Quant Cloud

Quant Cloud runs bulk forward jobs on dedicated cloud runners that keep going while your workstation is off or QuantCraft is closed. Each runner runs one bulk forward job at a time, so you configure and monitor a batch per runner. The desktop app connects to runners provisioned for your account after you sign in — it does not use your local Python service for these jobs.

This is the cloud counterpart of Auto Trading, which runs the same kind of batch on your local machine. This page covers what you do in the app; server setup and operations are outside the scope of this documentation.

The Quant Cloud page and nav entry appear when the Quant Cloud feature is enabled for your build.

---

Buying a cloud runner

Click Buy Cloud Runner and:

1. Pick a machine tier — each card shows the tier name, price ($X/mo), instance type, and a short description.
2. Continue to checkout, which shows an order summary and PayPal subscription buttons. Payment is a PayPal subscription; the app does not collect card details directly.
3. After approval the runner is provisioned and appears on the page within a few minutes — use Refresh runners to check.

You need an active QuantCraft subscription that includes Quant Cloud (see your plan).

---

Runner cards

Each runner shows a status — Warmup, Running, Loading…, Unavailable, or Ready — with its label and endpoint. Newly provisioned runners show a warmup banner (with time remaining) that temporarily blocks bulk runs, dependency installs, and refresh.

Actions on a runner: Dependencies, New bulk run (or Edit / Stop / Delete / Resume when a job exists), and Refresh. A collapsible footer shows the installed Packages and the latest install log.

---

Installing dependencies

Click Dependencies on a runner to install PyPI packages (the runner uses the same Python as bulk/forward algos, not your local IDE .venv). If your algo imports packages beyond the defaults (for example pandas, numpy), add them here:

• Enter comma-separated package names (e.g. pandas, numpy, backtrader).
• Click Install to watch a live install log; the runner restarts after a successful install so the new packages import (this can take up to a minute).
• Installs are blocked while a bulk job is running (stop it first) and during warmup.
• Installed packages appear as color-coded badges (e.g. pandas 2.1.0) in the Packages panel.

Install the same libraries you use in the IDE under Packages (Dependencies) when those packages are required at runtime.

---

Running a batch on a runner

• On an idle runner, click New bulk run. This opens the same New Run modal as Auto Trading — see Auto Trading for the Algorithm / Targets / Schedule & data tabs — bound to that runner.
• Choose your compiled algo (.qcraft.json), target symbols or scope, period/timeframe, and optional script parameters. Set timerIntervalMs if your strategy defines on_timer (Strategy lifecycle).
• One job per runner: once a job exists you'll see Edit run, Stop bulk run, Delete run, and Resume bulk run instead of New. Resume bulk run is for jobs in pending resume and requires an active trading account.
• The runner's bulk section shows Details and Logs (same layout as the local bulk card), with Pause / Resume (pauses or resumes the live log tail only — it does not pause the job), Refresh, Download logs (CSV), and Clear logs.

You can Load / Save at the top of the modal to reuse a run preset (.qcs). When editing an existing bulk run, the algorithm (algoId) is fixed — Load updates targets, timer, tick mode, and params but does not swap the algo file.

---

Logs

Each bulk forward run streams stdout, stderr, and status events to the runner's Logs tab in Quant Cloud:

Older lines may be dropped when log volume is high. Use Refresh if you suspect you are only seeing a tail of the full history. Deleting a bulk run removes that job's stored log file on the runner, and logs for an abandoned job may be purged after about 7 days.

---

Monitoring and stopping

• Bulk status polls about every 5 seconds while you're on the Quant Cloud page.
• Stop bulk run and Delete bulk forward run each ask for confirmation; delete clears the saved state on the runner and removes the job from the list.

---

Tips

• Match IDE and runner packages — if Test passes locally but the cloud run fails on ImportError, add the missing package via Dependencies.
• on_timer is for forward runs — the IDE backtest dialog does not configure timers; set timerIntervalMs in the bulk forward modal instead.
• on_tick on forward runs — fires on every broker price update from Alpaca while the algo runs; see Strategy lifecycle.
• Alpaca credentials — bulk jobs that trade live or paper may require broker credentials submitted per run; follow the modal prompts for your account type.
• Workspace folder — saving .qcs presets requires a linked workspace folder.

---

See also

• Auto Trading — local forward runs and the shared New Run modal
• Run presets (.qcs) — save and load run configurations