new-fly-app-instance

name

new-fly-app-instance

description

Stand up a new changelog.com Fly.io app instance (named changelog-YYYY-MM-DD), validate the whole CI/CD pipeline from a fork first, and later promote the instance to production. Use when creating a fresh Fly app, rotating the production instance, testing deploys from a fork before a PR, or cutting APP_PROD_INSTANCE over to a new instance. The operator runs every command themselves on their host; these touch production (Neon Postgres, Cloudflare R2, the CDN), so the skill is human-in-the-loop by design.

New Fly.io app instance — validate, create & promote

A guided runbook in two phases.

Before the PR merges — validate from a fork:

• Part A — Prepare your fork. Fork the repo and configure GitHub Actions so the pipeline can run in your account.
• Part B — Create & prime the Fly app. Stand up the dated instance and stage its one bootstrap secret.
• Part C — Trigger the pipeline & verify. Push to your fork's master to drive the workflow end-to-end and confirm it deploys to the new app.

After the PR merges — promote to production:

• Part D — Promote to production. Cut APP_PROD_INSTANCE and live traffic over to the new instance.

A–C validate a new instance from a fork before the PR lands; D happens later, once the merged instance has proven itself.

How to drive this skill — read every time

This runbook touches production: the Neon Postgres prod database, Cloudflare R2 buckets, and the public CDN. Human-in-the-loop is the point — but the default is to do the work yourself and verify, not to hand the operator a list of commands to type.

First, establish where you're running — the rules below depend on it:

• On the operator's host — one copy of the repo, possibly already authenticated. No file syncing needed; you may run authed commands if op / flyctl are signed in (still confirm before any production mutation).
• In a separate sandbox / VM — a distinct copy of the repo, usually not authenticated for production. Mirror file changes to the host, and run 1Password / Fly commands on the host.

Check at startup — flyctl auth whoami, op whoami, and whether this is the operator's real working tree or a copy — and if unsure, ask. Say which mode you're in before driving.

• Run each step yourself; the operator stays in the loop. Default to running commands here in the VM and verifying the result — don't hand the operator a list to type. They can always take a step over (then you verify). Before any command that mutates production (deploy, secret-set, DB/CDN change), say what it will do and get a yes first. One step at a time; don't advance until the current step is verified.
• Guard 1Password-authed production commands. Commands that need 1Password — op read / op signin, fnox exec --profile production|ci, and the secret-set that wraps op read (B4) — touch the crown-jewel token. In a sandbox without auth, the operator runs these on the host and you verify from their output; never copy the OP service-account token or an op sign-in into a sandbox. On the host with op already signed in, you may run them — confirm first. (Same for Fly auth: if the current environment lacks it, the operator runs the flyctl step or supplies a token.)
• Sandbox only: keep it in sync with the host. When you're in a separate copy, every file change must land in both — edit here and give the operator the exact change for the host (or mirror their host change here), then diff to confirm they match. On the host there's a single copy — skip this.
• Verify before advancing. If output looks off, diagnose it together. Never "continue anyway".
• Flag every production mutation loudly. Where a step writes to the prod DB, R2, the CDN, or shared repo config, say so and confirm intent first.
• Adapt to what's already done — if a step was completed out of band, verify its result and skip ahead rather than redoing it.

Naming convention: a new instance is changelog-YYYY-MM-DD using the date it's created — the date part is significant (it's how instances are told apart, and it threads through the Fly app name, the fly.io/<name>/ dir, and APP_PROD_INSTANCE). Throughout, ${OLD} is the current production app (mise env | rg APP_PROD_INSTANCE, currently changelog-2025-05-05) and ${NEW} is the one being created.

---

Before the PR merges — validate from a fork

Parts A–C run entirely in your fork and prove the new instance end-to-end before the PR that adds it is merged.

Part A — Prepare your fork

A1. Fork the repo and confirm the URL

Ask the operator to fork thechangelog/changelog.com to their account and paste the fork URL (e.g. https://github.com/gerhard/changelog.com). The fork is public, so verify it yourself before continuing — e.g. gh repo view <owner>/changelog.com --json url,visibility,isFork or fetch the URL. Confirm it exists, is public, and is a fork. The fork owner is the IMAGE_OWNER value in A2.

