Fly.io gives teams control over where their containers run, with Machines and regional placement for workloads that benefit from compute close to users. The backend still needs deployment configuration, process groups, network connections, and a storage plan, including replication for applications using local volumes. Teams looking for alternatives often want less work at that level, or need production in their own AWS or GCP account, while developers and agents keep adding backend features.

For teams looking for Fly.io alternatives, the problems tend to include:

• Application changes also require updates to Machine settings, process groups, and deployment configuration.
• Volume-backed workloads need an explicit replication, backup, and recovery plan across Machines and regions.
• Production needs to run in the AWS or GCP account the platform team already manages.
• Local tests do not reproduce every network, region, and storage assumption in the deployed application.
• Agents can deploy changes quickly, but the team still needs to trace their effects through resource connections and runtime configuration.

Fly.io alternatives at a glance

Alternative	Approach	Best fit
Encore	Type-safe APIs and infrastructure in application code, deployed to your AWS or GCP account	Teams that want developers and agents to work with backend resources while platform teams control production
Render	Managed web services, workers, databases, and YAML Blueprints	Teams keeping their framework and a managed service deployment model
Railway	Repository or container deployment with connected services and isolated environments	Teams deploying an existing stack with connected services
Coolify	Self-hosted deployment tooling for repositories, containers, and Compose	Teams prepared to operate their own servers and deployment platform
DigitalOcean App Platform	Managed services, workers, and jobs within DigitalOcean	Teams already using DigitalOcean infrastructure

Encore: backend code with infrastructure under your control

Encore combines the simplicity of a managed backend platform with infrastructure in your own AWS or GCP account, defined through type-safe primitives in application code. Developers and agents work with services, APIs, databases, Pub/Sub, buckets, caches, cron jobs, and secrets, while platform teams control how those resources run. The application runs on standard cloud services and can be built as a Docker image for deployment outside the Encore platform.

Encore uses static analysis to read the API and resource declarations without running the code, building an application model of service dependencies, resource connections, and the IAM needed for supported resources.

For an API moving off Fly.io, compute, scaling, networking, and regions are configured for the target AWS or GCP environment through environment configuration. Developers define the API and its resource dependencies in application code, while platform teams configure how it runs. Encore provisions supported resources with integrated logs, metrics, and tracing; existing Terraform can continue managing shared or unsupported infrastructure.

Working with agents

~/orders — claude

Claude Code v2.1.180Opus 4.8 · Encore MCP connected~/orders

Infra from codereading the code…

SQLDatabaseorders · postgres

Topicorders · pub/sub

Bucketdeclared in code

not running yet

A database, bucket, Pub/Sub topic, or any other supported infrastructure resource is declared in the code that uses it. When an agent adds one:

• APIs, business logic, and resource dependencies can be reviewed in the same pull request, with generated clients providing typed access from the frontend.
• From the first encore run, the agent can test the change against local infrastructure, then check it end to end in an isolated preview environment on Encore Cloud, or in your own cloud account on Enterprise.
• The same application definitions drive local development, previews, and production, keeping services and resource dependencies consistent while capacity and cloud settings are configured per environment.
• The agent can use type errors, traces, and logs to find and fix failures, and test the authorization checks and business rules in the API before opening a pull request.
• Platform teams can configure separate processes per service for independent deployment and scaling, with Pub/Sub subscribers for asynchronous work and cron jobs for scheduled processing.
• Platform teams keep control of production configuration and credentials through their access controls, while developers work with application-level resources.

Cloud resources are billed directly in your account, with costs determined by the services and capacity your team configures, alongside Encore's platform fee.

Best for

Encore fits engineering teams building APIs and event-driven backends that want production in their own AWS or GCP account, with platform teams controlling compute and scaling through environment configuration. Workloads that depend on direct Machine lifecycle control, attached volumes, or specialized hardware can remain on Fly.io or another runtime.

Start with one stateless API and retain components that still benefit from Fly's regional placement. Encore has no attached-disk primitive: files may move to object storage, structured data to Postgres, or the storage-dependent workload can stay external. Establish connectivity before sharing a database; Fly.io Managed Postgres is private-network-only, so an external connection needs a suitable proxy or private network path.

See the migration guide for workload mapping and adoption steps.

Render: managed hosting for services and workers

Render hosts web services, private services, background workers, cron jobs, and managed Postgres. Services in the same region can communicate over a private network, and Blueprints describe the deployment in a version-controlled YAML file.

Working with agents

Agents can edit application code and render.yaml, use Render's MCP server to inspect services and logs, and test changes in preview environments. A Blueprint can reproduce a group of services and databases for a pull request. Application-level dependencies and permissions still need to be expressed in the code and deployment configuration your team maintains.

Best for

Render fits teams that want hosted services and workers with little infrastructure setup, while keeping their existing framework. Production stays on Render's managed infrastructure; moving to AWS or GCP means recreating the deployment, resource connections, and operational configuration there.

Railway: connected services with a flexible deployment workflow

Railway deploys applications from repositories or container images, with database templates, volumes, cron jobs, and private networking. Reference variables connect services to each other's addresses and credentials, while deployment settings can live in TOML or JSON.

Working with agents

Railway provides MCP and agent tooling for inspecting and managing deployments. Agents can work with the existing application framework, configure services, and test changes in isolated PR environments. Resource connections use Railway configuration and reference variables, alongside the dependencies expressed in application code.

Best for

Railway fits teams that want to deploy an existing backend and its dependencies without adopting a new framework. Its standard offering runs on Railway infrastructure, with usage billing and spending controls. Railway also advertises Enterprise BYOC for deployment in an existing VPC; teams that only need a different hosting location should evaluate that option before migrating the application.

Coolify: a deployment platform on servers you control

Coolify provides a deployment dashboard for applications, databases, and services on your own servers. It supports repository builds, container images, and Docker Compose, so an existing backend can keep its framework and deployment packaging.

Working with agents

Agents can edit the application, Dockerfile, or Compose configuration and trigger deployments through Coolify's API or repository integration. Preview deployments run pull requests separately from production. Your team configures the resources and credentials each application uses, including how previews connect to databases and other stateful services.

Best for

Coolify fits teams that want a PaaS-like dashboard on their own VPS or cloud servers and have the capacity to operate it. Server security, platform updates, backups, recovery, and capacity planning remain part of the team's work. Self-hosting changes who controls the deployment without requiring the backend to adopt a new application model.

DigitalOcean App Platform: managed hosting within DigitalOcean

DigitalOcean App Platform builds and deploys web services, static sites, workers, and jobs. Applications can connect to DigitalOcean Managed Databases and other services in the same ecosystem.

Working with agents

An agent can edit the application's app spec and deploy it through the API or doctl. The spec describes components, instance settings, environment variables, and database connections. Local testing uses the application's existing framework and tooling, with cloud configuration checked separately.

Best for

App Platform fits teams already using DigitalOcean that want managed application hosting alongside its databases and storage. It keeps the backend on DigitalOcean rather than deploying into an existing AWS or GCP account. Compare component sizes, scaling behavior, database costs, and transfer charges against your workload.

How to choose

Choose Render or Railway if you want managed hosting while keeping the existing application framework. DigitalOcean App Platform fits teams already using its cloud services, and Coolify fits teams that want deployment tooling on their own servers. Encore fits API and event-driven backends that need application-defined resources and production in their own AWS or GCP account. Before moving, check whether the target can preserve the regional placement, latency, and storage behavior the application relies on.