F-Layer

Deploy cloud servers, manage their resources and check availability from Python or the command line.

F-Layer turns a deployment configuration into cloud resources and keeps a local record of what it created. That record lets you inspect the deployment, recover an interrupted operation, and remove the resources belonging to your stack. Use it to automate a service environment or give your application a reusable infrastructure backend instead of maintaining separate provisioning scripts.

The current release supports Yandex Cloud, a secure SSH gateway with per-device connection settings, and HTTP availability and timing checks. Other clouds and VPN profiles are roadmap work. Cloud resources are billed by your provider; F-Layer is open source under Apache 2.0.

Documentation · Quick Start · First deployment · API reference · Changelog · Releases

Quick Start

Use Python 3.11 or newer. Install the stable release in a virtual environment:

git clone https://github.com/Fuzzy-Technologies/F-Layer.git
cd F-Layer
git checkout v1.2.1
python -m venv .venv

Activate it with source .venv/bin/activate on Linux/macOS, .venv\Scripts\Activate.ps1 in PowerShell, or .venv\Scripts\activate.bat in Windows Command Prompt. Then run:

python -m pip install .
python -m flayer --help
python -m flayer check --format json

Expected result: the local check reports "status": "ok" and exits with 0. It checks Python and package availability without cloud credentials or network access. This is a working first check, not a server deployment.

Next, follow the Quick Start to try an endpoint check, or the gateway walkthrough to prepare a server plan and deploy it with explicit provider access.

What you can build

• A managed cloud environment: create, inspect, recover and destroy an owned stack through the same configuration and state file.
• A controlled SSH gateway: prepare server configuration and per-device SSH local forwards to explicitly allowed destinations.
• Operational checks: test an HTTP endpoint and measure bounded response and transfer timings, with JSON reports for automation.
• Application integrations: reuse the Python configuration, provider and lifecycle APIs in your own tools.

See the architecture for how these parts fit together. Stable releases are tagged on master; the changelog records their scope. develop also contains accepted work for later releases.

Contributing

Read AGENTS.md and DEVELOPMENT_PROTOCOL.md. Build the installed-wheel API documentation with python tools/build_api_reference.py; see documentation setup.

Release workflow · Apache License 2.0