Personally, I found that Defang makes deployment so much easier for me! There is a lot of value in being able to get an app up and running without the hassle of ClickOps. Highly recommend :)
Defang.io is a powerful tool that brings simplicity and speed to cloud deployments, especially for teams working with Docker Compose. Its streamlined CLI makes deploying to cloud platforms like AWS and Google Cloud straightforward, which is a huge advantage for developers looking to quickly prototype and test new ideas.
What sets Defang.io apart is how seamlessly it integrates into the workflow, reducing the usual friction associated with scaling prototypes into full-fledged cloud environments. With its certifications and solid backing from major cloud providers, it’s clear that reliability and performance are top priorities. If you’re a developer or a team looking to iterate quickly without compromising on deployment quality, Defang.io is worth exploring.
I love the simplicity of a nice `compose.yml` file and `docker compose up`, but it's really only for development environments. Defang beautifully bridges that gap, giving me `compose up` for production! It doesn't have to be complicated :)
Hello Product Hunt! I am Lio Lunesu, co‑founder and CTO of Defang.
Defang is your AI DevOps Agent that deploys any app to any cloud in a single step.
Since 2010 I’ve been building cloud infrastructure for startups and enterprise teams and noticed a recurring challenge: deploying production-quality apps across the cloud is unnecessarily complex. That inspired the development of Defang v2, now packed with features to simplify deployments, including Railpack integration, chat-driven IDE deployments, and transparent cost estimation.
With Railpack you no longer need a Dockerfile (but you can continue use a Dockerfile if you want). This feature lowers the barrier to entry significantly while preserving flexibility for advanced users.
Inside supported editors like VS Code, Cursor, Windsurf, Kiro or Claude Desktop, you can connect the Defang MCP Server, enabling your AI coding agent (e.g. Copilot) to access Defang tools and resources to perform tasks such as deploying a service to the cloud. Once the connection is in place, simply typing “deploy with defang” in the IDE’s AI chat will trigger your application deployment.
$ defang mcp setup --client=vscode
Defang also includes a real-time estimation feature for AWS and GCP. Before deployment, you can run the “estimate” tool via CLI to preview costs for different deployment configurations. You can choose from deployment modes Affordable, Balanced, or High_Availability based on your needs. This cost visibility feature helps you plan and decide before committing to a deployment.
We built these features so deploying a cloud app is simple, flexible, and production-ready. Railpack support removes the need for a Dockerfile by deploying from your code and a Compose file. MCP-powered chat in IDEs like VS Code, Cursor, Windsurf, or Claude Desktop allows you to deploy by typing “deploy” in chat. If anything goes wrong, our AI debugger scans logs and offers fixes automatically.
We are eager to hear your feedback. Join us in Discord or share your thoughts here. Thank you for taking the time to check out Defang v2. We can’t wait to see what you build next 💙
Defang
Hello Product Hunt! I am Lio Lunesu, co‑founder and CTO of Defang.
Defang is your AI DevOps Agent that deploys any app to any cloud in a single step.
Since 2010 I’ve been building cloud infrastructure for startups and enterprise teams and noticed a recurring challenge: deploying production-quality apps across the cloud is unnecessarily complex. That inspired the development of Defang v2, now packed with features to simplify deployments, including Railpack integration, chat-driven IDE deployments, and transparent cost estimation.
With Railpack you no longer need a Dockerfile (but you can continue use a Dockerfile if you want). This feature lowers the barrier to entry significantly while preserving flexibility for advanced users.
Inside supported editors like VS Code, Cursor, Windsurf, Kiro or Claude Desktop, you can connect the Defang MCP Server, enabling your AI coding agent (e.g. Copilot) to access Defang tools and resources to perform tasks such as deploying a service to the cloud. Once the connection is in place, simply typing “deploy with defang” in the IDE’s AI chat will trigger your application deployment.
Defang also includes a real-time estimation feature for AWS and GCP. Before deployment, you can run the “estimate” tool via CLI to preview costs for different deployment configurations. You can choose from deployment modes Affordable, Balanced, or High_Availability based on your needs. This cost visibility feature helps you plan and decide before committing to a deployment.
If you’re curious how the whole system fits together, check out https://defang.io/#how-it-works
We built these features so deploying a cloud app is simple, flexible, and production-ready. Railpack support removes the need for a Dockerfile by deploying from your code and a Compose file. MCP-powered chat in IDEs like VS Code, Cursor, Windsurf, or Claude Desktop allows you to deploy by typing “deploy” in chat. If anything goes wrong, our AI debugger scans logs and offers fixes automatically.
We are eager to hear your feedback. Join us in Discord or share your thoughts here. Thank you for taking the time to check out Defang v2. We can’t wait to see what you build next 💙
Defang MCP is insane ⚡
This looks awesome, will try it out! Congrats on the launch!