Defang
¿Qué es Defang?
Defang es una plataforma de desarrollo de aplicaciones en la nube que simplifica el proceso de desarrollar, implementar y depurar aplicaciones en la nube listas para producción. Permite a los usuarios realizar una transición rápida de Docker Compose a implementaciones en la nube seguras.
¿Cómo usar Defang?
Para utilizar Defang, empieza por seleccionar un proyecto de muestra o proporcionando una descripción en lenguaje natural de tu aplicación. Defang luego genera el esquema del proyecto y permite la implementación con un solo comando.
Características principales de Defang
Desarrollar aplicaciones en la nube a partir de indicaciones en lenguaje natural
Implementación rápida con un solo comando
Depuración asistida por IA para una resolución de problemas más rápida
Casos de uso de Defang
Implementar aplicaciones de forma segura en AWS en minutos
Transformar aplicaciones de Docker Compose en implementaciones listas para producción
FAQ de Defang
¿Qué lenguajes de programación soporta Defang?
¿Es Defang adecuado para principiantes?
Defang Reddit
Aquí está el Reddit de Defang: https://www.reddit.com/r/DefangLabs/
Defang Correo electrónico de soporte, contacto de servicio al cliente, contacto de reembolso, etc.
Más contacto, visite la página de contacto(Contact)
Defang empresa
Defang Nombre de la empresa: Defang .
Más información sobre Defang, visite la página acerca de nosotros(https://defang.io/about/) .
Precios de Defang
Enlace de precios de Defang: https://defang.io/pricing/
Youtube de Defang
Enlace de Youtube de Defang: https://www.youtube.com/@DefangLabs
Linkedin de Defang
Enlace de Linkedin de Defang: https://www.linkedin.com/company/defanglabs/
Twitter de Defang
Enlace de Twitter de Defang: https://twitter.com/DefangLabs
Reddit de Defang
Enlace de Reddit de Defang: https://www.reddit.com/r/DefangLabs/
Github de Defang
Enlace de Github de Defang: https://github.com/DefangLabs
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Defang in Codespaces, DevContainers, and GitPod. Deploy to AWS from your cloud IDE!
🚀 Supercharge your development workflow with Defang on GitHub Codespaces and Gitpod! 💻 In this video, we'll show you how to set up Defang, the easiest way for developers to deploy containerized applications to AWS, in both GitHub Codespaces and Gitpod. Whether you want to share configurations with your team, work on projects without local hardware limitations, or try something new without cluttering your machine, these cloud development environments have you covered. *We'll walk you through:* * Setting up a GitHub Codespace with Defang pre-installed * Logging into Defang from within a GitHub Codespace * Adding Defang to your devcontainer spec for use with VS Code, JetBrains IDEs, and more * Creating a Gitpod workspace with Defang using a custom Dockerfile and gitpod.yaml * Logging into Defang from within a Gitpod workspace *Resources:* 🐙 GitHub Codespace project with Defang pre-installed: https://github.com/defang-io/github-codespace 📦 Gitpod workspace with Defang: https://github.com/defang-io/gitpod-workspace 🚀 Get started with Defang: https://docs.defang.io/docs/getting-started ⬇️ Download Defang: https://github.com/defang-io/defang/releases 🐙🐱 Defang GitHub: https://github.com/defang-io/defang *Timestamps:* 00:00 - Intro 00:40 - GitHub Codespaces 1:55 - DevContainers 2:30 - GitPod Subscribe for more tutorials on simplifying your cloud development workflow! #Defang #AWS #CloudDevelopment #GitHubCodespaces #Gitpod #DevContainers #CloudDeployment #ContainerizedApplications
Getting started with Defang: deploying a cloud application in under 5 minutes
Welcome to Defang! 🚀 In this video, we’ll introduce you to the Defang Opinionated Platform, a radically simpler way to build, deploy, and optimize production-ready cloud apps. If you've been looking for a straightforward approach to launch your applications in the cloud, you've come to the right place. 👩💻 What We Cover: * Setting up the Defang CLI * Using the 'defang generate' command to create a chat room app with Express and Socket.IO using our AI-driven template generator * Customizing the generated code to suit your needs * Deploying your app in the cloud with 'defang compose up' 💡 Why Defang? Our AI-assisted platform helps you get started swiftly, offering templates and a guided setup while providing you full control over your code. With Defang, what used to take hours, setting up all the appropriate resources in an AWS or other cloud account, now takes minutes, freeing you up to focus on what matters most: building amazing applications. 📘 Resources: * Defang CLI setup guide: https://docs.defang.io/docs/getting-s... * Defang Portal: https://portal.defang.dev/ * Full documentation: https://docs.defang.io/ 🙌 Join Our Community: Be a part of a growing community of developers who choose Defang for its simplicity and power. Visit https://defang.io/ to learn more about how we can support your development needs. ✅ Subscribe for more tutorials, updates, and tips on making cloud app deployment a breeze. Don't forget to like and subscribe if you find this tutorial helpful. Drop your questions and feedback in the comments below, and we'll be sure to get back to you. Happy coding! 🖥️💻 #Defang #CloudDeployment #AppDevelopment #SoftwareTutorial #TechTutorial #CloudComputing #NodeJS #ExpressApp #SocketIO #AI #Programming #DeveloperTools #CloudServices
The fastest way to deploy Mistral to AWS with GPUs?
Ever wondered how to deploy a GPU-powered application like the Mistral LLM on AWS? How about how do do it *easily* 🚀 In this walkthrough, we'll introduce you to Defang BYOC, a game-changer for developers looking to simplify the process of deploying apps to their AWS accounts. We'll show you how to deploy Mistral using vLLM with a GPU instance, along with a NextJS front-end, all running on AWS ECS. This step-by-step guide covers everything from setting up the AWS and Defang CLIs to understanding the details of our sample docker-compose file and making sure your configuration is GPU-ready. *What You'll Learn* * Setting up AWS and Defang CLI for deployment * Understanding docker-compose files for GPU applications with Defang * Deploying the Mistral LLM using vLLM on AWS with a GPU * Using the Defang CLI to securely store a HuggingFace token in AWS * Using NextJS and the OpenAI SDK for a dynamic user interface *Resources* 🔧 Everything discussed is available in our git repo to get started ASAP: https://github.com/defang-io/defang/tree/main/samples/other/vllm 🚀 Get started with Defang: https://docs.defang.io/docs/getting-started ⬇️ Download Defang: https://github.com/defang-io/defang/releases 🐙🐱 Defang GitHub: https://github.com/defang-io/defang *Timestamps* 0:00 - Introduction 1:24 - Getting Started with AWS CLI and Defang CLI 2:37 - Checking out the Compose File 3:48 - GPU Spot Instance Quotas 4:25 - Back to the Compose File 4:38 - HuggingFace Token 5:25 - The Interface 7:49 - Configuring the Bot 9:29 - Deploy to Your Own AWS Account with Defang 11:04 - Domains 12:07 - ECS Clusters and Config 13:05 - Route53 14:08 - Conclusion Subscribe for more tutorials on deploying to the cloud! #Defang #AWS #GPU #CloudDeployment #NextJS #OpenAI #LLM #HuggingFace #CloudComputing #mistral #vllm #ai #chatbot
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