The University of Illinois at Urbana-Champaign has signed a contract with Microsoft to be able to provide access to Microsoft Azure cloud resources. Ultimately, the goal is to create a system similar to the current Amazon Web Services at Illinois offering where University staff and researchers can procure Azure resources while staying aligned with the University’s needs. Now that we have a contract in place, Technology Services is currently working through the logistics required to provision Microsoft Azure resources and re-bill through the University. Continue reading
Amazon S3 has been in the news lately:
Top Defense Contractor Left Sensitive Pentagon Files on Amazon Server With No Password
Cloud Leak: How A Verizon Partner Exposed Millions of Customer Accounts
S3’s default configuration does not allow public access to the contents of a bucket, but these stories all feature bucket or object permissions that were open to the world. It’s evident that it’s a common mistake, but how can we avoid it? Continue reading
You can now launch G3 instances, the latest generation of Amazon EC2 Accelerated Compute Instances. G3 instances make it easy to procure a powerful combination of GPU, CPU, and host memory for workloads such as 3D rendering, 3D visualizations, graphics-intensive remote workstations, video encoding, and virtual reality applications. Continue reading
Below are a number of technical updates announced by Amazon Web Services (AWS) recently:
- FPGA nodes in Amazon Web Services (AWS) are now available
- Research IT and Technology Services continue to work with the University on getting the Terms and Conditions agreed to and contracts in place for Microsoft Azure and Google Cloud platform. For announcements visit http://cloud.illinois.edu.
- A new version of the AWS Deep Learning machine image was released in April. It includes popular deep learning frameworks, including MXNet, Caffe, Caffe2, TensorFlow, Theano, CNTK, Torch and Keras. It also includes popular packages including Jupyter notebooks with Python 2.7 and Python 3.4 kernels, Matplotlib, Scikit-image, CppLint, Pylint, pandas, Graphviz, Bokeh Python packages, Boto and Boto 3 and the AWS CLI. The Deep Learning machine image also comes packaged with Anaconda 2 and Anaconda 3 Data Science platforms. More information can be found at https://aws.amazon.com/marketplace/pp/B01M0AXXQB
- The AWS Elastic Map Reduce (EMR) service, which provides tools such as Hadoop, Spark, Hbase, Presto and Hive, updated to versions of Presto (0.170), Apache Zeppelin (0.7.1), and Hue (3.12.0) on Amazon EMR release 5.5.0. Presto 0.170 includes support for LDAP authentication and various improvements and bug fixes. Hue 3.12.0 adds new features to the SQL editor, timeline and pivot graphing for visualization, and email notifications for Apache Oozie workflow completion. https://aws.amazon.com/about-aws/whats-new/2017/04/updates-to-presto-apache-zeppelin-apache-flink-and-hue-now-available-on-amazon-emr-release-5-5-0/
The Technology Services Amazon Web Services (AWS) team is positioned to assist you with the AWS Cloud Credits for Research Program. Through this program, Amazon directly awards researchers credits for the use of AWS to enhance cloud-based research.
If you apply for credits, you are encouraged to inform the Tech Services AWS team by emailing firstname.lastname@example.org. Doing so allows the Tech Services AWS team, and its Amazon Account Managers, to assist with the AWS process and improve chances of credits being awarded.
The AWS Cloud Credits for Research Program is specifically designed to award credits to those researchers who:
- Build cloud-hosted publicly available science-as-a-service applications, software, or tools to facilitate their future research and the research of their community.
- Perform proof of concept or benchmark tests evaluating the efficacy of moving research workloads or open data sets to the cloud.
- Train a broader community on the usage of cloud for research workloads via workshops or tutorials.
The program is not oriented towards providing credits in support of ongoing operations.
Proposals are reviewed once a quarter by research experts at AWS and awarded amounts are in the form of promotional credits to be used on AWS services. The quarterly deadlines for submitting grant applications are:
- March 31
- June 30
- September 30
- December 31
Decisions are typically communicated 2-3 months following the respective quarterly deadline.
To apply visit https://aws.amazon.com/research-credits/.