Professional Education on Cloud Computing
Technology and Services Engineering

Yuri Demchenko
University of Amsterdam
CloudCom SCC-Computing Summer Symposium
21 June 2013, UiS, Stavanger

Outline• Cloud Computing Common Body of Knowledge (CBK)• Course instructional approach: Bloom’s Taxonomy andAndragogy• Course structure and mapping to general Cloud Services
Model (CSM)• Testbed, hands in and labs
• Practical realisation – University of Amsterdam• Next steps and discussion

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Cloud Education and TrainingSlide_2

Common Body of Knowledge (CBK)in Cloud Computing
CBK refers to several domains or operational categories into which Cloud
Computing theory and practices breaks down•

Still in development but already piloted by some companies, including industry
certification program (e.g. IBM, AWS?)CBK Cloud Computing elements
1. Cloud Computing Architectures, service and deployment models
2. Cloud Computing platforms, software/middleware and API’s
3. Cloud Services Engineering, Cloud aware Services Design
4. Virtualisation technologies (Compute, Storage, Network)
5. Computer Networks, Software Defined Networks (SDN)
6. Service Computing, Web Services and Service Oriented Architecture (SOA)
7. Computing models: Grid, Distributed, Cluster Computing
8. Security Architecture and Models, Operational Security
9. IT Service Management, Business Continuity Planning (BCP)
10. Business and Operational Models, Compliance, Assurance, Certification2013, Y.Demchenko

Cloud Architectures and Infrastructure
Services Prvisioning

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CKB-Cloud Components LandscapeCloud Platforms, API

Cloud Architectures, ServiceModels

Business/Operational Models, Compliance, Assurance

Cloud Computing Fundamentals
Cloud Services Engineering&Design
DesignEngineering

Virtualisation

Networking

Web Services, SOA

Security, ID Management

Computing Models: Grid, Distributed, Cluster

IT Systems Management

Cloud Computing Common Body of Knowledge (Full)

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Cloud Education and Training

4Multilayer Cloud Services Model (CSM) – Taxonomy of
Existing Cloud Architecture Models

Security InfrastructureManagementOperations Support System

User/Client Services* Identity services (IDP)* Visualisation

User/Customer Side Functions and Resources

Administration andManagement Functions(Client)

Content/Data Services* Data * Content * Sensor * Device

1Endpoint Functions* Service Gateway* Portal/Desktop

Access/Delivery
InfrastructureInter-cloud Functions* Registry and Discovery* Federation Infrastructure

SaaS

PaaS

Layer C5Services
Access/Delivery

Layer C4Cloud Services(Infrastructure,Platforms,Applications,Software)

Cloud Services (Infrastructure, Platform, Application, Software)

IaaS

Layer C6
User/Customer
side Functions

PaaS-IaaS IF
PaaS-IaaS Interface

IaaS – Virtualisation Platform Interface

Cloud Management
Software(Generic Functions)

Cloud Management Platforms
OpenNebula

Virtualisation Platform

OpenStack

KVM

VM

VM

OtherCMS

XEN

VMwareNetwork
Virtualis

Proxy (adaptors/containers) - Component Services and Resources

StorageResources

ComputeResources

Contrl&Mngnt Links

VPN

Hardware/PhysicalResources

Network
Infrastructure

Data Links

Layer C3
Virtual Resources
Composition andControl(Orchestration)

CSM layers(C6) User/Customer side
Functions(C5) Services
Access/Delivery(C4) Cloud Services(Infrastructure, Platform,Applications)(C3) Virtual Resources
Composition andOrchestration(C2) Virtualisation Layer(C1) Hardware platform anddedicated network
infrastructure

Layer C2
Virtualisation

Layer C1
PhysicalHardware
Platform andNetwork

Control/Mngnt Links

Data Links

Relations Course Components and CSM

Layer C6
User/Customer
side Functions

User Applications

Layer C5
Services
Access/Delivery

Cloud Services API and Tools

Hybrid Clouds,
Integrated Infrastructure

User Applications

1Cloud Service Design, Operational
proceduresManagementSecurityOperations Support System

