We’ll be holding free AWS labs throughout the Fall semester. Here’s the full schedule of dates. Times and locations will be updated when available:
- July 12
- July 19
- August 9
- August 23
- September 13
- September 27
During each lab session, you’ll have your choice of topics:
- AWS 101: Introduction to EC2
- Identity and Access Management
- S3 and CloudFront for content distribution
- Relational Database Service
- Automating AWS with CloudFormation
- Introduction to Lambda
- Building clusters with Alces Flight
- Elastic MapReduce
You may run through multiple labs if time allows. An Amazon solutions architect will be on-site with our local staff to offer technical assistance and discuss cloud topics.
Technology Services will grant you access to a shared AWS account for the lab; you don’t need your own. Computers will be available onsite, though you’re welcome to bring your own laptop if you prefer.
Registration will be available once times and locations are announced.
Do you have questions about how you can use Amazon Web Services (AWS) to enhance your research, storage, or website hosting? AWS will host a FREE seminar in Chicago on Wednesday July 26 and Thursday July 27 at the McCormick Place Lakeside Center. To register online or see additional details visit https://aws.amazon.com/summits/chicago/.
This summit is a great, low-cost way to attend technical sessions and workshops, bootcamp training events, and labs. AWS engineers, solutions architects and AWS partners will be present and available throughout the event.
Onsite registration begins at 7:30am on Wednesday followed by labs and the keynote presentation at 9:30am.
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 email@example.com. 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/.