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@@ -62,6 +62,7 @@ Make it fast. Make it reliable. Monitor what's happening.
 
 How to run periodic tasks, long-running jobs, infrastructure automation, and the things that run when you’re asleep.
 
+- [Long-running tasks and machine lifecycle](/docs/blueprints/long-running-tasks/) NEW!!
 - [Building Infrastructure Automation without Terraform](/docs/blueprints/infra-automation-without-terraform/)
 - [Deferring long-running tasks to a distributed work queue](/docs/blueprints/work-queues/)
 - [Task scheduling guide with Cron Manager and friends](/docs/blueprints/task-scheduling/)
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+---
+title: Long-running tasks and machine lifecycle
+layout: docs
+nav: guides
+author: kcmartin
+date: 2026-06-15
+---
+
+This page covers what happens when your machine is busy doing work, but Fly thinks it's idle. Specifically: how `auto_stop_machines` decides what to stop, why a background task is invisible to that decision, and the two patterns that keep work from getting killed.
+
+If you're picking a queue technology or a cron runner, start with the [work queues](/docs/blueprints/work-queues/) or [task scheduling](/docs/blueprints/task-scheduling/) guides instead. This page is about the machine behavior underneath them.
+
+## The problem
+
+A typical setup: a FastAPI endpoint accepts a request, spawns an async task to generate a report, returns `202 Accepted`, and closes the connection. The proxy sees no active connections. A few minutes later, it stops the machine. The report dies half-finished.
+
+This isn't a bug. It's `auto_stop_machines` working exactly as documented. The proxy looks at inbound traffic. It does not look inside the container. From the proxy's point of view, a machine running a 20-minute job and a machine doing nothing look identical.
+
+There are two ways to fix it. Pick one based on whether your work is bursty or steady, request-triggered or queue-driven.
+
+## How autostop actually decides
+
+The Fly proxy evaluates machines every few minutes. The exact rule depends on how many machines you have:
+
+**Multiple machines.** The proxy uses your `soft_limit` [concurrency setting](/docs/blueprints/setting-concurrency-limits/) to compute excess capacity:
+
+```
+excess = num_machines − (num_machines_over_soft_limit + 1)
+```
+
+If `excess ≥ 1`, the proxy stops one machine. The `+ 1` keeps a buffer of one idle machine for incoming traffic.
+
+**Single machine.** Simpler: if load is zero, the proxy stops the machine.
+
+In both cases, "load" means traffic the proxy can see. Background work running inside the machine, whether that's async workers, cron-style loops, or anything else not driven by an inbound request, doesn't count. There's also no way for your application to tell the proxy, "I'm busy, leave me alone."
+
+This is the central fact for the rest of the guide. Everything below is a way to work around it.
+
+### Stop vs. suspend
+
+`auto_stop_machines` takes three values: `"off"`, `"stop"`, and `"suspend"`.
+
+- **stop** shuts the machine down cold. A restart takes seconds (about 2s for a Rails app, less for a small binary).
+- **suspend** dumps the entire VM state (memory, CPU, network) to disk. Resume takes a few hundred milliseconds.
+
+**Stop** is the simpler default: the machine shuts down when it's idle and cold-starts when it's needed again. For most apps, that's the right tradeoff.
+
+**Suspend** is the right choice when cold start is too painful (slow framework boot, heavy initialization, large in-memory state) and you'd still like to idle when inactive. The tradeoff: suspend is rougher on the underlying platform and has more constraints:
+
+- Machines must have 4 GB of RAM or less.
+- Swap and schedules are not supported.
+- Machines updated before June 20, 2024 cannot be suspended.
+- Suspend is not durable. Fly does not guarantee that a suspended machine will resume. Host migration, maintenance, or capacity pressure can turn what would have been a resume into a cold start. Treat suspend as a faster version of stop, not a guaranteed warm restart.
+- A few log lines may be lost across a suspend/resume cycle, and the system clock can take a second or two to re-synchronize after resume. See "[Suspend vs. Stop](/docs/getting-started/troubleshooting/#suspend-vs-stop)" for details on clock skew.
+
+Billing is the same for both: you pay for stopped machines like you pay for suspended ones.
+
+For the rest of this guide, "stop" and "suspend" are interchangeable. The patterns work the same way for both.
+
+## Pattern A: disable autostop, manage shutdown in the app
+
+**Use this when** your app has long-lived workers, in-process job runners, or any background work that the application itself can track.
+
+Turn autostop off in `fly.toml`:
+
+```toml
+[http_service]
+  internal_port = 8080
+  auto_stop_machines = "off"
+  auto_start_machines = true
+```
+
+With autostop off, the proxy never stops your machines for being idle. They stay up until something else stops them (a deploy, `fly machine stop`, or a host migration). You're paying for every machine 24/7, in every region you've scaled into, so make sure that's the right tradeoff before adopting this pattern.