Cross-layer
Service s (Planes)

Cloud/Intercloud Services Integration, Enterprise
IT infrastructure migration

1Customer Enterprise/Campus Infrastructure/Facility

Layer C4Cloud Services(Infrastructure,Platforms,Applications,Software)

Layer C3
Virtual Resources
Composition andControl(Orchestration)

Layer C2
Virtualisation

Cloud Services Platform

Cloud Service Provider
Datacenters and Infrastructure

Layer C1
PhysicalHardware
Platform andNetwork

Professional Knowledge in Cloud Computing• Professional level of knowledge (general) includes but not limited to– Knowing basic concepts and major application areas– Knowing similar concepts (and concepts inter-relation) and alternatives, as well as
application specific areas– Knowing basic technologies and their relation to basic concepts– Knowing authoritative (and not authoritative) sources of information and how toevaluate quality of information• Ability to work with standards (what is not an easy source of information)• Ability to critically evaluate and filter some inconsistent information, e.g. popular sites like
wikipedia and similar, blogs, etc.
• Critically evaluate vendors’ information which is sometimes biased and/or doesn’t provide
enough background information• Cloud computing is a new technology but it is becoming a common
preferred base/platform for all current and future developments• Becoming an expert in Cloud Computing– General professional knowledge and understanding of the main developmentareas– Practical development and experience with few projects, writing reports, technicaldocuments, following and contributing to standardisation– Cloud aware and cloud powered analysis and thinking
2013, Y.Demchenko

Cloud Architectures and Infrastructure
Services Prvisioning

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Professional Education in Cloud Computing Principles• Provide knowledge both in Cloud Computing as a newtechnology and background technologies• Empower the future professionals with ability to develop
new knowledge and build stronger expertise, prepare basis
for new emerging technologies such as Big Data
• Bloom’s Taxonomy as a basis for defining learning targets
and modules outcome• Provides a basis for knowledge testing and certification• Andragogy vs Pedagogy as instructional methodology for
professional education and training• Course format: On-campus education and training,
online courses, self-study
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Bloom’s Taxonomy – Cognitive ActivitiesKnowledge
Exhibit memory of previously learned materials by recalling facts, terms, basic concepts and answers••••Knowledge of specifics - terminology, specific facts
Knowledge of ways and means of dealing with specifics - conventions, trends and sequences, classifications and categories, criteria, methodology
Knowledge of the universals and abstractions in a field - principles and generalizations, theories and structures
Questions like: What are the main benefits of outsourcing company’s IT services to cloud?

Comprehension
Demonstrate understanding of facts and ideas by organizing, comparing, translating, interpreting, describing, and stating the main ideas••

Translation, Interpretation, Extrapolation
Questions like: Compare the business and operational models of private clouds and hybrid clouds.

Application
Using new knowledge. Solve problems in new situations by applying acquired knowledge, facts, techniques and rules in a different way•

Questions like: Which cloud service model is best suited for medium size software development company, and why?

AnalysisExamine and break information into parts by identifying motives or causes. Make inferences and find evidence to support generalizations••

Analysis of elements, relationships, organizational principles
Questions like: What cloud services are needed to support typical business processes of a web trading company? Give suggestions
how these services can be implemented with PaaS or IaaS clouds. Provide references to support your statements.

Synthesis
Compile information together in a different way by combining elements in a new pattern or proposing alternative solutions••

Production of a unique communication, a plan, or proposed set of operations, derivation of a set of abstract relations
Questions like: Describe the main steps and tasks for migrating IT services of an example company to clouds? What services and data
can be moved to clouds and which will remain at the enterprise premises.

Evaluation
Present and defend opinions by making judgments about information, validity of ideas or quality of work based on a set of criteria••

Judgments in terms of internal evidence or external criteria
Questions like: Do you think that cloudification of the enterprise infrastructure creates benefits for enterprises, short term and longterm?

