5 minute lightning rounds
How the Cloud is living up to its promise in Cornell Student Services – Phil Robinson
Might have the largest apps portfolio at Cornell – around 190 apps and sites, POS systems, etc. Compliance requirements including HIPAA. Pain points include lots of technical debt from inherited tech. Lots of time spent keeping up with server patching and upgrades. Looking to leverage elasticity to match student cycle spikes. Built a class roster with scheduler on AWS – scaled to over 1k simultaneous users in July, then scaled down. They have 10 apps in production in AWS. Identified an inspired team member to act as champion, prioritized cloud solutions. “Automate like crazy”
Using AWS workspaces for Graduate Students in applied social sciences – Chet Ramey & Jeff Gumpf (Case Western)
pilot project to test virtual desktops via AWS Workspaces. Department was eliminating a computer lab as building was being remodeled. Workspaces are easy to provision, manage, and use on multiple devices. Each person gets a Workspace, provisioned with stats software and other tools in Spring 2016, paid for by central IT. Originally planned for 3 courses and 26 students. Initial setup took about one hour. After first week of operation the pilot was expanded to 6 courses and 110 workspaces. Users were provisioned through the AWS Console. Built a master Workspace, created an image and two bundles from it, and used them to provision users. Problem with SPSS installer – won’t run on Windows Server. Got around that. Included Google Drive client for storage. About $150/student/semester, but with new AWS hourly pricing would be ~ $80.
Bringing IT Partners on Campus Along For the Ride – Susan Kelley (Yale)
Technology Architecture Committee – govern design and architecture, approve POCs, encourage documentation of strategies, working groups. Reviewed 31 projects in the last year. Formed a Cloud Working Group – 8 central IT staff and 7 IT partners. Decision 1: AWS and Azure. Med School helped with how to interpret Azure bills. School of Architecture wanted to get out of managing servers locally – used as test case for VPC, within one year migrated all their infrastructure to cloud. Now they go around telling other IT teams what they learned.
Securing Research Data: NIST 800-171 Compliance in the Crowd – Bob Winding (Notre Dame)
Lots of work will need to be compliant by end of 2017. Research that contains “controlled, unclassified information” – ITAR. Held a workshop with AWS and several other schools. Worked to create a Quickstart Guide and a Purdue Educause paper. GovCloud and Quickstart cover about 30% of the controls mandated. GovCloud is US persons only region, so that helps. Providing a VDI/RPC gateway in the Shared Services VPC – VDI client is the audit boundary. As long as you run on University-managed equipment you have an isolated environment. Still process-intensive, but you don’t have to worry about infrastructure.
Cloud Adoption: A Developer’s Perspective – Brett Haranin
Cost Engineering in AWS: Do Like We Say, Not Like We Did – Ben Rota
- Be careful that your people don’t confuse “cheap” with “free”
- For cost estimates, you generally only need to worry about RDS, EC2, and S3
- Easiest way to save money is to shut down what you don’t need (engineers aren’t used to doing this on premise)
- Enforce tagging standards that help you understand your spend (including tags for testing)
- Look out for unattached storage
- Consider over-provisioning storage rather than buying PIOPS
- Multi-AZ RDS instances are a low-risk way to get into RI purchases
- Real bang for buck in RI purchases is to do them at all
How to do? Set up Trusted Advisor or third party tool to help get the view of what’s going on.
Dirty Dancing In The Cloud – Scotty Logan
Why are we moving to the cloud? Geo-diversity, scalability, etc. Don’t forklift to the cloud. “Go Cortez” – burn your boats behind you. Go to new stuff, DevOps, CI, CD, etc. But you still have FIrewalls, IP Addresses – tightly coupled. Use TLS and client certs instead … but my CISo says we need to use static IPs and VPNs! If you have to, use NAT Gateways (AWS Service)… until you can get to the happy place.
Jetstream: Bob Flynn (Indiana)
Expanding NSF XD’s reach and impact. 70% of NSF researchers claimed to be resource constrained. Jetstream is NSF’s first production cloud facility. Infrastructure running Indiana and Texas, with dev at Arizona. Built on OpenStack. For researchers needing a handful of cores (1 to 44), devs, instructors looking for a course environment. Set of preconfigured images (like AMIs) to pick from. Went live September 1, over 125 XSEDE projects. NSF soliciting allocation requests, including Science Gateways. jetstream-cloud.org
Research Garden Path Case Studies – Rob Fatland (Washington)
CloudMaven – a github repo. Don’t recreate solutions. Has AWS procdurals. Has page on HIPAA compliance.
Prototyping library services using high performance NoSQL platform Erik Mitchell (Berkeley)
Costs about $8 per book to put it in a storage facility. Looked at levels of duplication across two libraries and 27 fields = 378 million data items to compare. Looked at big data solutions. Used BigQuery on Google – NoSql database with a GUI and SQL-like query language. Was able to analyze the data easily and discovered lots of places to save effort and money. Not everything needs to be an enterprise service, if the cloud service is easy enough to use at a local level.
Umbrellas for a Rainy Day: Cloud Contracts and Procurement – Sara Jeanes (Internet2)
In the world of cloud, ” contract is king” – all you own is the contract. Typical procurement processes are long and cumbersome – doesn’t work for the cloud. Challenges: Timeliness, Risk Management, Price Variability, Pilots and Trials. Possible solutions: Consortia, “piggybacking”, Community communication and collaboration
Red Cloud and Federated Cloud – Dave Lifka (Cornell)
Talked to lots of researchers – they liked everything a la carte – cheap computing on demand, with no permanent staffing or aging hardware. Built Red Cloud, a Eucalyptus stack (100% AWS compatible so you can burst). Gave each of them root, but then they built a subscription model and a for-fee service building VMs for researchers. Available externally as well as internal to Cornell. Aristotle – data building blocks. Bursting to other institutions and then AWS. Building an allocation and accounting system. It’s about time-to-science. Portal to tell people what resource they can get when and at what cost.