# I Tried 7 Fly.io Alternatives for Deploying a Full-Stack App. Here’s My Honest Take
I like having control over my infrastructure, but I do not necessarily want to manage every part of it.
That was what pushed me to start looking beyond Fly.io.
Fly.io gives developers a powerful way to run applications close to users. But once you move beyond a simple service, deployment can involve thinking about machines, regions, containers, networking, databases, scaling, and eventually costs.
At some point, infrastructure starts becoming another part of the job.
For the application I was working with, I did not need more infrastructure control.
I needed less infrastructure work.
I wanted to connect my Git repository, deploy the complete application, and spend most of my time building the product instead of deciding how the underlying infrastructure should run.
So I compared seven platforms:
- Kuberns
- Railway
- Render
- DigitalOcean App Platform
- Heroku
- Vercel
- Netlify
I also went through a more detailed comparison of Fly.io alternatives to understand how these platforms differ in deployment workflows, automation, pricing, and infrastructure management.
But for this comparison, I wanted to look at one simple question from a developer's perspective:
If I have a real application sitting in a Git repository, which platform gets me from code to production with the least unnecessary infrastructure work?
The Kind of Application I Wanted to Deploy
I did not want to compare these platforms using a static website or another hello-world application.
Instead, I used the requirements of a fairly normal full-stack application.
The application needed:
- A frontend
- A backend API
- A PostgreSQL database
- Environment variables
- A background worker
- A custom domain with SSL
- Automatic deployments when I pushed changes to Git
Nothing particularly unusual.
But once all these pieces are involved, the difference between deploying an application and managing its infrastructure becomes much more obvious.
My goal was to see how much work each platform required to get the complete application running.
Would I need to create every service individually?
Would I need to write a Dockerfile?
How much infrastructure configuration would be required?
How much would I need to think about scaling?
And once everything was live, how much operational work would still be left?
That became the baseline for comparing all seven platforms.
1. Kuberns: The Platform That Automated the Most
Kuberns was the first platform where I felt that the deployment workflow itself was being handled for me rather than simply being made easier to configure.
The starting point was straightforward.
I connected the Git repository, and its Agentic AI analyzed the application architecture and identified what was required to run it.
Instead of manually creating every service and configuring the infrastructure around them, much of that process was handled automatically.
For the type of full-stack application I was trying to deploy, this was the closest to the experience I wanted.
I did not need to start by preparing a Dockerfile or YAML configuration.
I also did not have to think about:
- Machines
- Regions
- Networking
- Infrastructure provisioning
- Manually configuring a CI/CD pipeline
The workflow was closer to:
Connect Repository
↓
AI Understands the Application
↓
Required Infrastructure Is Provisioned
↓
Application Is Deployed
↓
Cloud Operations Are Managed
What stood out to me was that the automation did not stop once the application was deployed.
Monitoring, logs, SSL, scaling, CI/CD, and ongoing cloud operations were already part of the platform experience.
Compared with Fly.io, the philosophy felt almost opposite.
Fly.io gives developers more direct control over infrastructure.
Kuberns tries to reduce how often developers need to think about that infrastructure in the first place.
For my original goal of getting a complete application from Git to production with the least unnecessary infrastructure work, Kuberns gave me the simplest overall experience.
2. Railway: Probably the Smoothest Traditional Developer Experience
Railway was one of the easiest platforms to understand from the moment I connected a project.
The developer experience is very polished.
You can connect a GitHub repository, let Railway detect how the application should be built, and quickly add services such as:
- PostgreSQL
- MySQL
- Redis
- MongoDB
Coming from Fly.io, this felt noticeably simpler because I was not thinking about machines or regions before getting the application online.
For developers who want to push code and quickly get a service running, Railway does this extremely well.
Adding databases and connecting multiple services also feels much more approachable than managing the infrastructure behind them directly.
The main difference I noticed compared with Kuberns was the level of automation.
Railway makes it easy to create and manage the services your application needs.
Kuberns goes a step further by trying to understand the application's architecture and automate more of the infrastructure provisioning and cloud operations around it.
Still, if I wanted a modern traditional PaaS where I already understood exactly which services I needed, Railway would probably be my strongest choice after Kuberns.
3. Render: Simple Until the Application Has Multiple Services
Render gave me a straightforward deployment experience from the beginning.
I could connect my repository, define the build and start commands, and deploy without thinking about servers or machines.
For a single web application or API, the experience felt clean and easy to follow.
Things became slightly different when I applied the requirements of my complete application.
I had:
- A frontend
- A backend
- A database
- A background worker
Each part needed to be configured as its own service.
Environment variables and other settings also needed to be managed across those services.
None of this was particularly difficult.
But I was still responsible for understanding the application's architecture and configuring each component correctly.
That is where I noticed the difference between simplifying infrastructure and automating deployment.
Render does a very good job of hiding much of the underlying cloud infrastructure.
But I still need to tell the platform how my application should be structured.
For a straightforward web application or API, I found Render very easy to work with.
For larger applications with multiple services, I preferred the idea of a platform that could automatically understand more of the application architecture.
4. DigitalOcean App Platform: Easier Cloud With More Control
DigitalOcean App Platform felt like a good middle ground between a traditional PaaS and directly managing cloud infrastructure.
You can connect a GitHub or GitLab repository, let the platform detect the application framework, and deploy without setting up servers manually.
Compared with Fly.io, that immediately removes a lot of infrastructure work.
For a simple application, the experience is straightforward.
But once I introduced the requirements of my full-stack application, I still had several decisions to make.
