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Source channel @githubtrending · Post #15055 · Aug 13

#go#open_telemetry#opentelemetry The OpenTelemetry Collector Contrib is a collection of extra components that extend the core OpenTelemetry Collector, helping you collect, process, and export telemetry data like traces, metrics, and logs from your applications. It supports many features such as filtering sensitive data, batching, retries, and custom processing, which improve security, reliability, and performance of your observability pipeline. You can build custom distributions using these components to fit your needs. This helps you monitor complex systems more easily, reduce costs, and maintain flexibility by supporting many data formats and backends without changing your application code. It is maintained by a community of experts ensuring quality and support. https://github.com/open-telemetry/opentelemetry-collector-contrib

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@githubtrending · Post #15271 · 11/05/2025, 12:30 PM

#cplusplus#arm#baidu#deep_learning#embedded#fpga#mali#mdl#mobile#mobile_deep_learning#neural_network Paddle Lite is a lightweight, high-performance deep learning inference framework designed to run AI models efficiently on mobile, embedded, and edge devices. It supports multiple platforms like Android, iOS, Linux, Windows, and macOS, and languages including C++, Java, and Python. You can easily convert models from other frameworks to PaddlePaddle format, optimize them for faster and smaller deployment, and run them with ready-made examples. This helps you deploy AI applications quickly on various devices with low memory use and fast speed, making it ideal for real-time, resource-limited environments. It also supports many hardware accelerators for better performance. https://github.com/PaddlePaddle/Paddle-Lite