Sold by: Inmatura
Deployed on AWS
Free Trial
AWS Free Tier
Ready to use JupyterHub installation with support for multiple users, easy user management, multiple Python and R versions with core packages installed. Support for GPUs. Includes RStudio and VSCode.
For more information look at our documentation: https://aws.inmatura.com/ami/jupyterhub/
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Overview
The JupyterHub AMI provides a multi-user JupyterHub installation with easy user management that can be launched on any AWS EC2 instance types.
It gives users access to AI and data science tools and resources without installation and maintenance tasks while providing the full flexibility of managing your own infrastructure. No vendor Lock-In.
- Immediately start using your JupyterHub installation, no SSH required to launch any services
- Multiple IDEs including JupyterLab, Jupyter Classic Notebook, RStudio IDE, and VSCode
- Multiple Python and R versions installed and configured
- A set of most popular Open Source packages installed and configured
- Easily installation of more packages, you have control
- Basic set of extensions installed without cluttering the server so you can configure the installation as needed
- Manage access of multiple users using an industry-standard system based on KeyCloak
- Easily connect to external LDAP or Kerberos to federate users from KeyCloak
- Easily configure a custon DNS for SSL termination
- GPU and multiple version of CUDA installed for the best usage of PyTorch and TensorFlow
- No per RAM or CPU pricing. Just a small fee for the AMI and use any EC2 instance type including GPUs
- Based on Ubuntu 22.04
- Free trial
For more information take a look at the documentation: https://aws.inmatura.com/ami/jupyterhub/
Highlights
- ZERO INITIAL CONFIGURATION: Immediately start using your JupyterHub installation, no ssh or configuration required
- BATTERIES INCLUDED: User management. Jupyter, RStudio IDE and VSCode, multiple Python and R versions with core data science packages installed
- STANDARD AND EXTENSIBLE: Standard JupyterHub with Python, R, just what you expect, no surprises. Extend as needed. You are in control
Details
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Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu 22.04
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.
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.
Dimension | Cost/hour |
|---|---|
c4.large Recommended | $0.15 |
t3.micro | $0.15 |
t2.micro | $0.15 |
m5.4xlarge | $0.15 |
m4.4xlarge | $0.15 |
p3.8xlarge | $0.15 |
m3.large | $0.15 |
p3.16xlarge | $0.15 |
t2.xlarge | $0.15 |
g2.2xlarge | $0.15 |
Dimensions summary
You pay an hourly software fee that stays the same across every option. Each dimension maps to a specific EC2 instance type, measured in hours. The list spans general-purpose, compute-optimized, memory sizes, and GPU instances. The software fee does not change by RAM, CPU, or GPU. Pick the instance that fits your workload, including GPU types for machine learning. You are charged only while your EC2 instance runs. AWS infrastructure costs are separate and depend on the instance type you choose. Larger or GPU instances raise your AWS infrastructure cost, not the software fee itself.
Top-of-mind questions for buyers
GPU instances provide graphics hardware for machine learning work. This product installs GPU drivers and multiple CUDA versions, tuned for common deep learning frameworks. You pick a GPU instance when you need that acceleration. The software fee stays the same whether you choose a GPU or non-GPU instance.
No. You pay the hourly software fee only while your EC2 instance is running. A stopped instance stops software charges. Note that AWS may still bill separately for storage tied to a stopped instance, but that is infrastructure cost, not the software fee.
No. The software fee is the same flat hourly rate across every instance type listed. It does not scale with RAM, CPU, or GPU count. Moving to a larger instance raises only your separate AWS infrastructure cost, which depends on the instance you select.
aws.inmatura.com
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Vendor refund policy
We do not currently support refunds, but you can cancel at any time. Email for special cases.
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
Update JupyterHub, Keycloak, Python, R, libraries, GPU driver and other underlying dependencies.
Additional details
Usage instructions
After launching an EC2 instance JupyterHub will start automatically on port 80
- Access it at: http://<instance-ip>
- The default username is: jupyterhub-admin
- The default password is the EC2 instance ID, you can get that from the EC2 dashboard, for example: i-0b3445939c7492
See full documentation at https://aws.inmatura.com/ami/jupyterhub/
Resources
Vendor resources
Support
Vendor support
Please look at the documentation:
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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Customer reviews
Matt
No Support
Reviewed on May 08, 2023
Review from a verified AWS customer
We could not get SSO to work with Azure AD. There is very little documentation for this AMI, and it just points you to KeyCloak's documentation for authentication - which was not helpful. I emailed support and never heard back.
James
Does not work
Reviewed on May 04, 2023
Review from a verified AWS customer
Once the instance is running, you open the web page and the only option it gives you is 'Sign In With KeyCloak'. When you click the button, it goes to 'This site can’t be reached'.
Please fix this!
Dev
It does not work
Reviewed on May 04, 2022
Review from a verified AWS customer
When the page opens there is a button that says "Sign in with KeyCloak", but when you click it does not redirect to the sign in page.
Pedro Sanchez
It does what it does
Reviewed on Oct 08, 2021
Review from a verified AWS customer
The AMI does exactly what it says it does. It is intended for people that know Jupyter and Python in order to extend the install other environments and other functionality but at the same time it works out of the box, as an AMI service you still need to manage the instance, backups but its easy to integrate with existing processes.
julien
lots of anoying bug
Reviewed on Apr 18, 2020
Review from a verified AWS customer
For a product as simple as this one there are a lot of annoying bugs. e.g. impossible to export large files (50mb) if your notebook becomes too large it doesn't save.
definitely not an out of the box solution