Mastodon is a free, open-source social network server based on the ActivityPub standard.
The Mastodon server is implemented a Rails app, which relies on PostgresSQL and Redis. It uses Sidekiq for background jobs, along with a separate Node.js http streaming server.
While following this guide, you may find it helpful to also view the Mastodon docker image list, the Mastodon Dockerfile, or the Mastodon docker-compose.yml.
You'll need a Fly.io account, and the Flyctl CLI.
Fork this repo and clone a copy of it. Choose a name for your app that isn't already taken on https://fly.io/, and run the script bin/name YOURNAME
. Follow this readme from inside your repo, after you have run the script, so that all of the steps will be updated for the name of your Fly.io app.
fly apps create mastodon-example
fly scale memory 1024 # Rails + Sidekiq needs more than 512
export SECRET_KEY_BASE=$(docker run --rm -it tootsuite/mastodon:latest bin/rake secret)
export OTP_SECRET=$(docker run --rm -it tootsuite/mastodon:latest bin/rake secret)
fly secrets set OTP_SECRET=$OTP_SECRET SECRET_KEY_BASE=$SECRET_KEY_BASE
docker run --rm -e OTP_SECRET=$OTP_SECRET -e SECRET_KEY_BASE=$SECRET_KEY_BASE -it tootsuite/mastodon:latest bin/rake mastodon:webpush:generate_vapid_key | sed 's/\r//' | fly secrets import
Redis is used to store the home/list feeds, along with the Sidekiq queue information. The feeds can be regenerated using tootctl
, so persistence is not strictly necessary.
Choose a region that is close to your users. See Fly regions for a list of regions or run fly platform regions
. In this example, we'll use sjc
(San Jose, CA).
fly apps create mastodon-example-redis
bin/fly-redis volumes create --region sjc --size 1 mastodon_redis
bin/fly-redis deploy
The fly.toml
uses a [mounts]
section to connect the /opt/mastodon/public/system
folder to a persistent volume.
Create that volume below, or remove the [mounts]
section and uncomment [env] > S3_ENABLED
for S3 storage.
fly volumes create --region sjc mastodon_uploads
S3, Wasabi, etc
fly secrets set AWS_ACCESS_KEY_ID=xxx AWS_SECRET_ACCESS_KEY=yyy
Uncomment the section in fly.toml
to configure AWS S3 or Wasabi. See mastodon.rake for the env vars needed for MinIO or Google Cloud Storage.
To serve cloud-stored images directly from your domain, set S3_ALIAS_HOST
in fly.toml
and then uncomment the section at the top of Caddyfile
.
fly pg create --region sjc --name mastodon-example-db
fly pg attach mastodon-example-db
fly deploy -c fly.setup.toml # run `rails db:schema:load`, may take 2-3 minutes
Mastodon sends emails on sign-up, to confirm email addresses. It also uses emails for password resets, notifications to the server admins, and various other tasks. To have a fully-functioning Mastodon server, you'll need to create an account with an email service like Postmark or Mailgun, get credentials, and provide those credentials to Mastodon as env vars or secrets. See fly.toml
for an example of the env vars you would set, and then provide your credentials as Fly secrets:
fly secrets set SMTP_LOGIN=<public token> SMTP_PASSWORD=<secret token>
-
Edit
fly.toml
and setLOCAL_DOMAIN
to your custom domain. -
Run
fly ips list
, and if the list is empty, runfly ips allocate-v4
. -
Then, create DNS records for your custom domain.
If your DNS host supports ALIAS records:
@ ALIAS mastodon-example.fly.dev www CNAME mastodon-example.fly.dev
If your DNS host only allows A records, use the IP. For example, if your IP was
3.3.3.3
:@ A 3.3.3.3 www CNAME @
-
Finally, generate SSL certificates from Let's Encrypt:
fly certs add MYDOMAIN.COM fly certs add WWW.MYDOMAIN.COM
fly deploy
After you've deployed, sign up. You will hopefully get an email, but if you don't, we'll manually confirm your account regardless as part of making you an owner on the instance. Substitute your own username in this command:
fly ssh console -C 'tootctl accounts modify <username> --confirm --role Owner'
Enjoy your server.
