Sold by: Elm Computing
Deployed on AWS
Free Trial
AWS Free Tier
RShiny Server AMI, supported by Elm Computing.
Overview
This is a repackaged open source software product wherein additional charges apply for support by Elm Computing.
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This RShiny Server AMI is a pre-built image of RShiny Server that can be quickly launched and comes with the latest version of R and RShiny Server, along with a selection of popular R packages covering various domains:
- data science
- machine learning
- econometrics
- teaching statistics
- time series analysis
- database
- Bayesian statistics
- clinical trials
- medical image processing
- natural language processing
- epidemiology
- experimental design
- psychometric methodology
- analysis of pharmacokinetic data
- analysis of spatial and spatiotemporal data
- reproducible research
- phylogenetics
- web technologies
- hydrology
- sports analytics
- actuarial science
- optimization
- genomics, proteomics, metabolomics, transcriptomics, and other omics
The details can be found at http://docs.elmcomputing.io listing all the installed R packages.
After the EC2 instance is started, you can access the RShiny Server with its public IP address.
The RShiny applications are served from the directory /srv/shiny-server.
Highlights
- Up-to-date R and RShiny Server
- Thousands of R packages
- Elm Computing Support
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 30 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.
Dimension | Cost/hour |
|---|---|
m6a.2xlarge Recommended | $0.10 |
t2.micro | $0.10 |
t3.micro | $0.10 |
d3.xlarge | $0.10 |
c6a.32xlarge | $0.10 |
c7i.8xlarge | $0.10 |
m6in.32xlarge | $0.10 |
c7i.large | $0.10 |
c5ad.8xlarge | $0.10 |
m5a.4xlarge | $0.10 |
Dimensions summary
You pay by the hour for RShiny Server, a preconfigured environment for hosting Shiny applications with thousands of R packages. Pricing is tied to the AWS EC2 instance type you choose to run the software. Each dimension maps to a specific instance size, from small general-purpose types to large memory-, compute-, and storage-optimized machines, plus bare-metal options. Larger or more specialized instances carry higher hourly rates. The software charge covers vendor support and is added on top of your separate AWS infrastructure cost. Select the instance that matches your workload's compute, memory, and storage needs.
Top-of-mind questions for buyers
The hourly charge covers vendor support for the preconfigured RShiny Server software. Elm Computing repackages open source software and adds support charges. This software fee is separate from, and added on top of, the underlying AWS compute cost for the EC2 instance you run.
The software fee meters running time, so a fully stopped instance stops accruing hourly software charges. You may still pay AWS storage fees for the stopped instance's disk. Charges resume when you restart the instance. Billing follows the hours your chosen instance type runs.
Each dimension maps to one EC2 instance type differing in CPU, memory, and storage. Pick the type matching your Shiny workload. You can stop the software on one instance type and relaunch on another; hourly charges then follow the new instance's rate.
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Vendor refund policy
Refunds are generally not available. Instances are billed hourly based on actual usage and can be terminated at any time to stop charges.
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 R to version 4.6.0, upgrade R packages to their latest versions, and apply security patches.
Additional details
Usage instructions
After the EC2 instance is started, you can access the RShiny Server with its public IP address. For example, if the IP address is 10.11.12.13, typing http://10.11.12.13 in the browser will bring you to the RShiny Server page.
The details can be found at https://docs.elmcomputing.io listing all the installed R packages.
Resources
Vendor resources
Support
Vendor support
Please do not hesitate to contact us at support@elmcomputing.io if you have any questions.
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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By Elm Computing
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Pre-built Application Environment
Pre-configured AMI image with latest version of R and RShiny Server ready for immediate deployment
Comprehensive R Package Library
Includes thousands of R packages covering data science, machine learning, econometrics, statistics, time series analysis, Bayesian statistics, clinical trials, medical image processing, natural language processing, epidemiology, genomics, proteomics, metabolomics, transcriptomics, and specialized domains
Web Application Framework
RShiny Server framework for building and serving interactive web applications from the /srv/shiny-server directory
Multi-domain Analytics Support
Specialized packages for diverse analytical domains including spatial and spatiotemporal data analysis, phylogenetics, hydrology, sports analytics, actuarial science, and optimization
Quick Deployment Capability
EC2-based deployment model enabling rapid instance launch and access to RShiny applications via public IP address
Multi-User Access Management
Industry-standard KeyCloak-based user management system with support for external LDAP and Kerberos federation
Multiple IDE Support
Includes JupyterLab, Jupyter Classic Notebook, RStudio IDE, and VSCode for diverse development environments
GPU and CUDA Support
GPU support with multiple CUDA versions installed for optimized PyTorch and TensorFlow usage
Pre-configured Development Environment
Multiple Python and R versions with core data science packages pre-installed and configured
Operating System Foundation
Built on Ubuntu 22.04 with SSL termination capability through custom DNS configuration
Browser-Based Remote Access
Full-featured Ubuntu 22.04 LTS Desktop environment accessible through a web browser without requiring client software installation.
Remote Desktop Protocol Support
Native Remote Desktop client connectivity enabling access to the workspace through remote desktop protocol.
Preinstalled Development Tools
Includes latest versions of Google Chrome, Anaconda, Jupyter, RStudio Server, Visual Studio Code, and Docker.
Multi-User Environment
Supports multiple concurrent users on appropriately sized instances with capability to add additional users to the system.
Integrated Development Interfaces
Secure browser-based access to Jupyter notebooks, RStudio Server, and Terminal sessions with copy-paste and drag-and-drop file upload functionality between virtual desktop and client.
Standard contract
No
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