A2. Set GitHub Actions variables & secrets on the fork

Under the fork's Settings → Secrets and variables → Actions:

Variables (Variables tab):

Variable	Set to	Why
APP_PROD_INSTANCE	${NEW} (e.g. changelog-2026-06-14)	The dated app this fork deploys to. mise.toml's [env] only supplies the default (${OLD}); the workflows forward vars.APP_PROD_INSTANCE so the fork targets its own app. The date must match the Fly app created in Part B.
IMAGE_OWNER	the fork owner (e.g. gerhard)	Publishes images to ghcr.io/<owner>/changelog-{runtime,prod} in your account instead of thechangelog. Defaults to thechangelog via mise.toml when unset.
DEPLOY_FROM_REPO	this repo as github.com/owner/repo (e.g. github.com/gerhard/changelog.com)	Opt-in gate for publish + deploy. Set it to the fork's own github.com/<owner>/changelog.com to run the full pipeline; leave unset for build & test only. No default anywhere — each repo that deploys declares itself.
RUNS_ON	namespace if this repo has Namespace.so access, else (unset)	ship_it.yml runs on Namespace.so when RUNS_ON contains namespace, otherwise GitHub-hosted ubuntu-latest — exactly one. Set namespace on any repo with access: the canonical repo or a fork that has it (e.g. gerhard/changelog.com, and others may). A fork without access leaves it unset and runs on GitHub.

Secrets (Secrets tab):

Secret	When	Why
OP_SERVICE_ACCOUNT_TOKEN	only if testing publish/deploy in CI	A 1Password service-account token. Build & test run unauthenticated, so it's not needed for those. Publish (GHCR) and Deploy (Fly) resolve all other credentials via fnox exec --profile ci, which needs this token.

Publish & deploy are gated by DEPLOY_FROM_REPO. github.yml / namespace.yml carry if: "${{ format('github.com/{0}', github.repository) == env.DEPLOY_FROM_REPO && github.ref_name == 'master' }}" (compares the live github.com/owner/repo to the variable; == keeps it safe when the var is unset — endsWith would match an empty var. GitHub expressions have no replace, so the github.com/ host is literal in format), and mise-tasks/team/cd builds the same string (${GITHUB_SERVER_URL#https://}/${GITHUB_REPOSITORY}) and guards on it. A fork opts into the full pipeline simply by setting DEPLOY_FROM_REPO to its own github.com/<owner>/changelog.com (and providing OP_SERVICE_ACCOUNT_TOKEN) — no source edits. Leave it unset for build & test only. The canonical repo must set DEPLOY_FROM_REPO=github.com/thechangelog/changelog.com for its own publish/deploy to run (the workflow if: reads the variable, not mise's defaults).

Confirm the variables/secrets are set (and whether the gate was touched) before moving on.

---

Part B — Create & prime the Fly app

Run B-steps from the host. ${NEW} = the dated name from A2.

B1. Create the Fly app

flyctl apps create ${NEW} --org changelog

Registers the app name in the changelog org. No machines, no traffic, no cost yet — reversible via flyctl apps destroy. Healthy result: New app created: ${NEW}.

B2. Copy the current instance's config

cp -r fly.io/${OLD} fly.io/${NEW}
cd fly.io/${NEW}

Each instance keeps its Fly config in fly.io/<app-name>/. Copying the current prod instance gives a known-good baseline. Run the rest of Part B from inside fly.io/${NEW}.

Verify the copy. Confirm it's a clean, unedited baseline: diff fly.io/${OLD}/fly.toml fly.io/${NEW}/fly.toml must be empty (identical). Any diff here means the copy is wrong — stop and resolve before the B3 edits. In a sandbox, the operator's host cp won't appear locally — reproduce it (cp -r fly.io/${OLD} fly.io/${NEW}) before diffing, so later edits land on the right files.

B3. Point fly.toml at the new app

Two required edits to fly.io/${NEW}/fly.toml:

• app = "${NEW}" — must match B1.
• [env] APP_INSTANCE = "experimental" — important. config/prod.exs only starts the Oban job queues when APP_INSTANCE == "production"; any other value leaves the queue list empty. So an experimental instance boots and serves HTTP but does not process scheduled jobs (Zulip import, feed/person bouncers, email) against the shared prod database. Without this, a second live instance would double-process those jobs.

