(ISM203) Enterprise Cloud Adoption Strategies in Higher Education

© 2015, Amazon Web Services, Inc. or its Affiliates. All rights reserved.

Sri Elaprolu - Manager, Solutions Architecture, Amazon Web Services

Mandie Chapman - Senior Business Systems Analyst, University of Michigan

Christopher Malek - Manager of Academic Development Services, California Institute of Technology

October 2015

ISM203

Enterprise Cloud Adoption

Strategies in Higher Education

What to Expect from the Session

• Why AWS for education

• Practical advice on how to begin the journey

• Adoption strategies and frameworks

• Lessons learned

Cloud is becoming the New Normal

Time to ResultsAccess infrastructure

in minutes

Low CostPay-as-you-go pricing

ElasticEasily add or remove capacity

Globally AccessibleEasily collaborate with users around the world

SecureA collection of tools to

protect data and privacy

ScalableAccess to effectively

limitless capacity

Why Do Education Customers Love Using AWS?

Business of Education

• Public & departmental websites

• Development & test environments

• ERP systems

• Data analytics

• Student information system software

• Disaster recovery

• Data center migrations

• Storage & backup

• UND migrated website and global student and

faculty authentication store to AWS with plans to

move 80% of its workloads in the next three years.

• UND Reports 40% savings on IT operational costs

annually.

We are confident in saying that

the AWS infrastructure has

performed exactly as intended.

Sharif Nijim

Enterprise Application Architect,

University of Notre Dame

”

“

Supporting Business of Education (Examples)

University of Maryland University College (UMUC) needed to replace its

legacy applications and decided to use AWS to run its new analytics

platform as well as several administrative workloads. By using AWS,

UMUC improved the performance of its analytics platform by twentyfold

and enabled its engineers to focus on building new applications instead of

managing IT infrastructure.

Ivy Tech Community College of Indiana is the largest community college in

the United States. About 170,000 students register for classes each year;

school maintains a student database with about 1.7 million records. School

needed to scale existing systems, including operational data store (ODS). By

leveraging AWS: Queries complete in as little as three seconds, down

from 40 minutes; Licensing and monthly operational costs are about 60

percent less.

http://www.umuc.edu/

http://www.ivytech.edu/

Online Teaching / Learning Solutions

• Lecture capture

• Learning / course management systems

• Distance learning

• Massive open online courses (MOOCs)

• Student lab environments

• Virtual desktop / virtual application delivery

• 21st century learning & collaboration

• With more than 300 classes on its website,

Coursera needed to track student data, store and

deliver videos, and enable students and teachers

to interact with each other

Teaching/Learning Use Cases on AWS (Examples)

• Using AWS, the company can dynamically handle

workload as two million students across 650 schools in

30 countries access the system

• AWS allows Echo 360 to deliver a reliably solution

globally at 30 percent less than what a customer would

be able to do on its own.

We could not scale our

business as seamlessly without

AWS – and we certainly couldn’t

do it on a global basis.

Tony Abate

COO, Echo360

”

“

Research on AWS

• Genomics research

• Statistical analysis

• Mathematical modeling

• Computational fluid dynamics

• Grid/cluster/high performance computing

• Carat is an application for mobile

devices that uses big data to

analyze energy productivity and

improve cell phone battery life

• By using AWS, UC Berkeley’s

researchers are able to focus on

research, analysis, and customer

service instead of administering

computing resources

Research Use Cases on AWS (Examples)

• The Biological Engineering Department scaled to meet

the demands of more than 6,000 users, who have

designed more than 50,000 synthetic DNA sequences

We can create an algorithm that

can take 32, 64, 128 different

cores, and make it accessible to

anyone in the world.

Howard Salis

Ph.D., Assistant Professor, Penn State

”

“

Global Impact Initiatives for Science

AWS Research Grants AWS Hosted Public Datasets

•Dedicated team focusing on scientific computing & research workloads

•Globally focussed and engaged in big science projects like theSKA.

•Leveraging AWS resources all over the world.

•Ensuring the cloud is able to make a disruptive impact on science.

AWS SciCo Team

• Grants to initiate & support development of cloud-enabled technologies.