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Cloud Education and Training

9Mapping Bloom’s Taxonomy from Cognitive Domain
to Professional Activity Domain•••••

Perform standard tasks,
use API and Guidelines
Create own complex
applications using
standard API (simpleengineering)
Integrate different
systems/components,
e.g. Cloud provider andenterprise (complexengineering)
Extend existing services,
design new services
Develop newarchitecture and models,
platforms andinfrastructures

Yuri Demchenko, 2013

Remember

Understand

Apply

CreateCloud Education and Training

Evaluate

Analyse10Mapping Course Components, Cloud Professional
Activity and Bloom’s Taxonomy
Customer Enterprise/Campus Infrastructure/FacilityApplicationAnalysis

User Applications
Cloud Services
API and Tools

1

Hybrid Clouds, Integrated
Infrastructure

User Applications

Comprehension

Cloud Service Design, Operational procedures

Knowledge

Cloud/Intercloud Services Integration, Enterprise IT
infrastructure migration

Taxonomy
Cognitive
Domain [3]Yuri Demchenko, 2013

Perform standard tasks,
use standard API andGuidelines

Create own complex
applications using
standard API (simpleengineering)
Integrate different
systems/components,
e.g. provider andenterprise infrastructure

Cloud Services Platform

Synthesis
Evaluation

Taxonomy
Professional
Activity Domain

Cloud Service Provider
Datacenters and Infrastructure

Cloud Education and Training

Extend existing services,
design new services
Develop new architecture
and models, platforms
and infrastructures11

Mapping Course Components, Cloud Professional
Activity and Bloom’s Taxonomy

Hybrid Clouds, IntegratedInfrastructure

Cloud Services
API and Tools

User Applications
User Applications

1

Cloud/Intercloud Services Integration, Enterprise IT
infrastructure migration

Cloud Service Design, Operational procedures

Customer Enterprise/Campus Infrastructure/Facility

Cloud Services Platform

Cloud Service Provider
Datacenters and Infrastructure

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Mapping Course Components, Cloud Professional
Activity and Bloom’s Taxonomy

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Pedagogy vs Andragogy
Pedagogy (child-leading) and Andragogy (man-leading)• On-campus and on-line education• Developed by American educator Malcolm Knowles, statedwith six assumptions related to motivation of adult learning:– Adults need to know the reason for learning something (Need toKnow)– Experience (including error) provides the basis for learning activities(Foundation)– Adults need to be responsible for their decisions on education;
involvement in the planning and evaluation of their instruction (Selfconcept)– Adults are most interested in learning subjects having immediate
relevance to their work and/or personal lives (Readiness).
– Adult learning is problem-centered rather than content-oriented(Orientation)– Adults respond better to internal versus external motivators(Motivation)
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Applying Andragogy to Self-Education and Online
Training - Problems• Andragogy concept is widely used in on-line education
but– Based on active discussion activities guided/moderated byinstructor/moderator– Combined with the Bloom’s taxonomy• Self-education (guided) and online training specifics– Course consistency in sense of style, presentation/graphics,etc– Requires the course workflow to be maximum automated• Especially if coupled with certification or pre-certification– Less time to be devoted by trainee• Estimated 1 hour per lesson, maximum 3 lessons per topic– Knowledge control questionnaires at the end of lessons ortopics
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Proposed Cloud Computing Course Structure
Basic parts & Advanced parts