Then review the rest of the file against the Fly config reference. The copied config carries whatever conventions were current when the previous instance was created, so this is the moment to catch drift. WebFetch the reference linked at the top of fly.toml (https://fly.io/docs/reference/configuration/) and, against the existing values, surface — as suggestions, in addition to the two required edits:

• Deprecated / non-standard constructs to modernize (e.g. [experimental] cmd → [processes]; the verbose [[services]] + [[services.ports]] + [[services.http_checks]] → the simpler [http_service] + [[http_service.checks]] for an HTTP-only app).
• Newer options worth adopting given how this app runs (e.g. explicit auto_stop_machines / auto_start_machines / min_machines_running to document always-on vs scale-to-zero; [[vm]] cpus/memory/cpu_kind instead of just size; duration strings like kill_timeout = "30s").

Sanity-check the inherited values, not just the structure. The limits and sizes were copied from the previous instance — confirm they still fit how the app actually runs:

• Cross-check internal_port against the app's configured HTTP port (config/prod.exs → http: [port: ...]).
• Justify the concurrency type/limits from the connection profile: grep for LiveView / Phoenix sockets / channels (lib/**/endpoint.ex, socket "..."). Long-lived websockets (LiveView) justify type = "connections" and generous limits — lowering them would shed live viewers during exactly the high-traffic live events you want to serve. Pure request/response would point to type = "requests" instead.
• Treat inherited values as proven-in-prod: validate against real peaks on fly-metrics.net rather than changing them blind. A connection limit does not bound CPU — for LiveView-heavy load the saturation risk is CPU / VM size, so watch metrics and scale [[vm]] / region count rather than touching the limit.

Present each with a recommendation and let the operator choose — don't apply unilaterally. The experimental instance is the safe place to trial any of these before they reach production (Part D).

Verify the edits yourself — don't ask the operator to paste a diff. Run diff fly.io/${OLD}/fly.toml fly.io/${NEW}/fly.toml and confirm it shows only the agreed changes. In a sandbox, first reproduce the operator's edits locally so both copies match.

Validate the schema, not just TOML syntax. A TOML parser (tomllib) only checks that the file parses — it won't catch Fly schema mistakes like auto_start_machines = "off" (it's a bool, not the string enum that auto_stop_machines takes), or fields whose types changed across flyctl versions. Run flyctl config validate -c fly.io/${NEW}/fly.toml. It needs Fly auth, so in a sandbox have the operator run it on the host before deploying — otherwise the first flyctl secrets set / deploy is where the error surfaces (as it did once here).

B4. Stage the one bootstrap secret

flyctl secrets set --stage \
    OP_SERVICE_ACCOUNT_TOKEN="$(op read op://changelog/op/credential --account changelog.1password.com --cache)"

OP_SERVICE_ACCOUNT_TOKEN is the single secret set directly on Fly; everything else resolves at boot via fnox exec --profile production, which reads 1Password using this token. --stage records it without deploying (no machines yet); it applies on the first deploy. Healthy result: Secrets are staged for the first deployment. Requires op whoami to be signed in; if not, eval $(op signin) first.

Optional first-boot smoke test (no prod writes). Before wiring CI you can seed the app with a known-good image while skipping the release command: flyctl deploy --ha=false --no-release-command --image=ghcr.io/thechangelog/changelog-prod:<LATEST_SHA> (latest tag at https://github.com/thechangelog/changelog.com/pkgs/container/changelog-prod). --no-release-command skips mix ecto.migrate + mix changelog.static.upload so it touches no prod data. Otherwise, let Part C drive the deploy.

Part B done. The app exists and has its bootstrap secret staged.

---

Part C — Trigger the pipeline & verify

This is where the workflow is exercised for real — not the first step, the last one, once A and B are in place.

C1. Push to the fork's master branch ⭐

Git runs on the host (vm:keep excludes .git/, so a sandbox's git is irrelevant). A host clone usually has only origin → upstream, so add a fork remote first if it's missing (git remote -v to check):

git remote add fork https://github.com/<owner>/changelog.com.git   # if absent
git add -A && git commit            # or amend, operator's choice
git push fork <your-branch>:master