• Typically one-off grants of AWS resources like Amazon EC2 (compute) or Amazon S3 & Amazon EBS (storage), or more exotic like Amazon Kinesis & Twitter feeds.

• Frequently results in reusable resources, like AMIs or open data, which we strongly encourage.

• Lowers the risk to try the cloud.

• Large and globally significant datasets hosted and paid for by AWS for community use.

• Data can be quickly and easily processed with elastic computing resources in the surrounding cloud.

• AWS hopes to enable more innovation, more quickly.

• Provided in partnership with content owners, who curate the data.

Peering with Global Research Networks

Image courtesy John Hover - Brookhaven National Lab

Universities All-In on AWS (Examples)

Labs and training on

cloud topics and AWS

products

Open course content by

leading professors and

AWS

Grants for free

usage of AWS

services

Communities that

share best practices

virtually and in person

We invite you to join AWS EducateAccelerate cloud learning with AWS credits, cloud training,

course content, and collaboration tools

Not a student or educator? Help extend AWS grants to more students by inviting your network to participate (#awseducate).

Learn more at: www.awseducate.com

http://www.awseducate.com/


Mandie Chapman and Chris Wood

October 2015

University of MichiganCloud adoption strategies at a

decentralized university

The University of Michigan

Established in 1817, located in Ann Arbor, Michigan

19 schools and colleges

22 non-academic departments

28,395 undergraduate students

15,230 graduate students

7,701 faculty

31,495 staff

Information and

Technology Services - Two

Roles

1. Cloud service provider

2. Cloud service adopter

Cloud

Foundational

Strategy

CO

E

PHR

LSA

ITS

SP

H

A&D DE

NT

ME

D

SNR

E

KIN

E

SMT

D

LA

W

SOE

RO

SS

PH AdministerConsult

IntegrateEnable

Enable campus to focus on the

mission of their business through

the use of cloud services

Flexible

Easy Cost EffectiveSecure

AgilityInnovation

Strategy – How Do We Help Adoption?

Enable AdministerConsultIntegrate

Provide contract,

University billing; develop

user groups, communities

of practices, and training

materials

Provide integration from

cloud vendors to local

data via secured networks

Provide in-depth

knowledge on chosen

cloud vendors including

best practices, solution

design, financial impact

assessment, migrations,

and implementation

Configure, operate,

maintain, and monitor

cloud solutions

Culture - Who Is Driving Cloud Adoption?

Leadership

Central IT driving leadership

• Articulate value proposition

• Cost/flexibility/scale

• Faster innovation

Leadership driving central IT*

• Understand drivers

• Security/compliance

• Political drivers

• Institutional reputation

*UM – Leadership is driving central IT

Campus

Central IT driving campus

• Understand campus constraints

• Budget/funding model

• Staff resources

• Trust/security

Campus driving central IT*

• Understand drivers

• Enable/not obstruct

• Need and speed (bi-modal IT)

*UM – Campus is driving central IT


IT Staff

Central IT driving IT staff

• Understand IT staff perspective

• Job security

• Loss of control

• Skill set gaps

IT staff driving central IT

• Understand consequences

• Loss of talent

• Viewed as slow to change


Education – How Can We Help?

What does

leadership

need

What does

campus need

What do IT

staff need

Retooling and

training in

cloud services

Develop a

training plan

for campus

Elevator

speech

Structure/Staffing – Order Matters

Strategy Structure Staffing

Develop your cloud

adoption strategy

Evaluate organizational

structure

• Siloed

• DevOps

• Shared

Unified team vs

technology domains*

Adjust your staffing

needs

• Architects

• Cloud Consultants

• Cloud Administrators

*UM – Unified team is our direction

AWSMicrosoft

AT&T

Rackspace

Google

IBMHP

CiscoVMware

Technology

Leverage industry advisors

CenturyLink

Verizon

Specialize on a few

select cloud

providers with proven

track records

Recommendations

1. It’s never too late to set your strategy

2. Consider your culture. “Culture eats strategy for breakfast” - Peter Drucker

3. Cost isn’t everything

4. Invest in educating your staff

5. Be deliberate, have dedicated resources

6. Understand your financial model and the impacts of moving to the cloud


Christopher Malek, Manager of Academic Development Services, Caltech

October 2015

Caltech in AWSMore with less

• California Institute of Technology

• Pasadena, CA

• Top-tier university: #1 in Times

Higher Education world rankings

• Small: 6400 people (1000

undergrads, 1200 grads, 300

faculty, 3900 staff)