+
+When deploys, manual stops, or host migrations _do_ stop the machine, your app gets `SIGTERM` and has `kill_timeout` seconds to clean up. The default of 5 seconds is almost certainly too short. Bump it. These are top-level keys in `fly.toml`:
+
+```toml
+kill_signal = "SIGTERM"
+kill_timeout = "30s"
+```
+
+The maximum is 300 seconds. `kill_timeout` is a drain window, not a "let the job finish" knob. If your jobs run longer than 5 minutes, either checkpoint them so they can resume, or stop accepting new work and let in-flight jobs drain before the timeout. Don't wait for everything to finish.
+
+A minimal shutdown pattern in Node:
+
+```javascript
+let activeJobs = 0
+let shuttingDown = false
+
+async function runJob(payload) {
+  if (shuttingDown) throw new Error("shutting down")
+  activeJobs++
+  try {
+    await doWork(payload)
+  } finally {
+    activeJobs--
+  }
+}
+
+process.on("SIGTERM", () => {
+  shuttingDown = true
+  const start = Date.now()
+  const deadline = 25_000 // 5s under kill_timeout
+  const tick = setInterval(() => {
+    if (activeJobs === 0 || Date.now() - start > deadline) {
+      clearInterval(tick)
+      process.exit(0)
+    }
+  }, 200)
+})
+```
+
+In Python with asyncio:
+
+```python
+import asyncio, signal
+
+active = 0
+shutting_down = asyncio.Event()
+
+async def run_job(payload):
+    global active
+    if shutting_down.is_set():
+        raise RuntimeError("shutting down")
+    active += 1
+    try:
+        await do_work(payload)
+    finally:
+        active -= 1
+
+async def shutdown():
+    shutting_down.set()
+    try:
+        await asyncio.wait_for(_drain(), timeout=25)
+    except asyncio.TimeoutError:
+        pass
+
+async def _drain():
+    while active > 0:
+        await asyncio.sleep(0.2)
+
+loop = asyncio.get_event_loop()
+loop.add_signal_handler(signal.SIGTERM, lambda: asyncio.create_task(shutdown()))
+```
+
+Both patterns refuse new work as soon as `SIGTERM` arrives, then wait for in-flight jobs up to a deadline a few seconds shorter than `kill_timeout`. The safety margin matters, if you wait the full 30s, Fly's `SIGKILL` arrives before your `exit(0)` runs.
+
+## Pattern B: split web and worker into separate process groups
+
+**Use this when** web traffic is bursty (a good candidate for autostop) but background work is steady or long-running (a bad candidate for autostop).
+
+Split with `processes` in `fly.toml`:
+
+```toml
+[processes]
+  web = "bundle exec puma"
+  worker = "bundle exec sidekiq"
+
+[http_service]
+  internal_port = 8080
+  auto_stop_machines = "suspend"
+  auto_start_machines = true
+  processes = ["web"]
+```
+
+The worker process group has no `[http_service]` attached, so the proxy never touches its machines. Autostop applies only to the web tier.
+
+Scale them independently:
+
+```cmd
+fly scale count web=2 worker=1
+```
+
+This is the pattern Sidekiq, Celery, and BullMQ workers actually want. The web tier scales to zero off-hours; the worker tier runs whenever there's work in the queue.
+
+Tradeoff: you're paying for at least one worker machine continuously. If your work is batchy enough that on-demand workers make sense, use the [work queues guide's on-demand worker pattern](/docs/blueprints/work-queues/) instead, as that spins up a fresh machine per job and lets it stop when done.
+
+## Graceful shutdown: what Fly sends
+
+When something stops your machine, whether that's `auto_stop_machines`, `fly machine stop`, a deploy, or a host migration, Fly sends `kill_signal` (default: `SIGTERM`) to PID 1. After waiting `kill_timeout` seconds, it sends `SIGKILL`.
+
+The defaults are conservative:
+
+| Option | Default | Max | Notes |
+| --- | --- | --- | --- |
+| `kill_signal` | `SIGTERM` | n/a | Also accepts `SIGQUIT`, `SIGUSR1`, `SIGUSR2`, `SIGKILL`, `SIGSTOP` |
+| `kill_timeout` | `5s` | `300s` | The drain window before `SIGKILL` |
+
+Five seconds is enough for an HTTP server to close keepalives. It is not enough for a long-running job to finish. If you have any background work, set `kill_timeout` to a value that allows your typical job to complete. You'll need to determine this on your side. Both keys are top-level in `fly.toml`:
+
+```toml
+kill_signal = "SIGTERM"
+kill_timeout = "30s"
+```
+
+PID 1 receives the signal. In a Docker container running your app directly, that's your process. In a container running a shell wrapper (`CMD ["sh", "-c", "..."]`), the shell is PID 1 and `SIGTERM` doesn't propagate. Use the exec form: `CMD ["myapp"]`, or `exec myapp` inside the wrapper.
