Desktop and Mobile Apps with Rust and Tauri 2

Class Duration

21 hours of live training delivered over 3-5 days to accommodate your scheduling needs.

Student Prerequisites

Working Rust experience equivalent to Rust Essentials
Comfort with HTML, CSS, and a JavaScript or Rust-based UI framework
Familiarity with the command line and Git

Target Audience

Engineers building cross-platform desktop applications — internal tools, developer tools, AI/LLM workstation apps, on-device productivity software — who want native performance, small binaries, and a tight security model. Also relevant for teams shipping the same app to desktop and mobile, since Tauri 2 supports iOS and Android.

Description

Tauri 2 became stable in October 2024 and is now the production-ready alternative to Electron for cross-platform desktop apps — and a viable mobile target as well. This course teaches engineers to build, ship, and operate small, fast, secure Tauri 2 apps on the Rust 2024 edition (1.85 introduced the edition; 1.95+ recommended for the current toolchain). It covers project setup with the customer's preferred frontend (Leptos, React, Vue, Svelte, or Solid), the Rust backend, the Tauri 2 capability/permission model (ACL), native context menus, file-system and OS interactions, mobile-specific APIs (notifications, dialogs, NFC, biometrics, deep links), and the full distribution story (signed installers, auto-update, App Store and Play Store packaging). Throughout, students use AI coding assistants (Claude Code, Cursor, GitHub Copilot) the way senior Rust engineers actually use them in 2026 — letting Cargo, clippy, and the compiler be the source of truth on the Rust side and AI handle the routine boilerplate.

Learning Outcomes

Stand up a Tauri 2 project with the customer's preferred frontend and a Rust backend.
Define and call backend Rust commands from the frontend with proper argument and error handling.
Use the Tauri 2 capability/ACL model to ship apps that follow least-privilege.
Build native UI affordances: windows, menus, tray icons, native context menus, dialogs, notifications, splash screens.
Connect to the file system, the database, and remote APIs from the Rust side.
Target iOS and Android with the same Tauri 2 codebase, including platform-specific APIs.
Build, sign, and distribute installers across macOS, Windows, Linux, and the mobile stores.
Use AI coding assistants effectively for Tauri 2 development without sacrificing the security model.

Training Materials

All students receive comprehensive courseware covering all topics in the course. Courseware is distributed via GitHub in the form of documentation and extensive code samples. Students practice the topics covered through challenging hands-on lab exercises that build into a complete signed Tauri 2 desktop app capstone, with optional mobile builds.

Software Requirements

A free GitHub account, the latest stable Rust toolchain installed via rustup (Rust 1.95+ on the 2024 edition), Visual Studio Code or another supported editor with the rust-analyzer extension, Node.js 22+ (if a JavaScript frontend is chosen), Docker for the local PostgreSQL instance (if the database lab is included), platform tooling for the chosen target OS (Xcode, Android SDK, etc.), and an AI coding assistant of choice (GitHub Copilot, Cursor, or Claude Code). A cloud-based environment can be provided if local installation is restricted.

Training Topics

Tauri 2 in 2026

What changed in Tauri 2: stable since October 2024, mobile support, ACL-based capabilities, native context menus
Tauri 2 vs. Electron, Qt, .NET MAUI, and Flutter
The architecture: Rust backend, native webview frontend
Why Tauri produces dramatically smaller and faster binaries than Electron
The roadmap and ecosystem in 2026

Getting Started

Creating a Tauri 2 project
Choosing the frontend: Leptos, React, Vue, Svelte, or Solid
Project structure, tauri.conf.json, and capability files
Running and debugging Tauri 2 apps

Frontend ↔ Backend Communication

Defining Rust commands with #[tauri::command]
Calling commands from the frontend with invoke
Argument and return-type conversions
Error handling across the boundary
Async commands and long-running tasks

App Architecture and State

The App, AppHandle, and Window APIs
Managed state with tauri::State
Event-driven communication: emit and listen
Multi-window apps and inter-window messaging

Native UI Elements

Windows, sizing, and platform-specific behavior
Application menus and per-window menus
Native context menus (powered by muda)
Tray icons with menus and actions
Splash screens
Native dialogs and notifications

Capabilities and the Permission Model (ACL)

Why ACL replaces the v1 allowlist
Defining capabilities for windows and contexts
Plugin permissions and scoping
Threat model: what a compromised webview can and cannot do
Auditing AI-generated capability files before shipping

Operating-System Integration

File system: pickers, watchers, paths, and permissions
Clipboard, deep links, and protocol handlers
Shell and process integration
Auto-launch and background services
The Tauri plugin ecosystem (notification, dialog, fs, store, sql, http, updater, …)

Mobile (iOS and Android)

Setting up mobile targets
Mobile-specific plugins: notifications, dialogs, NFC, barcode reading, biometric auth, clipboard, deep links
Platform-specific Rust code with #[cfg(...)]
Building, signing, and submitting to the App Store and Play Store

Database and Network

Connecting to PostgreSQL with sqlx (or SQLite for embedded use)
Calling REST APIs with reqwest
Caching and offline-first patterns
Background sync and push

Building and Distributing

Platform-specific installers: .dmg, .msi, .AppImage, .deb, .rpm
Code signing on macOS and Windows
Auto-update with the updater plugin
Cross-platform CI/CD with GitHub Actions
Mobile distribution via the App Store and Play Store

AI-Assisted Tauri 2 Development

Where AI assistants help on Tauri 2 boilerplate (commands, plugins, frontend bindings) and where they don't (capability files, security boundaries)
Prompts that work well for Tauri 2 plugin authoring and command design
Letting the compiler, clippy, and tests catch what AI gets wrong
Reviewing AI-generated capability files before shipping
Agentic Rust workflows for Tauri 2: AI-assisted refactors, code review, and CI

Capstone

Build and ship a small Tauri 2 desktop app: a Rust backend with a chosen frontend, a sensible capability file, native menus, file-system integration, a database, signed installers for at least two platforms, and optionally a mobile build — built with AI assistance and validated by the compiler, clippy, and tests
Course wrap-up and recommended next courses