“The data tsunami is changing everything in science. Every discipline is now confronted with it—a vast exploration of data that comes from instruments, from online sources, from the web, from social media. Analyzing this data can’t be done on a PC.”

— Dennis Gannon, director of Cloud Research Strategy for Microsoft Research Connections

This module will discuss five fast ways to make the cloud work for your research. Common use cases for the NeCTAR Research Cloud and the research outcomes they can enable will be described.

Video

The following video goes through the content in this module.

The Research Cloud

The Research Cloud provides the necessary processing power and storage that is required for computationally and storage intensive projects. That means the users of the application do not need to have huge processing power or storage capabilities locally. Cloud computing allows us to eliminate the use of standalone machines and provides all parties equal access to the models and data on a standard platform.

The NeCTAR National Research Cloud empowers researchers with new self-service abilities to publish research data, share knowledge and rapidly deploy and access software applications without the burden of operating their own computer servers.

The NeCTAR Research Cloud Services provide an Infrastructure-as-a-Service (IaaS): Researchers can run their own virtual machines and manage their storage.

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The Research Cloud uses the successful, open-source OpenStack cloud computing software platform. OpenStack includes compatibility with Amazon EC2 (Amazon’s computing service) and Amazon S3 (Amazon’s object storage service) APIs and thus client applications written for Amazon Web Services (AWS) can be used with OpenStack and NeCTAR Services with minimal porting effort, but it is recommended to use the native OpenStack APIs for access to all the NeCTAR cloud features.

To illustrate a few examples in which you may benefit from using the Research Cloud, we will discuss a few common use cases in this Module.

Conventions

The notation throughout the training documents can be interpreted as follows:

Words in italics are used for names and terminology, e.g. name of a software, or name of a computing concept. It may also just emphasise a word in the traditional way. Quotations are also written in italics and are put in between quotatioin marks.

Words in bold are used to highlight words which identify important concepts of a paragraph, to make it easier for users to skim through the text to find a paragraph which explains a certain idea, concept or technology.

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Additional information which is optional to read is displayed in info boxes like this one.

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Important information is displayed in boxes like this one.

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Definition of terms are displayed in boxes of this style.

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Possibly specific prerequisites for reading a particular section are contained in this type of box at the beginning of a section.