microservice-rust-mysql

of Linux containers) and fast (native GPU) AI inference apps for Tensorflow Lite models. https://wasmedge.org/docs/develop/rust/ai_inference/tensorfl... WasmEdge’s PyTorch plugin enables lightweight (1/10 of Linux containers) and fast (native GPU) AI inference apps for PyTorch models. https://wasmedge.org/docs/develop/rust/ai_inference/pytorch/ Through the new WasmEdge plugin system, the community are adding support for libraries like zlib, OpenCV, tesseract and ffmpeg etc. Putting these together, we are supporting complex AI libraries such as Mediapipe on WasmEdge! https://github.com/yanghaku/mediapipe-rs The Mediapipe story is esp interesting since WasmEdge is now adapted as a runtime for stream data process in products like Fluvio, Redpanda, YoMo, RisingWave and others. Mediapipe support allows developers to add AI into the stream data pipeline. https://github.com/xxchan/fluvio/pull/1 WasmEdge’s eBPF plugin enables developers to create secure and containerized eBPF tools and controllers in Kubernetes environments. https://github.com/WasmEdge/WasmEdge/tree/master/plugins/was... A good example of WasmEdge 0.12.1 WASI enhancement is the ability to limit the Wasm app to read-only access to files and folders. WasmEdge sockets API is refactored in 0.12.1 to be compatible with the much more limited WASI socket proposal. WasmEdge sockets have become a super set of WASI sockets. The WasmEdge networking sockets got new features in version 0.12.1, such as DNS, network device binding and TLS. You will be able to create sophisticated microservices that require highly-efficient non-blocking network sockets. https://github.com/second-state/wasmedge_wasi_socket Here are several complex networking applications possible with WasmEdge sockets. https://github.com/second-state/microservice-rust-mysql https://github.com/WasmEdge/wasmedge-db-examples https://github.com/WasmEdge/wasmedge_hyper_demo WasmEdge is already one of the smallest and most efficient Wasm runtimes out there. It embeds into libsql (SQLite on the server!) to execute user definited functions to perform complex tasks like HTTPS web services & AI inference from SQL statements! https://wasmedge.org/docs/embed/use-case/libsql/ The WasmEdge C++ and Rust SDKs allow host applications to embed Wasm functions asynchronously. It is critically important in many applications where the embedded Wasm function is simply not allowed to block the execution of the host applications. https://github.com/second-state/wasmedge-rustsdk-examples/bl... Asynchronous host SDKs are complex and a lot of work still remains. We are continuously improving it with our end user and partner communities. Preview: https://github.com/L-jasmine/WasmEdge/tree/feat/async What's coming next? * Support plugins in our Docker and k8s integrations * Wasm GC support for languages like Kotlin and Dart * WASI thread * Stack switching for coroutines * Component model * Support for inference on open source LLMs * Better JS & Python support for AI

the microservice itself. It provides a lightweight yet very fast web server to handle JSON over HTTP requests. It is based on the popular Rust tokio, hyper, and serde libraries. See more examples: https://github.com/WasmEdge/wasmedge_hyper_demo The microservice also features an async MySQL client to interact with backend databases. Even more examples: https://github.com/WasmEdge/wasmedge-db-examples This WasmEdge-based microservice utilizes high-performance non-blocking networking on both the HTTP service & the database client. It is a faster, lighter & more secure alt to Linux container-based microservices.