Fly.io Deployment Cheat Sheet
flyctl commands, fly.toml configuration, and scaling patterns for deploying apps and machines to Fly.io regions.
2 PagesBeginnerJun 1, 2026
Launch a New App
Bootstrap a fly.toml and provision an app from an existing project directory.
bash
fly auth login# Detects your framework/Dockerfile and generates fly.tomlfly launch --name my-app --region iad --no-deploy# Deploy itfly deploy
fly.toml Essentials
Minimal config for an HTTP service with a health check.
toml
app = "my-app"primary_region = "iad"[build] dockerfile = "Dockerfile"[http_service] internal_port = 8080 force_https = true auto_stop_machines = true auto_start_machines = true min_machines_running = 1[[http_service.checks]] interval = "15s" timeout = "2s" grace_period = "5s" method = "GET" path = "/health"
Scaling & Secrets
Adjust machine count/size and manage runtime secrets.
bash
# Scale out to 3 machines and set VM sizefly scale count 3fly scale vm shared-cpu-2x --memory 512# Set a secret (triggers a redeploy with the new value)fly secrets set DATABASE_URL="postgres://user:pass@host/db"# Attach a managed Postgres clusterfly postgres create --name my-app-dbfly postgres attach my-app-db
Core Concepts
Terminology specific to Fly.io's Machines-based platform.
- Machine- a fast-booting Firecracker microVM running your container
- Region- deploy the same app across multiple regions for low latency
- fly.toml- per-app config: build, services, checks, mounts
- Volumes- persistent, region-pinned storage attached to a machine
- flyctl- the CLI for deploy, scale, logs, ssh, and secrets
Pro Tip
Set `auto_stop_machines = true` with `min_machines_running = 0` for low-traffic services — Fly.io will suspend idle machines and resume them on the next request, cutting compute cost to near zero without changing your deploy config.
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