Amazon Web Services (AWS)

What is Amazon Web Services (AWS) Self-Service Portal?

DGIT has configured a self-service portal version of Amazon Web Services (AWS) which enables you, the user, to deploy preconfigured AWS services, on-demand, that meet UCLA Health compliance requirements.

The self-service portal offers:

  • Linux Servers (CPU & GPU)
  • RStudio Server
  • Jupyter Notebook (SageMaker)
  • Mathworks Matlab (GUI)
  • S3 Storage (Object storage)

Access type:

  • Staff provided
  • On request
  • Fee-based, dependent on group needs

Email DGIT AWS Inquiry

All you need to do is ask

We would love to connect with you to determine if this solution fits your needs. Simply email DGITAWSInquiry@mednet.ucla.edu, and our expert team will be in touch to figure out the next steps.

 

Curious on how AWS works?

Check out our AWS training guides to learn a little more on the uses of the service offering.

AWS training guides


Already have an account?

Simply submit a service request for help, and our expert team will be in touch to assist.

Submit a request
Security and Data Protection
  • AWS is HIPAA-compliant to ensure security and reliability in all projects

Cost

  • Cost of use is dependent on the server and storage needs along with a baseline for use of the HIPAA-compliant platform
  • Direct billing to teams, no inter-department recharge tracking necessary
  • For a break-down, check out our DGIT AWS cost sample PDF

Functionality

  • Servers and storage available on demand with ability to change specifications as needed within minutes
  • Access to install software without need for IT involvement
  • Reduced barrier for entry to leverage cloud computing by using pre-configured templates

 

 

Service frequently asked questions

How much does the AWS service cost?

 

  • The costs for data services vary on a case-by-case basis and depend largely on your needs. 
  • To get an idea of cost, visit our DGIT AWS Cost Sample PDF.
  • Don’t worry—we’ll provide a detailed cost estimate before you commit to a project.
How is this different from the campus AWS service offering?

 

DGIT's AWS is:

  • HIPAA-compliant
  • Restricted to specific services and pre-configured templates
  • Lower barrier for entry in terms of "cloud" knowledge

Campus's AWS:

  • Provides access to all AWS services
  • Does not allow PHI/RI
What are the differences between S3 vs Box and File Share?

 

S3
  • More suited for research data sets
  • Unlimited file size and capacity
  • Compatible with all file types
  • Easily transfer data within AWS
  • Currently, no auto-sync or mounting
  • Costs based on usage
Box
  • More suited for administrative files (e.g. MS Office documents)
  • Auto-sync with local computer with Box Sync
  • Mount drive using Box Drive
  • Limited to 15GB per individual file
  • Some files types not compatible
  • Costs are subsidized
File Share
  • Suitable for administrative files and research data sets <10TB
  • Limited capacity and growth
  • Mount share from local computer
  • Costs are subsidized
What data is allowed on the different UCLA Health Cloud Infrastructures?
Data type DGIT
AWS
UCLA Health IT
Azure
Non-restricted data
restricted data
identified ucla health data
discovery data repository (DDR) Extracts

 

  • Restricted Information is defined by the University California - Systemwide IT Policy Glossary https://security.ucop.edu/files/documents/policies/it-policy-glossary.pdf
  • UCLA Health Data is defined as any information pertaining to the health, care, and treatment of UCLA Health patients or health plan members which: (1) results in a report used in treatment or monitoring of a patient; (2) generates a claim or a bill for services that are provided; and/or (3) is used for operations, financial management, population health activities or quality metrics.
  • The Discovery Data Repository (DDR) is built upon a limited data set containing de-identified electronic UCLA health record data.

 

Can you provide more information on the service offered?

Linux Servers

  • Web-based command line interface (CLI) running a Linux operating system.
  • Ubuntu and Amazon Linux (RedHat-based) available.
  • Optional Deep Learning baseline available. The Deep Learning baseline is a pre-configured system with the following apps pre-installed: TensorFlow, PyTorch, Apache MXNet, Chainer, Microsoft Cognitive Toolkit, Gluon, Horovod, and Keras.
  • Options for both CPU and GPU processors.

 

RStudio Server

  • Web-based RStudio interface.
  • Studio is an integrated development environment for R, a programming language for statistical computing and graphics. It includes a console, syntax-highlighting editor that supports direct code execution, as well as tools for plotting, history, debugging and workspace management.

 

Jupyter Notebook

  • Web-based Jupyter Notebook and JupyterLab via Amazon Sagemaker notebook instances.
  • An Amazon SageMaker notebook instance is a machine learning (ML) compute instance running the Jupyter Notebook App. SageMaker manages creating the instance and related resources.
  • Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more.
  • JupyterLab is a web-based interactive development environment for Jupyter notebooks, code, and data.

 

Mathworks Matlab

  • Graphic, remote desktop-based Matlab interface.
  • In this service, researchers can install other graphics-based applications in addition to Matlab.
  • Matlab is a high-performance language and desktop environment tuned for iterative analysis, design processes, and expresses matrix and array mathematics directly.

 

S3 Storage

  • Amazon Simple Storage Service (S3) is a managed service that provides object storage that is persistent and durable for any amount of data.
  • Object storage is a computer data storage architecture that manages data as objects, as opposed to other storage architectures like file systems which manages data as a file hierarchy, and block storage which manages data as blocks within sectors and tracks.