Robert E. Gillen

AWS has been in the cloud computing space longer than most anyone, and they are the de facto standard when it comes to Infrastructure as a Service. While most developers are comfortable with the notion of virtual machines, reviewing the AWS offering can sometimes look like alphabet soup (EC2, S3, SNS, SDB, SQS). Join us to learn the power behind these acronyms and the tools that they can provide your next project. We’ll discuss the major components, some of the trade-offs between different implementation choices (i.e. boot from S3/boot from EBS, etc.) and provide you with the opportunity to work through some labs, deploy some code, and begin to experience the Amazon cloud for yourself. Examples are in .NET, but fundamental concepts apply to all platforms.

(Excerpt) Everyone (or so it seems) is talking about the cloud...
I have the privilege of being on the ground, working every day with these technologies and I’m seeing the actual transformation – the people who are beginning to embrace it, the scientists who are interested in using it, and some of the problems it has actually solved. Rather than hyping an idea or pushing a particular technology, I thought I’d take this opportunity to discuss some examples of the work we’ve been involved with and where we think it is headed.

In this paper we consider the problem of data movment in the Windows Azure cloud computing environment as a representation of similarly designed Platform as a Service (PaaS) infrastructures. We evaluate the standard application programming interfaces (APIs) and provided client libraries. We then consider various extensions to those APIs and libraries with the objective of maximizing the realized transfer rate. We explore these interactions both within the datacenter - a specific Windows Azure facility - as well as external to the datacenter. Specifically, we explore alternative transfer approaches such as data chunking, parallelization of data transfer threads, data proxies, and compression and provide evidence to suggest the appropriate scenarios in which to utilize these optimizations.

This talk was similar to some of the others I’ve given on the topic of using cloud computing for science but was specifically targeted to the audience at hand. This was one of four talks presented to a group of roughly 115 IT staff and researchers at the NASA’s Goddard Space Center.

We’ve all heard about Amazon’s S3 and EC2 platforms and we know that they are leaders in the cloud computing movement, but how accessible are they to the .NET developer? Come learn about the various SDKs, samples, and tools available to Microsoft Developer targeting the Amazon Cloud as well as tips and tricks for getting the most out of the platform.

Come learn about Microsoft’s Azure platform (and cloud computing in general) as we look at an application built to assist in the processing and publishing of large-scale scientific data. We will discuss architecture choices, benchmarking results, issues faced as well as the workarounds implemented. While your application may not be dealing with 35TB of numbers, this session will give you insight into the process of developing for the cloud, as well as tips and tricks to help you avoid some common pitfalls.

A variety of cloud computing platforms are emerging and there exist increasing calls for research to be performed utilizing these platforms. While the computational paradigms are improving and the platforms are, in fact, becoming increasingly viable for such research, significant issues remain surrounding the usage and movement of data (specifically large data) within these environments. If cloud computing as a paradigm is to deliver on its promise of democratizing large-scale compute by serving as a natural extension of the scientific workstation, significant effort must be applied towards the issues of data locality, presentation, and interaction. This talk assumes a layman’s perspective as work is reviewed illustrating challenges encountered while attempting to move and interact with large-scale data (subsets of the CMIP3 archive) within the cloud as well as from workstations outside of the cloud. Also discussed are issues surrounding the schism that exists between data formats that would be considered “Internet friendly” and those used in a variety of scientific research and how these formats exacerbate the problems surrounding data movement.

Come learn about Microsoft’s Azure platform (and cloud computing in general) as we look at an application built to assist in the processing and publishing of large-scale scientific data. We will discuss architecture choices, benchmarking results, issues faced as well as the work-arounds implemented. This session will give you insight into the process of developing for the cloud, as well as tips and tricks to help you avoid some common pitfalls.

A demonstration of how Windows Azure is being used to post-process climate data generated on the largest super computers in the world. We will also demonstrate data visualization tools that consume the post-processed data from Azure as a data service.

Come learn about Microsoft’s Azure platform (and cloud computing in general) as we look at an application built to assist inthe processing and publishing of large-scale scientific data. We will discuss architecture choices, benchmarking results, issues faced as well as the work-arounds implemented. This session will give you insight into the process of developing for the cloud, as well as tips and tricks to help you avoid some common pitfalls.

Have you been using the VS Extensions for SharePoint to create SharePoint packages and found yourself wondering how best to integrate with your source control platform and build system? Consistent packaging of SharePoint solutions can be a challenge and is not for the faint of heart. Come to this session and learn how our team utilizes TFS, Team Build, SandCastle, SharePoint Installer, and STSDev in concert to produce consistent installation packages for our SharePoint/MOSS environment.