Python Dev Center

Python Developer Center

The platform provides ready-to-use Apache Python and Python Engine application servers, preconfigured for Python workloads so developers can focus on application development instead of infrastructure orchestration.

Python cloud hosting
Python application hosting and management on the platform.
In this article

Python Environment Hosting

Create a Python environment through the topology wizard. Open the Python tab, choose Apache Python or Python Engine, select the engine version, set resource limits and node count, and add any required software stacks or public IP addresses.

Python environment topology wizard
Choose the Python application server, engine version, resources, node count, and additional stacks.
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Environment characteristics

Both Python templates use the modern systemd initialization system. Every instance is an isolated container, and nodes in the same layer are distributed across available hosts for higher availability.

Python Versioning

The documented Python versions currently available are:

Python VersionSelection Method
3.10.20Topology wizard or container redeployment
3.11.15Topology wizard or container redeployment
3.12.13Topology wizard or container redeployment
3.13.14Topology wizard or container redeployment
3.14.6Topology wizard or container redeployment
Python engine versions
Select the required Python engine version during creation or redeployment.
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Check the current list

The Software Stack Versions document is updated regularly. Review it before creating or redeploying a production environment.

Python Application Deployment

Deployment to Apache Python and Python Engine is automated and supports:

  • Remote version-control repositories such as GitHub
  • Application archives uploaded from a local computer
  • Application archives provided through an external URL
Deploy a Python application
Deploy from a VCS repository or an application archive.

For horizontally scaled servers, deployment can run sequentially or simultaneously. Git-based deployment can also redeploy automatically when new repository changes are detected.

Python Packages and Modules

Dependencies are installed automatically during deployment. A manually created virtual environment is not required.

Application ServerSupported Dependency Tools
Apache Pythonpip with requirements.txt
Python EnginePoetry, then Pipenv, then pip — one tool is selected per deployment according to the project files

For inspection or manual package changes outside deployment, connect through SSH and use standard pip commands. Manual virtual environments are optional and intended mainly for temporary debugging.

Domain Management

CNAME redirectRecommended for development and testing through the Shared Load Balancer.
DNS A recordSuitable for production environments using a public IP and handling higher traffic.
Swap DomainsSwitch traffic between environments quickly and without downtime.
SwapExtIpsSwap external IPs through the API or CLI when required.
Python custom domain management
Bind custom domains or swap traffic between Python environments.

Automatic Vertical Scaling

Set the upper Cloudlet limit for the Python application server. The platform then supplies the required RAM and CPU automatically as workload changes.

One Cloudlet equals 128 MiB of RAM and 400 MHz of CPU.

Python automatic vertical scaling
Set the upper resource limit and allow the platform to scale automatically.

Manual Horizontal Scaling

Use the plus and minus controls in the topology wizard to select the required number of Python application-server nodes.

StatelessCreates all new nodes from the base image template simultaneously.
StatefulCopies the primary container file system to new nodes sequentially.
Python horizontal scaling
Set the node count and select Stateless or Stateful scaling.
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Automatic load balancer

A load-balancer instance is added automatically when the Python server layer is scaled beyond one node.

Automatic Horizontal Scaling

Open Settings > Auto Horizontal Scaling and create triggers that increase or decrease the number of nodes according to CPU, RAM, network, or disk load. Email notifications can be enabled for scaling changes.

Python automatic horizontal scaling
Create load-based triggers to add or remove Python application-server nodes.

Database Connection to Python Applications

The platform provides scalable managed database servers that can be added to the Python environment. Configure the application according to the selected database type, such as MySQL, MariaDB, or Percona.

Additional Platform Features

  • Built-In SSL and Custom SSL
  • Public IPv4 and IPv6 addresses
  • Managed software stacks
  • Container firewalls, endpoints, and environment isolation
  • Dashboard management and Web SSH
  • Open API and Cloud Scripting
  • Pay-as-you-use pricing
  • Team collaboration
  • Multi-cloud distribution

What’s Next?