Part 1.1. Cloud Computing definition and general usecases
Part 1.2. Cloud Computing and enabling technologies
Part 2.1. Cloud Architecture models and industry standardisation: Architectures overview
Part 2.2. Cloud Architecture models and industry standardisation: Standard interfaces
Part 3.1. Major cloud provider platforms: Amazon AWS, Microsoft Azure, GoogleApps, etc
Part 3.2. Major cloud provider platforms: Public, Research and Community Clouds
Part 4. Cloud middleware platforms: Architecture, platforms (OpenStack, OpenNebula),API, usage examples
Part 5.1. Cloud Infrastructure as a Service (IaaS): Architecture, platform and providers
Part 5.2. Cloud Infrastructure as a Service (IaaS): IaaS services design andmanagement
Part 6.1. Cloud Platform as a Service (PaaS): Architecture, platform and providers
Part 6.2. Cloud Platform as a Service (PaaS): PaaS services design and management
Part 7.1. Security issues and practices in clouds
Part 7.2. Security services design in clouds; security models and Identity management
Part 8 (Advanced). InterCloud Architecture Framework (ICAF) for Interoperability andIntegration: Architecture definition and design patterns
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Target Audience• Basic profile ("essentials" or “fundamentals”) is for IT
decision makers, informed users:– all concepts are explained, clouds opportunities are demonstrated,general use cases are analysed, examples of use are provided– general security issues in clouds are explained– intended the course will allow this group of listeners to be able tounderstand what they need to learn more.

• "Advanced" part is for engineers/practitioners developing
cloud services, and doing integration/consulting work:– different cloud architectures are explained, details on the different
cloud related open interfaces (like CDMI, OVF, OCCI) and proprietary
API (like Amazon AWS API) are provided, detailed overview of
popular cloud platform/middleware (like OpenStack, OpenNebula,Eucalyptus) is provided– security models (including main cloud providers) and technologies
explained, federated cloud identity and access control is explained– provide advice/suggestions where to look for further information
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Cloud Testbed to Support Education - Concept• Support education course on clouds and cloud based,e.g. Big Data, SDN (Software Defined Networks)– Basis for hands-in assignments and labs

• Support other courses/labs than can bemodeled/simulated using interconnected VMs
infrastructure– E.g., network technologies, web design, etc.

• Can be easily and fast setup for the course semesterand suspended after finishing course– Platform independence– Should also allow replication/burst to e.g. Amazon EC2 or othercloud platforms– May require some peripheral devices, network switches, also
remote sites
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Practical Realisation – University of Amsterdam• Prototype tested as Short Cloud Technologies lecture course in
Hong Kong Polytechnic University – 21-22 November 2012
– Motivated to approach more conceptually• Part of Computer Science and Software Engineering Master– Options: Colloquium (3-4 lectures); Summer course; Online self-training• Duration: 8 week (6 credits)– Starts January 2013
– 3-4 guest lectures• Content– Lectures: Papers review; Research Topics; Hands-in/Labs (Cloud lab,Amazon, Azure(?)) and mini-project• Knowledge control and Grading– Weekly questions (multiple choice; tricky)– Exam (TBD)– Research topics report and feedback

Yuri Demchenko, 2013

Cloud Education and Training19Research Topics (discussion topics)• Free selection of 32 proposed topics– Twin topics covering main research problems in Cloud
Computing– Initial description (orientation) and choice ofrecommended papers• 3-4 papers need to be found by students– For group of 2 students• Presentations and discussion (on week 4 & week 8)– Short summary submitted a week before– Feedback before presentation (short) and after
presentation
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Next steps and beyond clouds• Create online professional training course on Cloud
Computing• Development of the curricula on Data Intensive Science andTechnologies– Define technology and Common Body of Knowledge (CBK)• Reuse Cloud Computing curricula experience• Contributing to the Research Data Alliance (RDA)– BoF on Education and Training in Data Intensive Science andTechnologies at RDA1 meeting 18-20 March 2013 (Gothenborg)– Next RDA meeting and BoF 15-17 September 2013 (Washington)– Prospective Working Group @RDA and intension to submit a project
proposal to H2020 (special fiche #7 in Data/Sci Infrastructure section)• NIST Big Data Working Group
http://bigdatawg.nist.gov/home.php– Kickoff call next Wednesday 26 June 2013 19:00-21:00 (CET)

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Discussion and FAQ• Will MOOC change need for professional in-campus
education?
• Lectures vs Projects hands-on & Collaborative
learning in groups• Any other?

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