and Qwen now hold 15% of the global AI market, up from 1% a year ago. Here''s what V4 and 3.5 actually deliver, what they cost, and when
1. A generalized engineering framework for production-grade agentic AI workflows. We introduce a structured methodology for designing, developing, and deploying agentic systems using multi-agent
Learn to deploy Google ADK agents to Cloud Run with our step-by-step guide. This tutorial covers project setup, local testing, and secure API key
Once you have a working MCP server and component bundle, host them behind a stable HTTPS endpoint. The key requirements are low-latency streaming
By following the steps outlined, you can deploy AI models efficiently using FastAPI, Docker, and Azure. This stack ensures flexibility, scalability, and
Learn how Claude Code can integrate with various third-party services and infrastructure to meet enterprise deployment requirements.
Deploy multi-agent AI systems on Kubernetes with zero trust. Learn how to use Kagenti with SPIFFE, Istio Ambient mesh, and A2A-native frameworks like BeeAI to secure AI agents in
Arm Holdings claims that it can substantially reduce the cost of deploying server CPUs in AI data centers.