Fly.io vs Netlify
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Fly.io and Netlify represent different compute models. Fly.io provides persistent Firecracker microVMs with private networking, persistent volumes, and infrastructure control. Netlify provides stateless serverless functions with a 15-minute background ceiling and no persistent compute. Fly.io wins on three agentic dimensions. Netlify wins on frontend deployment simplicity.
Where Fly.io wins
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Persistent microVMs with no execution timeout. Fly Machines run any Docker image as a full microVM indefinitely with no time limit and no CPU cap. Agent orchestrators, MCP tool servers, and background workers run as persistent processes, maintaining in-memory state, WebSocket connections, and long-running planning loops. Netlify's longest execution path is background functions at 15 minutes. Synchronous functions terminate at 60 seconds. There's no persistent process, no Docker support, no WebSocket support, and no always-on compute. An agent planning chain that runs 20 minutes or an MCP server that must stay alive cannot run on Netlify.
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Private 6PN networking for multi-service agent architectures. Fly.io provides private IPv6 networking across all Machines with
.internalDNS, TCP/UDP support, and WireGuard tunnels. An agent's orchestrator, tool servers, databases, and caches communicate over this private network with no public exposure. Netlify has no inter-function networking. Each function invocation is isolated—there's no service discovery, no private network, and no function-to-function communication. A multi-service agent on Netlify must route all inter-service communication through external services or the public internet. -
Persistent volumes, managed Postgres, and co-located state. Fly.io persistent volumes provide NVMe storage for vector indexes, model weights, or agent artifacts, mounted directly to Machines. Managed Postgres runs on the same private network. Agent state—conversation memory, tool results, session data—lives next to compute. Netlify offers Blob storage for file uploads but no managed database, no persistent volumes, and no co-located stateful storage. Every state access from a Netlify function requires a network request to an external database provider.
Where Netlify wins
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Simpler deployment for frontend-plus-function architectures. Netlify's Git-push deploys, automatic preview URLs, and integrated build system provide a streamlined path for deploying a frontend with thin API functions. For an agent that's a React frontend calling a single serverless function that proxies LLM API calls, Netlify's model is simpler than configuring Fly.io Machines, volumes, and networking. This applies only when the agent has no persistent state, no multi-service architecture, and every operation completes within 60 seconds or 15 minutes for background tasks.
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Background functions with automatic retries. Netlify Background Functions provide automatic retries on failure (1 minute, then 2 minutes) with no configuration. For simple async agent tasks—webhook processing, batch API calls—this retry behavior is built-in. Fly.io provides persistent processes that don't need retries the same way, but developers implement retry logic for individual operations.
The agentic difference
The gap between Fly.io and Netlify is architectural. Fly.io provides persistent processes, private networking, and co-located state—the infrastructure agents need. Netlify provides stateless functions with a 15-minute ceiling, no inter-service communication, and no persistent compute. Agent workloads that need processes running longer than 15 minutes, MCP tool servers, WebSocket connections, multi-service coordination, or co-located databases cannot run on Netlify without external infrastructure replacing every missing piece.
When to pick which
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Pick Fly.io when the agent needs persistent processes, private networking between services, persistent volumes, managed databases, or any compute beyond stateless request-response—which covers most agent architectures.
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Pick Netlify when the agent is a stateless frontend-plus-function deployment where every operation completes within 60 seconds or 15 minutes async, there's no need for persistent state or inter-service communication, and deployment simplicity is the priority.