Master Fleek with our step-by-step tutorial, detailed feature walkthrough, and expert tips.
Create a Fleek account at fleek.xyz and review the current product documentation for the deployment path you plan to use Connect a repository or use the Fleek CLI to configure hosting, functions, or agent deployment workflows Configure build settings, environment variables, API keys, model endpoints, and other agent configuration requirements Deploy your agent, website, or Fleek Function and test the generated endpoint before moving traffic to production Configure custom domains and SSL certificates for production deployment of your AI agent endpoints Review current pricing, function status, resource limits, and enterprise requirements before scaling production workloads
💡 Quick Start: Follow these 1 steps in order to get up and running with Fleek quickly.
Explore the key features that make Fleek powerful for deployment & hosting workflows.
Both Fleek and Vercel can support web deployment workflows, but they differ in positioning. Fleek emphasizes edge-oriented hosting, Fleek Network infrastructure, IPFS-related workflows, AI agent hosting, and SGX/TEE-oriented features. Vercel is more mature for Next.js and frontend application deployment with a larger ecosystem and clearer public production limits. For pure web app deployment, Vercel is usually easier to evaluate; for AI agents needing decentralized infrastructure, verifiable infrastructure, or Fleek-specific agent workflows, Fleek may be worth testing.
Fleek documentation currently describes Fleek Functions as JavaScript and TypeScript-based server-side functions, while AI agent hosting materials focus on deploying and managing agents such as Eliza-style agents. Python-based agent logic may require a separate compute service or a supported deployment pattern documented by Fleek at the time of implementation. Teams using LangChain, AutoGen, or CrewAI should verify current runtime support in Fleek's latest docs before choosing Fleek as the primary execution environment.
Fleek's documentation includes Fleek Network infrastructure, IPFS-related deployment and storage workflows, and SGX/TEE-oriented edge features. These are useful for Web3-integrated agents, decentralized applications, and projects where verifiability, censorship resistance, or content-addressed infrastructure matter. Most traditional AI agent use cases do not require these features, so teams should weigh the added architectural complexity against the product need.
Current public documentation does not provide enough consistently visible detail to confirm broad WebSocket support, plan-specific streaming behavior, or persistent connection limits. For streaming AI responses, teams should test the specific deployment path they plan to use and confirm current Fleek Functions or hosting limits in Fleek's latest documentation or support channels.
Fleek's public documentation describes Fleek Functions as server-side JavaScript and TypeScript functions running on Fleek Network infrastructure, with the functions feature marked as alpha in the CLI documentation. Exact execution time, memory, request size, and concurrency limits should be verified in the latest Fleek documentation or with Fleek support. Long-running inference, model training, and complex multi-step agent workflows may need a dedicated compute provider alongside Fleek-hosted endpoints.
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Tutorial updated March 2026