Fly.io allows developers to deploy app servers globally, running any code close to users for fast, reliable, and fearlessly scalable applications.
Features
- Fly Machines — Hardware-virtualized containers (KVM-isolated) that launch instantly and run only when needed. They start fast enough to handle HTTP requests and can scale into tens of thousands of instances, making them ideal for both persistent applications and ephemeral workloads.
- Sprites Sandboxes — Hardware-isolated sandboxes designed for safely running AI-generated or untrusted code. Each Sprite is a self-contained environment that spins up in under a second, supports checkpointing/restoring entire environments, and bills only for actual CPU and memory consumption down to the second.
- Global Edge Deployment — Deploy applications across 18 worldwide regions—from Sydney to São Paulo—achieving sub-100ms response times. This gives users a native-app experience regardless of their geographic location, with granular routing for fine-tuned traffic control.
- Built-In Private Networking — Automatic private networks per sandbox with granular routing and end-to-end encryption. No additional configuration needed—VMs get isolated, secure networking out of the box for distributed systems and multi-tenant architectures.
- Framework-Agnostic Deployment — Deploy with any popular framework including Phoenix, Rails, Django, Laravel, NextJS, SvelteKit, and .NET. No Dockerfile? No problem—the CLI automatically generates containers for supported frameworks, dramatically reducing setup complexity.
- Integrated Storage Solutions — Fast local NVMe storage for low-latency workloads plus global, durable object storage for persistent data. Supports snapshotting environments, persisting state, and scaling storage alongside sandboxes seamlessly.
Use Cases
AI Agent Infrastructure
Build and scale AI agents that require dedicated resources per instance. Each agent runs on its own VM with dedicated CPU, memory, networking, and private filesystem—eliminating noisy neighbor issues. Supports persistent brains for long-running agents and ephemeral workers for burst processing, scaling to millions of users. Target Audience: AI/ML engineers and startups building autonomous agents, copilots, and AI-powered applications
Running Untrusted or AI-Generated Code Safely
Execute AI-generated code, user-submitted scripts, or third-party plugins in hardware-isolated sandboxes. Sprites provide complete environment isolation with checkpoint/restore capabilities—if something breaks, simply restore to the last snapshot. Pay-per-second billing makes experimentation cost-effective. Target Audience: Platform developers, EdTech companies, and SaaS products offering code execution environments to their users
Globally Distributed Web Applications
Deploy web applications close to users worldwide with sub-100ms latency. Ideal for real-time collaboration tools, interactive dashboards, and consumer-facing apps where performance directly impacts user experience. Zero-downtime deploys ensure continuous availability during updates. Target Audience: Full-stack developers and engineering teams building latency-sensitive consumer and B2B web applications
Distributed Database Systems
Run clustered databases like CockroachDB, globally-distributed Postgres, and modern RPC systems like Elixir FLAME without managing complex infrastructure. Fly Machines handle the orchestration, letting teams focus on application logic rather than Terraform configurations. Target Audience: Backend engineers and database administrators building distributed, high-availability data systems
Pros
- Instant deployment and fast cold starts—Machines launch in seconds and Sprites in under one second, enabling rapid iteration and true serverless-like economics without sacrificing control.
- Hardware-level isolation via KVM virtualization on bare metal with a memory-safe Rust and Go stack, providing enterprise-grade security for running untrusted code.
- Per-second billing granularity means you only pay for actual CPU and memory consumption—no idle costs for bursty or experimental workloads.
- Framework-agnostic with zero-config container generation for popular frameworks (Rails, Django, Phoenix, Laravel, NextJS, etc.), reducing time-to-deploy significantly.
- Global edge presence across 18 regions with built-in private networking, autoscaling, and zero-downtime deploys—delivering native-app performance worldwide without managing complex infrastructure.
Cons
- Limited to 18 edge regions compared to hyperscale providers (AWS, GCP, Azure) with 30+ regions, which may be insufficient for applications requiring hyper-local presence in underserved geographies.
- Learning curve for developers unfamiliar with container orchestration concepts, despite the simplified CLI—distributed systems patterns still require understanding.
- Pricing complexity with per-second billing across multiple resource dimensions (CPU, memory, storage, bandwidth) can make cost prediction challenging for budget-constrained teams.
- Ecosystem maturity—while growing, Fly.io's managed services catalog (databases, queues, caches) is narrower than established cloud providers, potentially requiring more self-managed components.
