$ show hongbo-miao/hongbomiao.com
This repository is a comprehensive personal R&D platform implementing a polyglot microservices architecture. It hosts a personal website/web application (React/Vite), multiple API servers in different languages (Rust/Axum, Go/Gin/gRPC, Python/FastAPI, Node.js/Express), mobile applications (iOS/Android/React Native), and desktop applications (Qt). The platform includes extensive data processing infrastructure (Kafka, Pulsar, NATS, Spark, Flink), machine learning capabilities (model training/serving/fine-tuning), monitoring and observability tools, and infrastructure as code (Terraform/OpenTofu, Kubernetes). Services communicate via messaging systems and APIs, with a clear separation of concerns and standardized patterns for configuration, health checks, logging, and error handling across language implementations.
The LLM identified 5 files worth highlighting for reuse:
Implements a robust configuration management pattern using once_cell for lazy initialization with environment variable fallback. Demonstrates Rust-specific idioms for safe, efficient configuration loading that could be extracted as a reusable library with minimal dependencies (primarily once_cell and std::env).
Provides a standardized health check utility with liveness and readiness probes following industry best practices. The component is isolated (imports only standard library and psutil), demonstrates consistent error handling, and could be easily extracted for use in other Python services with minimal modification.
Implements a variance-weighted distance fusion algorithm for sensor data with clear mathematical encapsulation. The function is self-contained (imports only nalgebra for vector operations), demonstrates domain-specific expertise in sensor fusion, and could be reused in any robotics or autonomous systems project requiring similar fusion logic.
Shows a robust telemetry message validation pattern with comprehensive error handling and type checking. While it imports generated protobuf classes, the validation logic itself is reusable and demonstrates good practices for stream processing systems that could be adapted to different message schemas with minimal changes.
Implements a standardized logging initialization pattern using zerolog with consistent formatting and output configuration. The component is isolated (imports only standard logging libraries), demonstrates good practices for production-ready logging, and could be extracted as a reusable Go logging module with minimal dependencies.