Sold by: Websoft9
Deployed on AWS
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This product has charges associated with it for Websoft9 support. Pre-configured, web-based, cloud-native, secure, one-click to deploy Python Runtime with Websoft9 Applications Hosting Platform on AWS. This integration environment helps you focus on code delivery, deployment, and management of Python APPS.
Overview
This is a cloud-native Python runtime on the Websoft9 Applications Hosting Platform. It is always up-to-date, secure, and ready to use right out of the box with business support from Websoft9.
Python Runtime is a fully production environment, it lets you focus on code deliver and deploy or manage Python APPS in a reliable, repeatable, and controlled way, also helps automate deployment and reduces the risk of human error, especially for complex large environments.
Websoft9 is a lightweight, self-hosting PaaS that allows you to deploy multiple applications on your own cloud infrastructure. It employs a GitOps approach and includes an integrated app store that supports one-click deployment of over 200 template applications, as well as the ability to deploy custom applications. Users have complete autonomy, ensuring that applications can be easily configured and continuously deployed even after they are live. Additionally, the web-based interface allows users to effortlessly perform tasks such as domain binding, HTTPS setup, access control, and status monitoring.
Image Components
Python 3.13/3.12/3.11/3.10/3.9/3.8/3.7/3.6, Docker, Websoft9 Platform
Trademark Statement
Python and PyCon are trademarks or registered trademarks of the Python Software Foundation.
Use Cases
Run Python application
Ready-to-use related applications
This product enables users to deploy additional app runtime related to Pythone with a one-click, including Java, PHP, Ruby, Golang, Docker, Node.js, Static website, and others you may need.
EC2 requirements
CPU no less than 2 core, Memory no less than 4G
Highlights
- Docker-based, easy to deploy and upgrade
- Console panel for installing and managing multiple applications on a single instance
- One-click deployment of over 200+ template applications from the console
Details
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Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu 24.04
Deployed on AWS
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Pricing
Free trial
Try this product free for 5 days according to the free trial terms set by the vendor. Usage-based pricing is in effect for usage beyond the free trial terms. Your free trial gets automatically converted to a paid subscription when the trial ends, but may be canceled any time before that.
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time. Alternatively, you can pay upfront for a contract, which typically covers your anticipated usage for the contract duration. Any usage beyond contract will incur additional usage-based costs.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
If you are an AWS Free Tier customer with a free plan, you are eligible to subscribe to this offer. You can use free credits to cover the cost of eligible AWS infrastructure. See AWS Free Tier for more details. If you created an AWS account before July 15th, 2025, and qualify for the Legacy AWS Free Tier, Amazon EC2 charges for Micro instances are free for up to 750 hours per month. See Legacy AWS Free Tier for more details.
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Dimension | Cost/hour |
|---|---|
t2.medium Recommended | $0.055 |
t3.micro | $0.055 |
t2.micro | $0.039 |
d2.4xlarge | $0.155 |
i3.large | $0.055 |
t2.small | $0.039 |
i3.8xlarge | $0.22 |
x1.32xlarge | $0.439 |
h1.8xlarge | $0.22 |
g3.4xlarge | $0.155 |
Dimensions summary
You pay by the hour based on the EC2 instance size you pick to run this Python app runtime. Each dimension maps to a specific AWS instance type, so your rate changes with the compute, memory, and storage of that instance. Smaller instances like t2.nano and t2.micro cost less per hour, while large instances such as x1e.32xlarge and c6a.metal cost more. You choose the instance that fits your workload. Billing runs on usage, so you pay only for the hours the instance runs, with no upfront commitment.
Top-of-mind questions for buyers
You get a pre-configured Python web runtime image running on the EC2 instance type you select. Each dimension matches one AWS instance size, so the hardware you receive scales with that type's vCPU, memory, and storage. The image ships with Python, pip, and application servers like Gunicorn and uWSGI ready to use.
The software charge meters running hours only, so a fully stopped instance stops accruing the hourly software fee. You pay only for the hours the instance runs. Note that stopped instances may still incur underlying AWS storage fees for attached volumes, which are separate from this listing's software charge.
Your rate is tied to the instance type you launch. To change it, you deploy on a different instance size, such as moving from t2.micro to m5.4xlarge. The new hourly rate applies only to hours run on the new instance. The change is manual, not automatic, since you choose the instance.
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Vendor refund policy
Annual Subscriptions: Refunds are allowed if you are canceling a subscription to purchase a new subscription from Websoft9 at the same or higher rate. Hourly Subscriptions: We do not currently support refunds, but you can cancel at any time.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
Python 3.13/3.12/3.11/3.10/3.9/3.8/3.7/3.6, Docker, Websoft9 v2.2.17
Additional details
Usage instructions
Once the instance is running, enter the http://Public DNS:9000 provided by AWS into your browser.
You will then see the Websoft9 Console. And refer to the following steps to get started:
- Use SSH to connect your AWS EC2 by user ubuntu
- Run command 'sudo usermod -aG docker ubuntu && sudo passwd ubuntu' to set password and permisson for this user
- Use your EC2 username 'ubuntu' and password to log in Websoft9 Console.
- Go to the "App Store" in the Websoft9 Console and install Python with a one-click.
- Once installation is complete, go to "My Apps" to get the port, access url and credentials of Python.
Resources
Vendor resources
Support
Vendor support
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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