2 posts tagged with "Agentic Apps"

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.

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.

Deploying Agentic Apps to the Cloud Shouldn’t Be This Hard…​

Agentic apps are redefining how software is built: multi-agent workflows, persistent memory, tool-using LLMs, and orchestrated autonomy. But deploying them to the cloud is still painful - for example, your agentic app typically needs to provision:

• Managed databases like Postgres or MongoDB
• Fast, scalable caching (hello Redis)
• Containerized compute that scales
• Secure networking and service discovery
• Managed LLMs like AWS Bedrock or GCP Vertex AI

And for many teams, these apps must run inside the customer’s cloud, where sensitive data lives and compliance rules apply. That means you cannot just spin up your own environment and call it a day. Instead, you are deploying across AWS, GCP, DigitalOcean, or whichever stack your customers demand, each with its own APIs, quirks, and limitations.

Now you are not just building agents; you are picking the right infrastructure, rewriting IaC templates for every provider, and untangling the edge cases of each cloud.

The result: weeks of DevOps headaches, lost momentum, and engineers stuck wiring infrastructure instead of shipping agents.

We Made it Simple with Cloud Native Support for Agentic Apps​

That’s where Defang comes in. We make it easy to deploy full-stack agentic apps to your cloud of choice: native, secure, and scalable. Defang understands the common ingredients of agentic apps and makes them first-class citizens:

• Compute: Your Dockerized services deploy as cloud-native workloads (e.g. AWS ECS, or GCP Cloud Run)
• Databases: Provision managed Postgres or MongoDB with one config line
• Caching: Add Redis and Defang spins up a managed Redis instance in your cloud
• LLMs: Integrate directly with Bedrock or Vertex AI - even provision an OpenAI gateway for compatibility with OpenAI APIs.
• Secure Defaults: : TLS, secrets, IAM, and service accounts handled out of the box

Built for All your Favorite Agentic Frameworks​

Defang works seamlessly with leading agentic frameworks. Try them out with our ready-to-deploy samples:

• Autogen - demo featuring Mistral AI + FastAPI, deployable with Defang’s OpenAI Access Gateway.
• CrewAI - sample app showing multi-agent orchestration in action.
• LangGraph - workflow sample that defines and controls multi-step agentic graphs with LangChain.
• Agentic Strands - A Strands Agent application.

More framework templates coming soon.

Why It Matters​

Agentic apps need to be fast, secure, and ready to scale. Defang delivers cloud-native deployments in your environment (AWS, GCP, DO), so you can move from idea to production quickly with consistent behavior across dev, test, and prod.

The Developer Journey, Simplified​

1. Build your agentic app locally using Docker Compose
2. Test in Defang's free playground with defang compose up
3. Deploy to your cloud:

defang compose up --provider=aws  # or gcp, digitalocean

It just works. No Terraform. No YAML explosion. No vendor lock-in.

The Future of AI Apps Is Agentic and Cloud-Native​

Agility and scalability should not be a trade-off. With Defang, you get both. Developers focus on agents, tools, and outcomes. Defang takes care of the cloud infrastructure.

Try it out​

Explore more samples at docs.defang.io Join our community on Discord