Before pushing, validate any changed workflow YAML. GitHub rejects the whole file on a syntax error. Watch two traps in run:/if: values: mise's parallel separator ::: (e.g. mise run a ::: b) and any expression containing quotes or {…} (e.g. a format(...) if:) — the embedded colon-space or braces break an unquoted YAML scalar, so wrap the whole value in double quotes (run: "… ::: …", if: "${{ … }}"). And a YAML parser only catches syntax — it won't catch invalid GitHub expressions: the expression language has a limited function set (contains, startsWith, endsWith, format, join, toJSON, fromJSON, hashFiles) — notably no replace. Validate both with actionlint: mise x aqua:rhysd/actionlint@latest -- actionlint -ignore 'label "namespace-profile-changelog" is unknown' .github/workflows/*.yml (the ignore drops a false positive for the Namespace self-hosted runner).

ship_it.yml triggers on push to master, and the publish/deploy gate requires github.ref_name == 'master'. Pushing to any other branch runs build & test only — it will not publish an image or deploy. So to validate the full pipeline you must land the change on the fork's master. Remind the operator of this explicitly; it's the single most-forgotten step.

(With DEPLOY_FROM_REPO set to this fork in A2, the master push is also what makes publish + deploy fire here.)

C2. Watch the "Ship It!" run

In the fork's Actions tab, confirm:

• Build & test pass on ubuntu-latest.
• Publish pushes images to ghcr.io/${IMAGE_OWNER}/changelog-{runtime,prod}.
• Deploy runs flyctl deploy against ${NEW}.

⚠️ A new GHCR package is private → Fly can't pull it. The first time images land in a new namespace, ghcr.io/${IMAGE_OWNER}/changelog-{runtime,prod} are private, so flyctl deploy fails with Authentication required to access image "ghcr.io/.../changelog-prod:…". Make the package public before the deploy — GitHub → your profile/org → Packages → the package → Package settings → Change visibility → Public. At minimum changelog-prod (the image Fly pulls; the prod image is self-contained, so the runtime package can stay private). One-time per new namespace (a fork, or a new org). Alternatively give Fly registry credentials, but public is simplest for a test fork.

⚠️ Deploy touches production data. fly.toml's release_command runs on.deploy in the new container before cutover: fnox exec --profile production -- mix ecto.migrate and mix changelog.static.upload. With profile production these hit the prod Neon DB and prod R2 assets bucket even on an experimental app. ecto.migrate is a no-op when prod is already migrated; static.upload re-pushes assets. Watch the release-command logs for fnox: command not found (fnox must be installed in Dockerfile.runtime).

C3. Verify the deployed app

flyctl status --app ${NEW}
flyctl logs --app ${NEW}
curl -fsS https://${NEW}.fly.dev/health

Confirm the machine is started/healthy, logs are clean, /health returns OK. team:cd deploys with --ha=false, so a fresh instance comes up as a single machine in the primary region (iad). The instance now runs but is not in the request path and not processing jobs (APP_INSTANCE=experimental) — exactly what we want until promotion.

Deploys are blue-green — they never replace a running app in place. fly.toml sets [deploy] strategy = "bluegreen" and team:cd doesn't override it (--ha=false is orthogonal — it only sets the machine count, not the strategy). On a redeploy, new (green) machines boot alongside the running (blue) ones, one per region, and traffic shifts only once green pass health checks; if they fail, blue keeps serving and the deploy fails safely. (The very first deploy of a fresh app has no blue to protect, so blue-green only kicks in from the second deploy on — e.g. C5's GitHub redeploy, and every prod deploy.) Verify mid-deploy with flyctl machines list --app ${NEW}: you'll see green machines in created/0/2 next to started/1/1 blue, one green per region. After cutover, confirm with flyctl config show --app ${NEW} | grep -A2 '"deploy"' → "strategy": "bluegreen".

C4. Run across two regions — required

Two regions is essential, not optional: a single-region failure must not take the site down (status.changelog.com/incident/513790). Validate it on the experimental instance too. It isn't promoted yet, so APP_PROD_INSTANCE still points at the old prod — override it inline (the mise.toml [env] template coalesces the OS env var over its default):

APP_PROD_INSTANCE=${NEW} mise team:prod:multi-region
flyctl status --app ${NEW}

team:prod:multi-region runs flyctl scale count 2 --max-per-region 1 --region iad,ewr, so you end with 1 healthy machine in iad and 1 in ewr — --max-per-region 1 rebalances if the deploy happened to bring up two in the primary. Confirm flyctl status lists both regions, each started with passing checks.

