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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 #15303 · 12/04/2025, 07:00 PM

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#ruby#hotwire#kanban#rails#ruby Fizzy is an open-source Kanban tool by 37signals that helps you visually track tasks and ideas using boards with columns. You can set it up easily, run it locally or with MySQL, and test it with built-in commands. It supports email previews and web push notifications for updates. Fizzy is designed to be simple, modern, and customizable, letting you self-host for full control over your data. It also offers a companion SaaS gem for billing and production setups. This means you get a flexible, transparent way to manage projects and workflows, with the option to run it yourself or use a hosted service. https://github.com/basecamp/fizzy

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