Fly.io’s global network means your app can run closer to your users, but blindly deploying everywhere is a recipe for latency headaches.
Here’s a user’s app running on Fly.io, serving requests from a user in Tokyo to a server in New York:
User (Tokyo) -> DNS Resolution -> Fly.io Edge -> Fly.io App (New York) -> User (Tokyo)
You can see the round trip: Tokyo to New York and back. That’s a lot of distance for a packet to travel.
Fly.io’s core magic is its distributed Anycast network. When a user’s request hits a Fly.io edge location, that edge is configured to route the request to the closest available machine running your app. The "closest" part is key, and it’s not always what you expect.
The problem Fly.io solves is the traditional cloud’s "one-region-or-bust" model. You’d pick a single cloud provider region (e.g., us-east-1) and all your users, regardless of their location, would be funneled there. This meant users in Australia experienced the same latency as users in London, which is obviously terrible. Fly.io’s approach is to let you self-host your application’s compute across many geographic locations, and their network intelligently directs users to the nearest copy.
The primary levers you control are:
fly.tomlconfiguration: This file tells Fly.io where to deploy your app and how to manage it.flyctlcommands: The command-line interface you use to interact with Fly.io, including deploying and managing your app’s configuration.
Here’s a typical fly.toml for an app that needs to be deployed to multiple regions:
app = "my-low-latency-app"
primary_region = "lhr" # London
[deploy]
release_command = "migrate"
[services]
concurrency = 10
internal_port = 8080
[[services.ports]]
force_https = true
handlers = ["http"]
port = 80
[[services.ports]]
handlers = ["http"]
port = 443
[[services.tcp_checks]]
grace_period = "1s"
interval = "10s"
port = 8080
timeout = "2s"
[[hints]]
# This is where the magic happens for regional deployment.
# We tell Fly.io that requests originating from specific geographic
# areas should be routed to specific regions.
#
# The 'ip' field contains CIDR blocks representing IP address ranges
# associated with those geographies. Fly.io's Anycast network uses this
# to make routing decisions.
#
# 'region' is the Fly.io region code where the app should run for requests
# originating from the specified IP ranges.
#
# 'services' specifies which services (defined in the [services] section)
# this hint applies to.
# Example: Route users from North America to the US East region
[[hints.ip]]
ip = "192.0.2.0/24" # Placeholder for North American IPs
region = "iad"
services = ["http", "https"]
# Example: Route users from Europe to the London region
[[hints.ip]]
ip = "203.0.113.0/24" # Placeholder for European IPs
region = "lhr"
services = ["http", "https"]
# Example: Route users from Asia to the Singapore region
[[hints.ip]]
ip = "198.51.100.0/24" # Placeholder for Asian IPs
region = "sin"
services = ["http", "https"]
This configuration is a bit misleading. The hints.ip section doesn’t actually contain real IP ranges for continents. Instead, Fly.io uses its internal, sophisticated understanding of global IP address allocation and network topology to infer user location. When you deploy to multiple regions using flyctl deploy --regions lhr,iad,sin, Fly.io’s edge network automatically handles the routing. The hints section is more of a conceptual guide or for advanced, specific overrides that most users don’t need. The critical part is deploying your app to the regions you want to serve from.
The actual mechanism Fly.io uses is a combination of BGP Anycast and sophisticated geo-IP mapping. When a user’s request hits one of Fly.io’s globally distributed edge routers, that router looks at the source IP address of the request. Fly.io maintains a continuously updated database that maps IP address ranges to geographic locations. Based on this mapping, the edge router then chooses the nearest Fly.io region that has an instance of your application running. This is why simply deploying to lhr,iad,sin is often enough; Fly.io’s network takes care of the rest.
The surprise is that you don’t specify IP ranges in fly.toml for general geo-routing. You just tell Fly.io which regions to deploy your app to. The hints section is primarily for advanced scenarios or overriding default routing behavior if you have specific needs, not for the basic "deploy everywhere" approach.
The next step is understanding how to distribute your data across these regions to avoid latency issues with database operations.