+
+`kill_timeout` is not a "finish your work" timer. It's a drain window. Inside it, you should:
+
+1. Stop accepting new work
+1. Let in-flight work finish, or checkpoint it
+1. Exit cleanly
+
+If your jobs take longer than 5 minutes, you can't drain them inside `kill_timeout`. You need either Pattern A with checkpoint/resume, or Pattern B with a worker tier that's never autostopped.
+
+Run `fly config validate --strict` before relying on any of this. By default, `fly config validate` silently accepts unrecognized sections and keys. A typo or outdated section name can pass validation and then do nothing at runtime. Strict mode catches those errors.
+
+## Picking a pattern
+
+| Situation | Pattern |
+| --- | --- |
+| Jobs are short (< 30 seconds) | Increase `kill_timeout`; everything else can stay as default |
+| Long-running jobs, steady web traffic | A: disable autostop, in-app drain |
+| Long-running jobs, bursty web traffic | B: split web/worker processes |
+| Cron-style scheduled jobs | See [task scheduling](/docs/blueprints/task-scheduling/) |
+| Queue-driven workers | B: combine with [work queues](/docs/blueprints/work-queues/) |
+| One-off jobs (fire and forget per request) | On-demand workers; see [work queues](/docs/blueprints/work-queues/) |
+| Can't restructure right now | A: accept the continuous machine cost |
+
+## Common problems
+
+**My `SIGTERM` handler runs but the job still gets killed.** `kill_timeout` is shorter than your handler needs. Bump it (max 300s) and set your handler's deadline a few seconds under that.
+
+**The machine stops mid-job even with `auto_stop_machines = "off"`.** Autostop is only one of several things that stop machines. Deploys, `fly machine stop`, scale-down, and host migrations all do too. Check `fly logs` for the `instance refused` or `host migration` events. Pattern A still applies. The only difference is that autostop is no longer the trigger.
+
+**Why doesn't a self-ping keep my machine alive?** It won't. The [autostop reference](/docs/reference/fly-proxy-autostop-autostart/) defines idle as "a load of 0" but doesn't specify what counts as load. Empirically, sending a successful HTTP request every 60 seconds from a machine to its own `<app>.fly.dev` hostname does not prevent autostop. The proxy still stops the machine after 5 to 10 minutes. To keep a machine running through idle traffic, turn off autostop (Pattern A) or move the work into a process group without `[http_service]` (Pattern B).
+
+**Worker machines won't stop when I deploy.** A process group with no `[http_service]`, such as the worker tier in Pattern B, is invisible to the proxy. Deploys still update those machines because `flyctl` talks to them directly, but the proxy does not manage their lifecycle and cannot autostop them. To stop them gracefully, send a signal with `fly machine stop` or let `fly deploy` replace them during a deployment.
+
+**Suspend resumes are slower than the docs say.** Suspend isn't durable. If Fly can't restore the snapshot (host migration, capacity pressure), you get a cold start. There's no flag to tell you which happened; check the first-request latency. If cold starts matter, run with `min_machines_running = 1`.
+
+## Where to go next
+
+- [Work queues guide](/docs/blueprints/work-queues/): Picking a queue technology
+- [Task scheduling guide](/docs/blueprints/task-scheduling/): cron-style triggers and scheduled machines
+- [Autostart and autostop reference](/docs/reference/fly-proxy-autostop-autostart/): The proxy's full decision logic
+- [Configuration reference](/docs/reference/configuration/): `kill_signal`, `kill_timeout`, `processes`, `auto_stop_machines`
+- [Machine states](/docs/machines/machine-states/):  what `stopping`, `stopped`, and `suspended` actually mean
diff --git a/partials/_guides_nav.html.erb b/partials/_guides_nav.html.erb
index 5837c74f67..429db9d396 100644
--- a/partials/_guides_nav.html.erb
+++ b/partials/_guides_nav.html.erb
@@ -66,6 +66,7 @@
       title: "Background Jobs & Automation",
       open: true,
       links: [
+        { text: "Long-running tasks and machine lifecycle", path: "/docs/blueprints/long-running-tasks/" },
         { text: "Building Infrastructure Automation without Terraform", path: "/docs/blueprints/infra-automation-without-terraform/" },
         { text: "Deferring long-running tasks to a distributed work queue", path: "/docs/blueprints/work-queues/" },
         { text: "Task scheduling guide with Cron Manager and friends", path: "/docs/blueprints/task-scheduling/" },