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About Cloud Computing

Learn about cloud computing at UC San Diego.

Cloud computing, also known as the public cloud, the commercial cloud, or just “the cloud,” is a massive computing resource accessed via the internet. Cloud computing has five components:

  • Compute: Virtual machines ranging from small to extremely powerful
  • Storage: Effectively infinite
  • Networking: Connectivity both local and with the internet
  • Data management: Databases and related structure
  • Services: Special features such as streaming data analytics

Microsoft, Amazon Web Services, and Google are among the largest Cloud Service Providers (CSPs). They offer their computers, storage and networking hardware as a service, through the web, known as “Infrastructure as a Service” (IaaS). They also provide higher-level “Platform as a Service” (PaaS) on top of those basic services, such as data management and networking tools that range from operating systems to databases and many more add-on services. All these resources are maintained in secure data centers in multiple geographic locations. Customers access resources online, buying as little or as much as they need.

UC San Diego IT Services works closely with public cloud vendors to provide the campus with cost-effective cloud access, while allowing federal compliance regulations (HIPAA, FISMA, FERPA, PCI, FedRAMP, etc). Read below for more information on the benefits of cloud computing for research, including cost, security, usability and scale. Currently IT Services is focusing heavily on Amazon Web Services (AWS) as a primary Cloud Service Provider (CSP) for simplicity, ease of use, and cost savings.

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Research computing and the cloud

Cloud computing scales down or (way) up to support research computing without the hassles of operating and maintaining your own computing environment. You can implement processing pipelines, build and test modifications, create websites and web applications, implement databases, and securely manage your research computing environment. You can collaborate and easily share your data with others. Specifically, you can:

  • Archive data cheaply with extremely high reliability
  • Build out familiar data systems (Postgres, MySQL, Spark)
  • Create automated secure data feeds that extract from/ load to your data system
  • Maintain data repositories for other researchers to access
  • Manage access to your cloud resources across your research team, and with collaborators around the globe
  • Learn about capabilities and features of the cloud that may be new to you
  • Run MATLAB, R, Python or any other programming environment
  • Create an accurate estimate of what your use of the cloud will cost
  • Easily pull your data and software out of the cloud if you so choose, or move to a different cloud

Cost of cloud computing

The cloud is paid for as a utility

You pay for what you use and turn resources off when you are done. You are responsible for your costs.

At UC San Diego, cloud computing is not subject to indirect costs.

Two important points to keep in mind about costs:

  • Cloud vendors such as Amazon and Microsoft are promoting cloud adoption by making research grants available. This means that you can easily apply for and obtain a year of cloud credit or Free Tier usage to explore using the cloud with little financial risk
  • An hour of compute time on a moderately powerful computer and a gigabyte-month of storage each cost about three cents, a starting point for thinking about cost. However, as use scales, so do costs.

Security of the cloud

The cloud is physically and programmatically secure, provided you take the appropriate precautions.

As part of our cloud consulting service we will help you develop, document and follow the necessary steps to secure your data. We provide a growing set of guidelines and procedures pertaining to cloud security that includes compliance with HIPAA regulations (UC has a BAA with AWS for HIPAA compliant instances) and we are available to help you determine what you need. Email us at aws@ucsd.edu.

Scalability of the cloud

Four elements make up the ‘cloud scale’ argument — how cloud computing resources scale to a given computational task. They include:

  • Machine types: Cloud vendors have many types of computers available to match your work: memory-intensive, compute-intensive, general purpose, small-scale, moderate, powerful, GPU-based and so on
  • Machine quantity: A parallelizable compute task can be scaled to multiple machines (hundreds or thousands) in order to complete the task in a short amount of time; this costs the same as using fewer machines and more time
  • Start-up latency: There is no wait for cloud resources to become available
  • Obstruction: Others are not blocked from doing their computational work when you are using the public cloud

Support for cloud computing

Like any new technology, using the cloud involves a learning curve. The key to adopting the cloud is making time to learn how to use it effectively. To help you evaluate whether that time investment will pay off in the long term, IT Services Research Computing provides:

  • Consultation
  • Tutorials
  • Links to excellent resources
  • Dedicated training courses
  • Direct contact with vendors

We work closely with the San Diego Supercomputer Center and UC San Diego Health System to support your needs.

Our goal is to help you overcome obstacles and make your path more about function and less about purchase orders, building hardware, fixing cooling problems, and updating operating system patches. We believe that AWS as a service can be a powerful tool to help you along that path.

In the cloud migration process, each case is unique. Sometimes cloud migration can be quite straightforward, but in cases where some additional help and training is needed, we are here to support you. Email us at aws@ucsd.edu.

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