If you still haven't gotten enough, here are some notes on how to operate your instance after it's running.
Useful resources for operating and debugging a running instance include fly logs
, fly scale show
, fly ssh console
, the Metrics section of fly dashboard
, and the Sidekiq dashboard at https://mastodon-example.fly.dev/sidekiq (you have to be logged in to Mastodon as an admin user to see it).
If your instance is getting slow or falling over, you may find Scaling Mastodon in the Face of an Exodus helpful.
To upgrade to a new version of Mastodon, change the version number on the first line of Dockerfile
, and then check the release notes for upgrade instructions.
If there are migrations that need to be run, make sure that the release command in fly.toml
is uncommented.
If there are migrations that must be run before deploying to avoid downtime, you can run the pre-deploy migrations using a second app. By scaling this app to a VM count of zero, it won't add to our bill, but it will let us run the pre-deploy migrations as a release command before the web processes get the new code.
fly apps create mastodon-example-predeploy
bin/fly-predeploy secrets set OTP_SECRET=placeholder SECRET_KEY_BASE=placeholder
bin/fly-predeploy secrets set $(fly ssh console -C env | grep DATABASE_URL)
bin/fly-predeploy scale memory 1024
bin/fly-predeploy scale count 0
bin/fly-predeploy deploy
After that, just deploy the updated container as usual, and the post-deploy migrations will run in the regular release command:
fly deploy
If your instance attracts many users (or maybe a few users who follow a huge number of other accounts), you may notice things start to slow down, and you may run out of database, redis, or storage space.
If you need more web processes, or more sidekiq workers, the easiest option is to choose a larger Fly VM size via fly scale vm
. With a larger VM, you can run more Puma processes by setting WEB_CONCURRENCY
, and you can run more sidekiq processes by setting OVERMIND_FORMATION
. Try to aim for about as many Puma+Sidekiq processes as you have cores, and review the CPU usage of your VM to know whether to adjust up or down.
For example, if you upgrade to dedicated-cpu-4x
, you might set WEB_CONCURRENCY=2
and OVERMIND_FORMATION=sidekiq=2
in fly.toml
.
At that point, you'll have two Puma processes and two Sidekiq processes, running 5 threads each. If your CPUs aren't fully utilized yet, you can increase the threads for each single-CPU process by setting MAX_THREADS
. Adjust up or down until your CPUs are as utilized as you'd like them to be.
If you need to scale beyond the largest Fly VM (8 CPU cores and 16GB, at the time of writing), or you just want to run a bigger number of smaller VMs, you can also do that. We're going to split up responsibilities, creating one type of VM that runs the Sidekiq scheduler process, another type of VM that runs Sidekiq workers for all the other background jobs, and a third type of VM that runs the Rails, Node, and Caddy servers. You'll be able to tell Fly how many of each VM you want, separately.
Caveats:
- You must already be using cloud storage instead of Fly volumes.
- To undo this change you have to destroy your Fly app and recreate it.
Ready? Okay, let's do it:
-
Convert your application to multiple-VM mode by uncommenting the
[processes]
section infly.toml
. -
Scale memory so everything can run successfully.
fly scale memory 512 --group sidekiq # a single sidekiq with 5 threads uses about 400MB fly scale memory 512 --group schedule # a single sidekiq with 5 threads uses about 400MB fly scale memory 512 --group rails # rails with 5 threads plus node uses about 430MB fly scale count schedule=1 rails=2 sidekiq=2 # or your desired number of VMs fly deploy
Increase the number of rails
or sidekiq
processes by running fly scale count rails=N
or fly scale count sidekiq=N
as needed. Don't forget to also adjust the number of Puma and Sidekiq threads, as described in A bigger VM above, to match your CPU and memory settings!
Finally, make sure that your Postgres is big enough to successfully handle one connection for every thread in Pumo or Sidekiq across all VMs. If your postgres is unable to accept more connections, you might need to increase the CPU or memory on your Postgres VM(s), or you might need to add pg_bouncer to act as a connection proxy and reduce the number of open connections directly to the database.