Production-ready Jupyter Notebook with full root access, pre-configured Python environments, and security hardening - ideal for data science teams needing a private, customizable notebook server on AWS.
This fully managed Jupyter Notebook solution delivers a production-ready, secure data science platform on AWS, built on Ubuntu 24.04 LTS. Every instance comes pre-configured with security best practices, optimized Python environments, and automated operations.
Key Features
Pre-configured Data Science Environment
Jupyter Notebook comes ready with Python, pip, and essential libraries. Install TensorFlow, PyTorch, scikit-learn, or pandas as needed with full root access.
Security Hardened
HTTPS-ready configuration, token-based authentication, UFW firewall pre-configured to allow only SSH (22) and web access (80/443) from trusted sources, and latest security patches applied.
Automated Setup
On first login, an interactive setup script configures Jupyter Notebook with secure access, sets up authentication tokens, and configures firewall rules - all within minutes.
Monitoring and Integration
Integrate with AWS CloudWatch for resource monitoring. Connect to S3 for data storage, RDS for database access, or Redshift for data warehousing directly from your notebooks.
Use Cases
Data exploration, visualization, and statistical analysis
Machine learning model development and prototyping
Academic research and collaborative data science
ETL pipeline development and testing
Business intelligence reporting and ad-hoc analysis
Teaching and training environments for Python and data science
Getting Started
Launch the AMI from AWS Marketplace on your preferred instance type
SSH into your instance and follow the interactive setup wizard
Access Jupyter Notebook via your browser and start analyzing data
Support
Managed and supported by Perimattic, a cloud infrastructure company with 13+ years of experience serving global clients. We offer free setup assistance, custom integrations, infrastructure consulting, and 24/7 support.
Highlights
Full Root Access Jupyter Notebook: get complete OS-level control to install custom packages, configure GPU drivers, and manage dependencies without vendor restrictions.
Pre-configured Data Science Platform: Ready-to-use Jupyter on Ubuntu 24.04 LTS with Python and pip. Add TensorFlow, PyTorch, or any framework with full root access.
24/7 Expert Support by Perimattic: 13+ years of cloud infrastructure expertise with free setup assistance, environment configuration, and dedicated support at aws-support@perimattic.com.
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
You pay by the hour for the compute instance size you run. Pricing scales with the instance type you select. The t2 and t3 families give you general-purpose burstable options in medium, large, and xlarge sizes. The m5 family adds two general-purpose sizes, large and xlarge, for steadier workloads. Larger sizes carry more CPU and memory, so their hourly rate is higher. There is no upfront commitment. You are billed only for the hours each instance runs, and you can switch sizes as your notebook needs change.
Top-of-mind questions for buyers
What resources and services do I get with each hourly instance rate?
Each rate covers a dedicated managed Jupyter Notebook deployment on the instance size you pick. The vendor handles provisioning, SSL, monitoring, daily backups, updates, and security patches. Every deployment includes firewall rules, TLS encryption, and role-based access control. You run production-grade tooling without managing the underlying servers yourself.
Am I charged when my notebook instance is stopped or idle?
The software fee meters running hours only. A fully stopped instance does not accrue hourly software charges. Underlying AWS storage tied to a stopped instance may still incur AWS fees, but the notebook software bills for active running time. You can stop instances when not in use to limit charges.
Which instance family should I choose, the burstable t2/t3 or the m5?
The t2 and t3 families are burstable, so they suit workloads with occasional CPU spikes and quieter periods. The m5 family gives steadier CPU and memory for continuous processing. You pick based on workload pattern, not just size. You can switch families as your notebook needs change.
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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
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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
Initial release of a fully automated Jupyter Notebook environment for AWS EC2.
Includes official Jupyter Data Science Notebook with preinstalled Python libraries.
Secure first-boot configuration with auto-generated strong password.
Persistent notebook and data storage preconfigured using Docker volumes.
Domain mapping wizard with DNS validation during first setup run.
Automated SSL certificate provisioning with Certbot for secure HTTPS access.
Integrated Apache reverse proxy for hardened access to Jupyter over the internet.
Automatic logging and configuration stored in /opt/app/.env for easy credential recovery.
Guided onboarding with interactive setup scripts and failsafe rerun support.
Additional details
Usage instructions
Launch an Instance
From AWS Marketplace, click Continue to Subscribe, then Continue to Configuration, and launch the AMI.
Choose the Recommended Instance Type
Select t2.medium or higher for a smooth Jupyter Notebook experience.
Data science workloads benefit from more CPU/RAM - larger instance types will significantly improve notebook execution performance and library handling.
Configure Security Group
Allow inbound traffic on the following ports:
22 (SSH) - For secure terminal access
80 (HTTP) - Required temporarily for SSL validation
443 (HTTPS) - Secure access to Jupyter Notebook in browser
Connect to the Instance
Use SSH to connect:
ssh -i <your-key.pem> ubuntu@<public-ip>
First-Boot Setup (Guided)
On first boot, an interactive guided setup will automatically start:
Detects public IP
Prompts for the domain name to map Jupyter Notebook
Validates DNS A-record propagation
Asks for admin email for SSL certificate issuance
Generates a secure random Jupyter access password
Stores credentials securely in /opt/app/.env
Configures Apache reverse proxy for HTTPS
Requests and installs a free Let's Encrypt SSL certificate
Deploys Jupyter Notebook using Docker Compose
Shows access URL and generated password after completion
DNS Configuration Required
Before (or during) the setup script, add this DNS A-record:
yourdomain.com <your-instance-public-IP>
Setup continues only when global DNS resolvers confirm valid mapping.
Automatic SSL Setup
After DNS validation completes:
Enables HTTPS access to Jupyter Notebook
Auto-installs valid TLS certificate from Let's Encrypt
HTTP access is disabled for security
Start / Restart Jupyter Manually (if needed)
cd /opt/app
docker compose ps
docker compose restart
Access the Jupyter Notebook
Open your browser and visit:
https://<your-domain>
Login credentials (displayed after setup & stored in .env):
Username: root
Password: <generated-password>
Retrieve Credentials Anytime
cat /opt/app/.env
Thank you for subscribing. Your instance is ready to go!
Need Support or Customization?
Whether you're facing setup issues or need custom features, Perimattic's expert team is here to help:
We offer:
Free setup assistance
Custom development & integrations
Infrastructure consulting
Automation & AI solutions
With 13+ years of experience serving global clients, we ensure your deployment runs smoothly and scales with your needs.
What We Help With:
Initial setup and configuration assistance (free)
Troubleshooting connectivity, performance, and backup issues
Custom development and integrations
Infrastructure consulting and architecture review
Migration planning from other solutions
Automation solutions and scaling guidance
Instance Sizing Guidance:
t2.medium or t3.medium: Development environments, small applications
m5.large: Production workloads with moderate traffic
m5.xlarge: High-traffic production deployments and larger datasets
For workload-specific sizing recommendations, contact our team for a free consultation.
Refunds and Issues:
If you experience any issues or need to request a refund, contact us at aws-support@perimattic.com and we will respond promptly.
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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