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Source channel @githubtrending · Post #14693 · May 10

#jupyter_notebook#a2a#agentic_ai#dapr#dapr_pub_sub#dapr_service_invocation#dapr_sidecar#dapr_workflow#docker#kafka#kubernetes#langmem#mcp#openai#openai_agents_sdk#openai_api#postgresql_database#rabbitmq#rancher_desktop#redis#serverless_containers The Dapr Agentic Cloud Ascent (DACA) design pattern helps you build powerful, scalable AI systems that can handle millions of AI agents working together without crashing. It uses Dapr technology with Kubernetes to efficiently manage many AI agents as lightweight virtual actors, ensuring fast response, reliability, and easy scaling. You can start small using free or low-cost cloud tools and grow to planet-scale systems. The OpenAI Agents SDK is recommended for beginners because it is simple, flexible, and gives you good control to develop AI agents quickly. This approach saves costs, avoids vendor lock-in, and supports resilient, event-driven AI workflows, making it ideal for developers aiming to create advanced, cloud-native AI applications[1][2][3][4]. https://github.com/panaversity/learn-agentic-ai

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@githubtrending · Post #14989 · 07/23/2025, 11:30 AM

#c_lang#bluetooth#bluetooth_le#embedded#embedded_c#iot#mcu#microcontroller#real_time#rtos#zephyr#zephyr_rtos#zephyros Zephyr is a free, open-source real-time operating system (RTOS) designed for small, resource-limited devices like sensors, wearables, and IoT gateways. It supports many hardware types such as ARM, Intel x86, and RISC-V, making it flexible for different projects. Zephyr is modular, so you can include only what you need, saving memory and power. It focuses on security with features like memory protection and secure boot. It also offers built-in networking and tools for easy development and testing. This helps you build reliable, fast, and secure embedded systems efficiently, especially for IoT and real-time applications[1][2][3]. https://github.com/zephyrproject-rtos/zephyr