Building a Plugin System With WebAssembly Sandboxing
Safely run third-party untrusted code inside your Node.js or browser application using WebAssembly memory sandboxing.
26 articles tagged with WebAssembly
Safely run third-party untrusted code inside your Node.js or browser application using WebAssembly memory sandboxing.
Learn how WASI (WebAssembly System Interface) brings secure, sandboxed Wasm execution to serverless backends, edge runtimes, and local CLI tools.
Conflict-free Replicated Data Types (CRDTs) are notoriously memory-hungry. Learn how Loro, built in Rust, optimizes client-side state sync for real-time multiplayer apps.
Ditch WebGL shaders. Learn how to configure WebGPU bindings inside background Web Workers for high-throughput, hardware-accelerated browser neural networks.
Should you compile your application logic to run inside client runtimes (Wasm) or stream rendering from edge servers (RSC)? Learn the performance trade-offs of both options.
Flutter Web has historically been criticized for high bundle sizes and poor SEO. Discover how WebAssembly (Wasm) compilation and edge rendering overlays solve these challenges.
Allowing users to write custom plugins historically meant running risky JS eval sandboxes or full virtual machines. Learn how Wasm runtimes make extensibility safe and fast.
LLMs that write and execute code are powerful — and dangerous. Learn how WASM Component Model, WASI preview 2, and Wasmtime turn Node.js into a fortress for autonomous agent code execution.
Learn how to optimize browser-native LLM execution. Compile heavy HuggingFace tokenizers from Rust to WebAssembly to eliminate pre-processing bottlenecks in WebGPU pipelines.
Learn how to build a high-performance, multitrack real-time audio mixer using the Web Audio API and custom AudioWorkletProcessor threads.
Learn how to build a client-side execution sandbox using WebAssembly. Run untrusted Python code securely inside browser Web Workers with Pyodide and virtual filesystems.
Learn how to program WebGPU compute shaders using WGSL. Write a high-performance matrix multiplication (MatMul) kernel from scratch using workgroups and local memory.