"Operate PyCaret's self-hosted platform deployment, configuration,
Scanned 9/8/2026
Install to Claude Code
npx -y skills add VectorSpaceLab/AREX-Skill --skill platform-operations --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Platform Operations?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/vectorspacelab-platform-operations)More formats (shields.io, HTML) on the badges page.
---
name: platform-operations
description: "Operate PyCaret's self-hosted platform deployment, configuration,
storage, queues, workers, backups, and runtime health checks."
disable-model-invocation: true
metadata:
disco-role: operating
license: NOASSERTION
---
# Platform Operations
Use this sub-skill when the task is about running or operating the PyCaret
Control Plane rather than changing engine code or web source. It covers local
single-process installs, Docker Compose deployments, production-shaped
Postgres/Redis/MinIO deployments, secrets persistence, object storage,
backup/restore, migrations, worker queues, optional GPU workers, and platform
health checks.
## Route first
1. Identify the install shape:
- single-process `pycaret-server` process,
- compact Docker Compose (`api` + `web`, SQLite/local artifacts),
- production-shaped Compose (`api` + `worker` + Postgres + Redis + MinIO),
- Kubernetes/Helm or cloud/Terraform target.
2. Load the matching reference:
- [deployment modes](references/deployment-modes.md) for services, ports, and start/stop commands.
- [configuration and secrets](references/configuration-and-secrets.md) for `PYCARET_*` settings and Fernet/JWT handling.
- [backup, restore, and upgrade](references/backup-restore-and-upgrade.md) before touching state, migrations, or images.
- [GPU workers and queues](references/gpu-workers-and-queues.md) for `default`, `cpu-heavy`, `gpu`, and `inference` worker routing.
- [troubleshooting](references/troubleshooting.md) when a platform surface is stuck or unhealthy.
3. Prefer bundled, non-secret checks before destructive actions:
- `python scripts/ops_doctor.py`
- `bash scripts/check_container_secret_key.sh --data-dir ./data`
4. State clearly when a surface is documented as a future or stub target. Do
not present Helm or Terraform as production-complete without verifying the
actual chart/module templates in the user's distribution.
## Common commands
```bash
# Bootstrap and run a direct server install.
pycaret-server init --data-dir ./data
pycaret-server migrate
pycaret-server serve --host 0.0.0.0 --port 8020
pycaret-server doctor
# Compact Docker Compose from a source distribution.
docker compose up --build
docker compose logs -f api
docker compose down # preserves named volumes
docker compose down --volumes # wipes data volumes
# Production-shaped Compose from a source distribution.
docker compose -f infra/docker/docker-compose.prod.yml up --build
# Redis worker process.
PYCARET_RUNS_BACKEND=redis pycaret-server worker --queues default,cpu-heavy --worker-id worker-1
```
## Boundaries
Route elsewhere for:
- Engine experiment/task API, model lists, `RunConfig`, and `pycaret` library use → `engine-workflows`.
- Editing React/Vite source, routes, or components → `web-ui`.
- Contributor Python style, package tests, release notes, and code changes → `repo-development`.
Keep operations guidance self-contained. Do not rely on a local checkout path,
private environment prefix, or secret value. Never print JWT secrets, Fernet
keys, storage credentials, SMTP passwords, or connection passwords.
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!