High Availability & Global Replication

This document applies to Postgres clusters running on our next-gen Apps V2 architecture (Fly Machines). If you created your cluster using any flyctl version before v0.0.412, refer to Fly Postgres on Apps V1 and Multi-region PostgreSQL instead.

Fly Postgres uses stolon for leader election and streaming replication between 2+ Postgres servers. It provides a number of things, including a “keeper” that controls the Postgres process, a “sentinel” that builds the cluster view, and a “proxy” that always routes connections to the current leader.

If the leader becomes unhealthy (e.g. network or hardware issues), the proxy drops all connections until a new leader is elected. Once it’s ready, new connections go to the new leader automatically. The previous leader’s VM will be replaced by another VM which will rejoin the cluster as a replica.

Adding replicas

The easiest way to add additional replicas at this time is through the fly machine clone command:

fly machine clone 148e306c77e089 --region ord --app <app-name>
Cloning machine 148e306c77e089 into region lax
Provisioning a new machine with image registry-1.docker.io/flyio/postgres:14...
  Machine 17814e3b990389 has been created...
  Waiting for machine 17814e3b990389 to start...
  Waiting for 17814e3b990389 to become healthy (started, 3/3)
Machine has been successfully cloned!

This will clone the spec from the source machine and use it to create the new replica in a desired region.

Performing a failover

To perform a manual failover against your HA Postgres app, run the following command:

fly postgres failover --app <app-name>
Performing a failover
  Waiting for e784927ad23583 to become healthy (started, 3/3)
  Waiting for 148e306c77e089 to become healthy (started, 3/3)
Failover complete

Note: Only healthy members residing in your PRIMARY_REGION will be considered for leadership.

Performing a regional failover

There may be situations where you want to move leadership into a completely new region. While this process is a bit more involved, you can achieve this by performing the steps below.

If you haven’t already pulled down your fly.toml configuration file, you can do so by running:

fly config save --app <app-name>

Now, let’s open up the fly.toml file and set the PRIMARY_REGION environment variable to our target region. In this example, we are looking to move leadership into the lax region.


Before we can deploy this change, we must first identify which Postgres version we are currently running.

fly image show
Image Details
e784927ad23583  registry-1.docker.io  flyio/postgres  14.4  v0.0.32 sha256:9daaa15119742e5777f5480ef476024e8827016718b5b020ef33a5fb084b60e8
148e275b1d1d89  registry-1.docker.io  flyio/postgres  14.4  v0.0.32 sha256:9daaa15119742e5777f5480ef476024e8827016718b5b020ef33a5fb084b60e8

Take note of the version specified within the Tag column, we will be using this in our next command.

Warning: This deploy process will result in a small amount of downtime. Once the PRIMARY_REGION change has been deployed, your cluster will become read-only until the failover process completes.

fly deploy . --image flyio/postgres:<tag> --strategy=immediate

Once the deploy process has completed, we can now work to transfer leadership into our new region.

fly pg failover
Performing a failover
  Waiting for e784927ad23583 to become healthy (started, 3/3)
  Waiting for 148e306c77e089 to become healthy (started, 3/3)
Failover complete

That’s it! You should now run fly status to verify your changes.

Connecting to read replicas

The generated connection string uses port 5432 to connect to PostgreSQL. This port always forwards you to a writable instance. Port 5433 is direct to the PostgreSQL member, and used to connect to read replicas directly.

You can use the proxy port (5432) to connect from every region, but it will be quite slow. Especially because we put our PostgreSQL cluster in Santiago. Connecting to “local” replicas is much quicker, but does take some app logic.

The basic logic to connect is:

  1. Set a PRIMARY_REGION environment variable on your app, scl for our chaos-postgres cluster.
  2. Check the FLY_REGION environment variable at connect time, use DATABASE_URL as is when FLY_REGION=scl
  3. Modify the DATABASE_URL when running in other regions:
    1. Change the port to 5433

This is what it looks like in Ruby:

class Fly
  def self.database_url
    primary = ENV["PRIMARY_REGION"]
    current = ENV["FLY_REGION"]
    db_url = ENV["DATABASE_URL"]

    if primary.blank? || current.blank? || primary == current
      return db_url

    u = URI.parse(db_url)
    u.port = 5433

    return u.to_s

Running this in scl will use the built-in DATABASE_URL and connect to port 5432:


In the other regions, the app will connect to port 5433:


Detect write requests

Catch read-only errors

PostgreSQL conveniently sends a “read only transaction” error when you attempt to write to a read replica. All you need to do to detect write requests is catch this error.

Replay the request

Once caught, just send a fly-replay header specifying the primary region. For chaos-postgres, send fly-replay: region=scl, and we’ll take care of the rest.

If you’re working in Rails, just add this to your ApplicationController:

class ApplicationController < ActionController::Base
  rescue_from ActiveRecord::StatementInvalid do |e|
    if e.cause.is_a?(PG::ReadOnlySqlTransaction)
      response.headers["fly-replay"] = "region=#{r}"
      Rails.logger.info "Replaying request in #{r}"
      render plain: "retry in region #{r}", status: 409
      raise e

Library support

We would like to build libraries to make this seamless for most application frameworks and runtimes. If you have a particular app you’d like to distribute with PostgreSQL, post in our community forums and we’ll write some code for you.

Consistency model

This is a fairly typical read replica model. Read replicas are usually eventually consistent, and can fall behind the leader. Running read replicas across the world can exacerbate this effect and make read replicas stale more frequently.

Request with writes

Requests to the primary region are strongly consistent. When you use the replay header to target a particular region, the entire request runs against the leader database. Your application will behave like you expect.

Read only requests

Most apps accept a POST or PUT, do a bunch of writes, and then redirect the user to a GET request. In most cases, the database will replicate the changes before the user makes the second request. But not always!

Most read heavy applications aren’t especially sensitive to stale data on subsequent requests. A lagging read replica might result in an out of date view for users, but this might be reasonable for your use case.

If your app is sensitive to this (meaning, you never, under any circumstances want to show users stale data), you should be careful using read replicas.

Managing eventual consistency

For apps that are sensitive to consistency issues, you can add a counter or timestamp to user sessions that indicates what “version” of the database a particular user is expecting. When the user makes a request and the session’s data version differs from the replica, you can use the same fly-replay header to redirect their request to the primary region – and then you’ll know it’s not stale.

In theory, you could run PostgreSQL with synchronous replication and block until replicas receive writes. This probably won’t work well for far flung read replicas.

This is wrong for some apps

We built this set of features for read heavy apps that are primary HTTP request based. That is, most requests only perform reads and only some requests include writes.

Write-heavy workloads

If you write to the database on every request, this will not work for you. You will need to make some architectural changes to run a write-heavy app in multiple regions.

Some apps write background info like metrics or audit logs on every request, but are otherwise read heavy. If you’re running an application like this, you should consider using something like nats.io to send information to your primary region asynchronously.

Truly write-heavy apps require latency aware data partitioning, either at the app level or in a database engine. There are lots of interesting new databases that have features for this, try them out!

Long lived connections

If your app makes heavy use of long lived connections with interpolated writes, like websockets, this will not work for you. This technique is specific to HTTP request/response based apps that bundle writes up into specific requests.