• 3:1 undergrad-faculty ratio

• JPL: Founded by Caltech in 30s,

managed for NASA since 1958

Academic Development Services

• Part of IMSS, the central IT org

• Lean, 6 people, all developers, even management

• 35 years of collective systems administration experience

• 50 years of collective development experience

• ~130 websites and web applications, including www.caltech.edu and the

campus intranet portal

• Much smaller than counterparts at peer institutions

Our job: Enable research and instruction through software

http://www.caltech.edu/

Small School, Big Needs

Top-tier school with small-school resources

• Fewer people and resources than our peers

• Have same needs as those peers, though

• Many vendors historically out of our price range

• Lack of resources caused Caltech to appear behind peers IT-wise

Caltech Before the Cloud: DIY

• Engineering in an environment of scarcity

• DIY or not do it

• Much effort on maintaining low level services

• Storage systems, backups, firewall, hardware, file services,

virtualization system, etc.

• Complicated, slow to deploy new services

• Much time spent not actually solving customer problems

Cloud Adoption (2010)

Upper management pro-cloud

Operations not pro-cloud

Primary concerns: information security, changing

operational procedures, learning curve, time

Strategy: DevOps, public data, Field of Dreams model

Timeline

Mar 2011

www.imss.caltech.edu

•Drupal 6, media in

Amazon S3

•Multi-AZ

•Amazon EC2

•ELB

•Amazon RDS

•More tooling

Apr 2011

www.caltech.edu

•The “secret” upgrade

•Drupal 6, media in

Amazon S3

•Multi-AZ

•Amazon EC2

•ELB

•Amazon RDS

•First among our peers

Oct 2012

www.caltech.edu 2012

•Drupal 7,

Amazon S3-backed

•Auto Scaling groups

•Multi-AZ

•Amazon CloudWatch

•Amazon SNS

•ElastiCache

•Amazon RDS, ELB,

Amazon EC2

http://www.caltech.edu/

Oct 2013-2015: Divisions and Admissions

More site rollouts

•Drupal 7,

Amazon S3-backed

•New web services

•Auto Scaling groups

•Multi-AZ

•Amazon CloudWatch

•AWS CloudFormation

•Amazon SNS

•Amazon RDS, ELB,

Amazon EC2

Current Projects

Move intranet portal to cloud• VPC with tunnel to campus

• Leverage Docker and Amazon ECS for deployment and scaling

• Much infrastructure migrating to VPC: LDAP, Shibboleth, Syslog

• Tighter ties to our on-campus infrastructure

Move hosted CMS service to cloud• About 100 sites

• Amazon ECS, Amazon S3

What We Gained

Agility

Utility pricing, programmable infrastructure, post-scarcity

• Low cost to try things out

• Adapt quickly

• Evolve processes

• Clone environments

• Enabler for DevOps

New Capabilities

Costly or impossible to do ourselves

•Multi-AZ

•Elastic Load Balancing

•Amazon S3

•Amazon ECS

•Auto Scaling

•IAM

•AWS CloudFront

•Amazon EFS

•Etc.

Focus on Our Value

Leverage AWS scale and expertise

•AWS better than us at many things

•Don’t have to run low level services

•Allows us to concentrate on how we add value

Cloud Adoption (2015)

5 years now in AWS; ~90 instances

Upper management still pro-cloud

Operations very pro-cloud

Field of dreams model worked

Lessons

Upper management support was critical

Customer support and trust was also critical

Caltech’s small size helped

Team’s particular expertise helped

Take baby steps and choose low hanging fruit first

Learning curve is long; dedicate people and time to it

Expect to do it wrong and then adapt

Be prepared to rethink the way you do things

Remember to complete

your evaluations!

Thank you!