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    Relevance Lab RStudio IDE - Secure EC2 Linux for Research

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    Deployed on AWS
    Secure RStudio IDE on EC2 Linux with auto-renewing HTTPS. Unlike manual installs or SageMaker, researchers launch a production-ready R and Python environment in minutes with no server configuration.

    Overview

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    Relevance Lab RStudio with EC2 Linux

    A pre-configured Amazon Machine Image (AMI) that delivers a secure, ready-to-use RStudio environment on EC2 Linux for scientific research computing. Unlike manually installing RStudio Server on a vanilla EC2 instance - which requires configuring Nginx reverse proxies, generating SSL certificates, resolving package dependencies, and hardening security settings - this AMI provides a production-ready environment that researchers can access securely through their browser within minutes of launch.

    What's Included

    • RStudio IDE - Full-featured integrated development environment for R and Python
    • Pre-installed scientific computing packages commonly used in research workflows
    • HTTPS security via AWS Certificate Manager (ACM) certificates and Application Load Balancer (ALB)
    • EC2 Linux base optimized for research computing workloads

    How It Works

    This AMI integrates with AWS Certificate Manager and an Application Load Balancer to provide encrypted HTTPS access to your RStudio instance. The deployment flow is:

    1. Subscribe to the AMI on AWS Marketplace
    2. Launch an EC2 instance using the AMI
    3. Configure an Application Load Balancer with an ACM-issued SSL/TLS certificate
    4. Access RStudio securely through your browser via the ALB endpoint

    This architecture ensures that all traffic between the researcher and the RStudio environment is encrypted in transit using Amazon-issued certificates, eliminating the need for self-signed certificates or manual SSL configuration.

    Why This AMI vs. Manual Installation

    Researchers who install RStudio Server manually on EC2 typically spend hours resolving Linux library dependencies, configuring web server proxies, obtaining and renewing SSL certificates, and troubleshooting connectivity. This AMI eliminates that entire workflow. Compared to Amazon SageMaker notebooks, this product provides a familiar RStudio desktop-style IDE experience with full R package ecosystem access and persistent storage on EC2, giving researchers complete control over their computing environment without SageMaker's managed notebook constraints.

    Key Differentiators

    • Security by default - ACM certificates and ALB integration provide enterprise-grade HTTPS without manual certificate management or self-signed certificate risks
    • Research-ready - Pre-installed packages for scientific computing eliminate environment setup so researchers begin analysis immediately after launch
    • Rapid deployment - Researchers focus on science, not server administration or Linux system configuration
    • Cost-effective - Pay only for the EC2 compute time you use; stop instances when not in active use
    • AWS-native integration - Works with existing VPCs, IAM policies, and AWS security controls

    Detailed Use Case: Biostatistics Research Workflow

    A biostatistics research team analyzing clinical trial data can launch this AMI on a memory-optimized EC2 instance (e.g., r5.xlarge), immediately access pre-installed packages for survival analysis and mixed-effects modeling, import datasets from Amazon S3, run Cox proportional hazards models and generate publication-ready forest plots - all within a single secure browser session. The ALB/ACM architecture ensures that sensitive patient-derived data remains encrypted in transit, meeting institutional review board (IRB) security requirements without requiring the research team to configure SSL infrastructure.

    AWS Integration Points

    • AWS Certificate Manager (ACM) - Automated SSL/TLS certificate provisioning and renewal
    • Application Load Balancer (ALB) - Secure traffic routing and HTTPS termination
    • Amazon EC2 - Flexible instance sizing to match workload requirements
    • Amazon VPC - Network isolation for sensitive research data
    • IAM - Fine-grained access control for multi-user research teams
    • Amazon S3 - Store and retrieve research datasets directly from RStudio

    Who This Is For

    • Academic researchers needing secure, cloud-based R and Python environments
    • Research IT teams provisioning standardized computing environments
    • Data scientists requiring reproducible analysis platforms
    • Institutions seeking to provide scalable research computing without on-premises infrastructure

    Getting Started

    After subscribing, launch the AMI on your preferred EC2 instance type, configure the ALB with an ACM certificate for your domain, and access RStudio through your browser. For a detailed deployment walkthrough, architecture guidance, or to schedule a guided setup session with our team, contact Relevance Lab support.

    For additional product details, visit the Relevance Lab blog at relevancelab.com/post/rstudio-research-ec2-linux.

    Highlights

    • Enterprise grade HTTPS encryption via AWS Certificate Manager and Application Load Balancer provides auto renewing Amazon issued certificates from first launch. Unlike manual RStudio Server installs that require configuring Nginx proxies, generating SSL certificates, and writing renewal scripts, this AMI delivers encrypted browser sessions meeting institutional security requirements with zero certificate management overhead.
    • Pre installed scientific computing packages for R and Python enable researchers to begin analysis immediately after deployment, unlike a blank EC2 instance where hours are typically spent resolving Linux library dependencies, package conflicts, and configuration issues. Compared to SageMaker notebooks, researchers get a familiar RStudio desktop style IDE with full R package ecosystem access and persistent EC2 storage.
    • AWS native deployment integrates with Amazon VPC for network isolation, IAM for fine grained access control, and flexible EC2 instance sizing to match workload requirements from individual researchers to multi user teams. Stop instances between sessions to pay only for compute time actually used.

    Details

    Delivery method

    Delivery option
    64-bit (x86) Amazon Machine Image (AMI)

    Latest version

    Operating system
    AmazonLinux 2023

    Deployed on AWS
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    Pricing

    Relevance Lab RStudio IDE - Secure EC2 Linux for Research

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    This product is available free of charge. Free 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.

    Vendor refund policy

    Not Applicable

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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) .

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    Usage information

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    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

    RStudio Server on Amazon Linux 2023 is a secure, ready-to-use environment for data scientists and researchers. This AMI provides a pre-installed, optimized RStudio Server with automated authentication and security best practices.

    Additional details

    Usage instructions

    Kindly refer the link given below for the userguide

    Resources

    Support

    Vendor support

    Contact Support

    For assistance with deployment, configuration, or troubleshooting of the RStudio with EC2 Linux AMI, contact the Relevance Lab support team at rlcloudsupport@relevancelab.com .

    Support Scope

    The support team can assist with:

    • Initial AMI deployment and EC2 instance launch issues
    • Application Load Balancer and ACM certificate configuration
    • RStudio IDE access and connectivity troubleshooting
    • Pre-installed package questions and compatibility guidance
    • Instance type sizing recommendations for different workload sizes
    • General product usage guidance

    Instance Sizing Guidance

    For individual researchers running standard statistical analyses, a t3.medium or t3.large instance provides adequate compute. For memory-intensive workloads such as large dataset processing or parallel model fitting, consider r5.xlarge or larger. For teams requiring concurrent access, contact support for multi-user architecture recommendations.

    Deployment Prerequisites

    Before launching, ensure you have:

    • A registered domain name for ALB HTTPS access
    • A validated ACM certificate for your domain
    • A VPC with at least two public subnets (required for ALB)
    • Appropriate IAM permissions to create EC2 instances and ALB resources

    AWS Infrastructure Support

    For AWS infrastructure issues unrelated to this AMI (billing, account access, EC2 service limits), contact AWS Support directly through your AWS Console.

    Refunds

    For refund requests related to this product, contact rlcloudsupport@relevancelab.com  with your AWS account ID and subscription details.

    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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