I needed to think about:
- Databases
- Environment variables
- Scaling settings
- Application components
- How different services should be configured
I actually liked having that flexibility.
DigitalOcean App Platform gives developers more control without forcing them to directly manage the underlying infrastructure.
But that also means it is not the most hands-off option.
If I already knew exactly how I wanted my application's infrastructure to look, DigitalOcean App Platform would make a lot of sense.
For my goal of minimizing infrastructure decisions, however, I found myself preferring platforms that automated more of that process.
5. Heroku: The Workflow Still Works
Heroku still feels familiar, even when compared with much newer deployment platforms.
The basic idea remains simple:
Push Code → Build Application → Run Application
For developers who simply want to get an application online without managing servers, the workflow still makes sense.
Compared with Fly.io, I had far fewer infrastructure decisions to make.
I was not thinking about machines or regions, and Heroku's add-on ecosystem makes it relatively straightforward to add things like databases and caching.
But when I looked at the complete application, I still needed to configure several pieces individually:
- Web dynos
- Worker dynos
- Environment variables
- Databases
- Add-ons
The underlying server management disappears, but you are still responsible for putting the different application components together.
Pricing was another consideration.
Once a production application requires multiple dynos and additional services, the total cost can increase relatively quickly.
Even so, it is easy to understand why Heroku's developer experience influenced so many of the deployment platforms that came after it.
The workflow is proven, the documentation is mature, and the platform remains easy to understand.
For a new project today, though, I would personally prefer a platform that automates more of the application setup and ongoing operations.
6. Vercel: An Excellent Experience for Frontend Applications
For frontend deployment, Vercel was one of the easiest platforms in this comparison.
You can connect a Git repository, push your code, and have the application automatically built and deployed.
Features such as:
- Preview deployments
- CI/CD
- Global delivery
- SSL
- Git-based deployment
are handled with very little effort.
For Next.js and modern frontend applications, the developer experience is extremely polished.
The challenge started when I brought the rest of my test application into the picture.
I needed:
- A traditional backend API
- PostgreSQL
- A long-running background worker
At that point, I either had to adapt parts of the application to the platform's architecture or introduce additional services into the stack.
For frontend-focused applications, Vercel would easily be one of my first choices.
For the complete full-stack architecture I was testing, however, it did not give me the all-in-one deployment experience I wanted.
7. Netlify: Excellent for Frontend and Jamstack Workloads
My experience with Netlify was similar in some ways.
Connecting a repository and deploying a frontend application is extremely simple.
Git-based deployments, SSL, previews, and global delivery require very little manual work.
For static sites, frontend applications, and Jamstack projects, Netlify remains a strong option.
But my application needed more than a frontend.
Once I added a backend API, PostgreSQL, and a background worker, I needed external services or a different architecture for parts of the application.
That was not necessarily a problem with Netlify.
It simply meant that the platform was solving a different problem from the one I had.
I wanted to simplify deployment for the entire application, not only the frontend.
What the Deployment Experience Actually Looked Like
After going through all seven platforms, this was roughly how I saw the developer experience.
| Platform | Repo to Deploy | Database Setup | Multi-Service Setup | Infrastructure Work | My Experience |
|---|---|---|---|---|---|
| Kuberns | Very simple | Automated | Mostly automated | Very low | Simplest overall |
| Railway | Simple | Very simple | Simple | Low | Best traditional PaaS experience |
| Render | Simple | Simple | Manual service setup | Low to medium | Great for straightforward apps |
| DigitalOcean App Platform | Simple | Requires configuration | Requires configuration | Medium | Good balance of control and simplicity |
| Heroku | Simple | Add-on based | Requires configuration | Low to medium | Proven and familiar |
| Vercel | Extremely simple | External for traditional databases | Limited for traditional services | Very low for frontend | Excellent frontend experience |
| Netlify | Extremely simple | External | Limited for traditional services | Very low for frontend | Excellent for frontend and Jamstack |
The biggest difference was not necessarily whether a platform could run the application.
Most of them could.
The difference was how much I had to think about before and after deployment.
With some platforms, I still needed to decide how to split the application into services, configure each component, connect the database, and think about scaling later.
With frontend-focused platforms, deployment was incredibly simple as long as my application matched the platform's preferred architecture.
Kuberns required the least infrastructure involvement from me across the complete application.
Railway came closest when I wanted a more traditional PaaS workflow while still controlling how individual services were configured.
The Simplest Option I Found
After comparing all seven platforms against the same full-stack requirements, Kuberns was the simplest overall option for me.
Not because every individual feature was unique.
The difference was how little infrastructure work I needed to do myself.
With most platforms, the deployment process still started with me understanding exactly how the application needed to be deployed.
I had to think about:
- Services
- Databases
- Workers
- Resources
- Deployment configuration
- How everything should connect
With Kuberns, the starting point was different.
I connected the repository, and the platform's Agentic AI handled more of the process by understanding the application architecture, identifying the required resources, provisioning the infrastructure, and deploying the application.
That is ultimately the type of deployment experience I am looking for.
I do not want to spend my development time becoming better at configuring deployment platforms.
I want to build the application, push my code, and let the platform handle as much of the operational work as possible.
For developers moving away from Fly.io specifically because they want less machine management, fewer infrastructure decisions, and a simpler way to deploy complete applications, Kuberns would be my first recommendation.
For a deeper breakdown of the platforms, pricing, features, and deployment differences, you can also check out this detailed comparison of Fly.io alternatives.
If I were deploying a new full-stack application today, my priority would be simple:
Choose the platform that lets me spend the most time building the application and the least time managing everything underneath it.
For me, that platform would be Kuberns.
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