Ship faster.
Deploy anything.
Hubfly space lets you deploy containers, stacks, and services from GitHub, Docker images, or ready made templates without the infrastructure overhead.
Choose your fastest path to production
These are the main entry points into the platform. Start with the fastest route if you are evaluating Hubfly space, or jump directly to the workflow that matches how your service is already built.
Quick Start
Create a project and launch your first service in under five minutes.
Deploy from Git
Connect a GitHub repository and build directly from your source code.
Deploy from Image
Run any Docker image with custom commands, ports, and launch settings.
Templates
Launch curated app and service starters without building everything from scratch.
Go deeper by platform area
Once the first deploy is clear, these guides cover the infrastructure around it: runtime behavior, networking, volumes, balancing, private access, and advanced workloads.
Platform
Understand projects, runtime tiers, resource sizing, and shared platform concepts.
Compose Stacks
Deploy and manage multi-container services with Compose-based workflows.
Volumes
Attach persistent storage to stateful services and keep data across deploys.
Networking
Configure internal aliases, public endpoints, and custom domain routing.
Load Balancers
Distribute traffic across multiple targets with domains and routing policies.
GPU Deployments
Provision accelerated workloads, notebook access, and GPU-backed compute.
CLI
Deploy locally, open private tunnels, and automate repeatable workflows from the terminal.
HubTunnels
Open secure private access to services without exposing them publicly.
Architecture
See how the main platform systems fit together behind deployments.
Container tiers
| Tier | Resources | Best for |
|---|---|---|
shared | Shared infrastructure | Development, staging, low-traffic services |
dedicated | Reserved resources | Production, high-traffic, latency-sensitive apps |
Most teams run shared in development and dedicated in production, a simple split that keeps costs predictable without compromising reliability where it matters.