Then confirm the app actually serves 200 from each region — started ≠ serving traffic. Force each region and read the serving region (sr) out of Fly's debug header:

for r in iad ewr; do
  echo "== forcing ${r} =="
  curl -sS -D - -o /dev/null \
    -H "Fly-Force-Region: ${r}" -H "Flyio-Debug: doit" \
    https://${NEW}.fly.dev/health | grep -iE '^(HTTP/|flyio-debug:)'
done

Each must show 200 and a flyio-debug JSON whose "sr" (serving region) matches the region you forced — that proves that region's machine handled it (sr = serving region, sid = serving machine; nr is only the edge you hit). Use Fly-Force-Instance-Id: <machine-id> to pin a specific machine. (Technique borrowed from pipely's test/acceptance/periodic/region.hurl.)

Promotion (Part D) makes this the permanent default.

C5. Confirm the GitHub-hosted path too

The first run proved the Namespace path (the fork's default, RUNS_ON=namespace). ship_it.yml runs exactly one runner, so the GitHub-hosted path hasn't executed yet — prove it too, since forks without Namespace access rely on it. Flip the runner and trigger again:

• Set the RUNS_ON repo variable to github (any value not containing namespace works — including unsetting it; the github job runs whenever RUNS_ON lacks namespace).
• Trigger a fresh "Ship It!" run on master — amend + force-push, or any new commit (a workflow_dispatch from the Actions tab also works).
• Confirm the github job runs (on ubuntu-latest, not the Namespace runner) and that build & test → publish → deploy all pass, deploying the same ${NEW}. This exercises a genuinely different code path: with no remote builder, docker:build-runtime --loads the runtime into the local Docker daemon and docker:test / docker:build-prod FROM it (Namespace instead pushes the runtime to nscr.io) — so it's worth confirming independently.
• Afterwards set RUNS_ON back to namespace to restore the preferred default (persistent Namespace caching).

Part C done. The pipeline is proven end-to-end in your account on both runners — Namespace and GitHub-hosted — deploying to ${NEW} and running healthy across two regions.

---

After the PR merges — promote to production

Part D runs once the merged instance config is on master and the experimental instance has soaked.

Part D — Promote an instance to production

Only when ${NEW} has proven itself. Deliberate, ordered cutover — do not batch. Region resilience is already in place: C4 scaled ${NEW} to two regions (iad,ewr, one machine each) and that count persists across deploys, so there's no separate scale step here — just confirm flyctl status still shows both.

D1. Make ${NEW} the default for team tasks

APP_PROD_INSTANCE is defined once, in mise.toml [env], as a template whose literal fallback is the current prod app. Edit that fallback to ${NEW}, then:

mise trust
mise env | rg APP_PROD_INSTANCE   # should show ${NEW}

This is what team:cd, team:prod:multi-region, etc. target locally.

D2. Flip the instance to production mode

Edit fly.io/${NEW}/fly.toml: set [env] APP_INSTANCE = "production" so the Oban queues start (inverse of B3). Remove any env vars that shouldn't be on the canonical prod instance (e.g. stray URL_HOST, STATIC_URL_HOST). Redeploy so the change and the queues take effect.

⚠️ From here ${NEW} is a full production worker.

D3. Cut the CDN origin over

Update the origin in pipely to https://${NEW}.fly.dev, then release a new Pipely version. This is the public traffic cutover — changelog.com now serves from ${NEW}. Watch Honeycomb / BetterStack as it rolls.

D4. Update the upstream GitHub Actions variable

Set the APP_PROD_INSTANCE repo variable on thechangelog/changelog.com to ${NEW}: https://github.com/thechangelog/changelog.com/settings/variables/actions/APP_PROD_INSTANCE so upstream CI deploys target the new instance.

D5. Sweep remaining references

rg ${OLD}

Update every lingering reference — the INFRASTRUCTURE.md architecture diagram, fly.toml PIPEDREAM_HOST, docs — to ${NEW}.

D6. Retire the old instance

Once ${NEW} is confirmed healthy in production and serving all traffic, scale ${OLD} down (eventually flyctl apps destroy ${OLD}) so you're not paying for two prod instances. Only after a soak period.

Part D done. ${NEW} is production; ${OLD} is retired.

---

Related

• Branch the prod DB for local work: mise team:neon:branch-create, then mise team:db:neon-use-remote-branch (or mise team:db:neon-import-main-locally).
• Secrets model: fnox.toml holds 1Password references only; OP_SERVICE_ACCOUNT_TOKEN is the one manually-set secret (on Fly and in GitHub Actions).