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· 3 min read

Defang Compose Update

August was about making migrations smoother and showing how you can already use Defang to deploy agentic apps at scale. We expanded our sample projects for popular multi-agent frameworks like CrewAI, LangGraph, Autogen, and Strands, validating them on Playground, AWS, and GCP so you can run multi-agent workloads in production without extra DevOps. Our new Heroku migration flow inspects dynos and add-ons, generates a clean Compose file, provisions managed equivalents like Postgres and Redis, and ships to your own cloud in one command. This cuts costs and removes lock-in. We also introduced MCP BYOC prompts so you can deploy to AWS and GCP straight from your IDE. Railpack on GCP now delivers faster, more reliable no-Dockerfile builds with clearer logs and closer parity with AWS.

Heroku Migration​

As more and more teams are moving away from legacy PaaS solutions, looking for more flexibility and more control, we’ve made it easier for teams to move off Heroku. Defang now supports deployments without a Dockerfile and Defang will even generate a compose file from your Heroku application. The result is a smoother path to AWS or GCP with more features, lower costs, and no lock-in.

Agentic Applications​

We expanded and refined our sample projects for agentic frameworks like CrewAI, LangGraph, Autogen, and Strands, validating across Playground, AWS, and GCP for a seamless move to production. Agentic applications demand more than code. They need scalable compute, managed databases and caches, security, orchestration, and LLM integrations. That’s why Defang automates all the heavy lifting. When you define your app once in Docker Compose, Defang handles provisioning on AWS or GCP including compute, managed Postgres or MongoDB, Redis, LLM services, security, auto scaling, and compliance so you can focus purely on your agents.

MCP BYOC Prompts​

We now support deploying to AWS and GCP through the Defang MCP Server using prompts in your IDE. This keeps your workflow fast and frictionless, letting you go from code to cloud in seconds without breaking focus. You can stay in the flow with no context switching, spinning up services or scaling workloads simply by chatting in your editor. It means faster iteration, shorter feedback loops, and less time wrestling with terminals or cloud consoles.

note

Requires Defang CLI v2.1.3 or later.

Railpack GCP​

Railpack now works more smoothly on GCP with fixes to image builds, provider consistency, and a redesigned repo. You’ll see faster first builds and rebuilds with better caching, clearer logs when something fails, and closer parity with AWS so templates behave the same across clouds. Railpack also auto-detects common stacks when no Dockerfile is present, applies sensible defaults for runtime, ports, and health checks, and produces clean OCI images for Playground or your own cloud. Net result: you can ship no-Dockerfile apps across clouds with less setup and fewer surprises.

Events and Community​

In August, one of our campus advocates, Swapnendu Banerjee, hosted a session that showed how quickly you can deploy real apps to the cloud with Defang. Looking ahead, we’ll be at the ALL IN conference in Montreal this month and would love to connect if you’re a Defang user or planning to attend.

We are excited to see what you will deploy with Defang next. Join our Discord to ask questions, get support, and share your builds with the community.

More coming in September.

· 3 min read

Defang Compose Update

July was all about making cloud deployments even smoother and smarter. We focused on removing friction from deployments and giving you better visibility into costs. Railpack now builds production-ready images automatically when no Dockerfile is present, and our real-time cost estimation feature now supports Google Cloud alongside AWS. We also added managed MongoDB on GCP, introduced an Agentic LangGraph sample, and connected with builders at Bière & Code & Beer MTL. Here’s what’s new.

Railpack Integration​

We’ve integrated Railpack into Defang to make deployments even smoother. Railpack automatically builds OCI-compliant images from your source code with minimal configuration. This helps eliminate one of the most common issues our users face: missing or invalid Dockerfiles, especially when they’re generated by LLMs or created by users with limited Docker experience. Now, if no Dockerfile is provided, Defang will seamlessly use Railpack to build a working image for you, so you can focus on your code, not your container setup.

GCP Cost Estimation​

In June, Defang announced real-time cost estimation for AWS. In July, we took our live cloud cost estimation to the next level by extending support to GCP. Defang now makes it easy to compare real-time pricing for both cloud providers. All you need is your project's compose.yaml file. Whether you’re optimizing for cost, performance, or flexibility, Defang makes it easy to get the information you need to deploy with confidence.

Managed MongoDB on GCP​

Defang now supports managed MongoDB on GCP through MongoDB-compatible APIs provided by Google Cloud. This integration allows you to spin up a fully managed Firestore datastore and interact with it just like a standard MongoDB instance without any manual setup or configuration.

Agentic LangGraph Sample​

We have published a new Agentic LangGraph sample project that demonstrates LangGraph agent deployment with Defang. As AI agent development grows, Defang makes it simple to deploy and scale agents, including those built with LangChain or LangGraph. You can explore the example to see how it works in practice.

Events and Community​

In July, we hosted the Bière & Code & Beer MTL during Startupfest in Montreal. It was an incredible evening with great energy, tech conversations, and the chance to connect with so many talented builders over drinks.

We are excited to see what you will deploy with Defang next. Join our Discord to ask questions, get support, and share your builds with the community.

More coming in August.