This document discusses quality management for service-based systems and cloud applications. It begins with quotes from Aristotle about how constantly performing certain actions can lead one to acquire particular qualities. It then discusses the need to manage how cloud services act in order to ensure quality. The document provides an overview of a proposed quality management architecture, including concepts like quality models, monitoring tools, and execution environments for analytics. It also reviews some existing quality models, monitoring techniques and tools, and cloud management platforms. Finally, it outlines next steps around designing and testing a complete quality management example.

1. Quality Management in
Service-based Systems and
Cloud Applications
WP4 Quality Management and
Business Model Innovation
RELATE-ITN
Dr. Jose María Alvarez-Rodríguez
Research Fellow, SEERC
Prague, 19-04-2013

2. “Cloud-based services acquire a particular quality by
constantly acting a particular way... they become just by
performing just actions, temperate by performing
temperate actions, brave by performing brave actions.”
16/04/2013 Prague, Czech Republic #2
Aristotle
“Men acquire a particular quality by constantly acting a
particular way... you become just by performing just
actions, temperate by performing temperate
actions, brave by performing brave actions.”
…we need to manage this particular way of acting!
Some time ago…

3. Which kind of quality do you prefer?

4. 16/04/2013 Prague, Czech Republic #4
I need help…
I have a mobile application that needs a Geocoding service and
the response time must be in milliseconds.
• More than 54 geocoding APIs
– How can I select the most suitable service?
– How can I compare different providers?
– How can I track the quality (response time) of the selected
service?
– …
http://blog.programmableweb.com/2012/06/21/7-free-geocoding-apis-google-bing-yahoo-and-mapquest/

5. Context
 A growing offering of cloud services
 …more complexity
…new needs and requirements
 Cloud Management for…
 Cloud models and types
 Track and control my third-party dependencies
 Context-aware quality dimensions/indicators/metrics
Security, storage, etc.
Subjective experience
 …to improve, optimize and accomplish…
 efficiency, costs, SLAs, etc.
 by means of providing advanced services
 Analytics/Prediction/…
#516/04/2013 Prague, Czech Republic

6. #6
Cloud
Computing
On-
demand
self-service
Broad
network
access
Resource
pooling
Rapid
elasticity
Measured
service
Source: The NIST Definition of Cloud Computing
?
What kind of service we want to track…
What kind of characteristics are
applicable to that service…
What kind of operation should
be deliver…
alert service, analytics, prediction?
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7. What is “Quality”?
Classical view
Dimensions
 Tangibles
 Reliability
 Responsiveness
 Service assurance
 Empathy
 Others…
 Competence
 Credibility
 Security
 Access
Gaps
 Consumer expectation and
management perception
 Management perception
and service quality
specification
 Service quality specification
and service delivery
 Service delivery and
external communication
 Expected service and
experienced service
#716/04/2013 Prague, Czech Republic

8. #8
Monitoring tool
(execution environment)
Continuous
assurance
Analytics Prediction
Quality
Model
Customer
Profile
Cloud Service
Profile
Mapping &
configuration
Type of
operation
Dashboard
-Abstraction+
…
Domain
knowledge
High-level
tools
Built-ins
services
+Executable-
……
… …
16/04/2013 Prague, Czech Republic
Overview of
a QoS Management Architecture

9. State-of-the-Art
 Cloud Management Application Platforms
 QoS Models
 Monitoring tools and techniques
 Execution environments (Big Data analytics)
#9
…
* Rodríguez, J. M. A; Kourtesis, D.; Paraskakis, I. Semantic- based QoS management in Cloud Systems: Current Status and Future Challenges. Future Generation
Computer Systems, Special Issue on Semantic Technologies and Linked Data over Grid and Cloud Architectures. IF: 1.978 (2012). (Under review).
…
16/04/2013 Prague, Czech Republic

10. http://www.cloudyn.com
http://www.rightscale.com/ http://www.enstratius.com/
http://scalr.com https://www.cloudexpress.com/
https://app.cloudability.com/analytics

11. #1116/04/2013 Prague, Czech Republic

12. Some existing
QoS models…
#1216/04/2013 Prague, Czech Republic

13. #13
Some existing
monitoring techniques and tools…
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14. Approach
#14
• Concepts & relationships
• Dimensions, indicators and metrics
• Service and Customer profile
• Reuse of existing vocabularies and standards
Abstract Model of Qos Management
• Standard, common and shared data model
• data integration through semantic technologies
• Configuration
• Dashboard
• Qualify Functions deployment (aggregation operators)
Mapping and High-level tools
• Monitoring tool
• Continuous queries
• Connection to data sources
• ~Google analytics or Google Trends for QoS in cloud systems
Execution
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15. 16/04/2013 Prague, Czech Republic #15
Partial Data model
Overview
*Reuse of existing models and standards are not included.

16. 16/04/2013 Prague, Czech Republic #16
I still need help…
I have a mobile application that needs a Geocoding service and
the response time must be in milliseconds.
• More than 54 geocoding APIs
– How can I select the most suitable service?
– How can I compare different providers?
– How can I track the quality (response time) of the selected
service?
– …
http://blog.programmableweb.com/2012/06/21/7-free-geocoding-apis-google-bing-yahoo-and-mapquest/

17. 16/04/2013 Prague, Czech Republic #17
My Profile (partial)

18. 16/04/2013 Prague, Czech Republic #18
A Provider Profile (partial)

19. Key points
 Represent providers and my own QoS features in a
common, shared and standard way
 to be able to consume and make comparisons (information and data):
 E.g. compare metrics with different units, seconds and milliseconds
 Map providers API information to the QoS model
 Connectivity parameters
 Data
 Deploy the quality function and Track the services with the
monitoring tool
 Select “the best” according to my target profile
#1916/04/2013 Prague, Czech Republic

20. #2016/04/2013 Prague, Czech Republic

21. * A toy example of monitoring the
use of words in Tweeter
#21
Storm
Trident
Real-
time
views
Batch
views
Storm
Trident
Algorithms Sync
Registered Queries
(Quality Functions)
Results
Monitoring tool
16/04/2013 Prague, Czech Republic

22. Benefits
#22
• Integrated and Unified view of QoS
• Extensibility
Abstract Model Qos Management
• Standard, common and shared data model (maybe semantically-based )
• (Semi)-Automatic deployment of Quality Functions
• Expressivity and Analytics
Mapping and High-level tools
• Real time capabilities
• Big Data processing
• Flexibility & scalability
Execution
16/04/2013 Prague, Czech Republic

23. Open Questions
#23
Motivating
Scenario
• Bottom-up
approach
Design a QoS
model
Select cloud
type and model
Design
management
services
Execute and
test
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24. Situated QoS
#24
… can a broker take advantage of the QoS
management?
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25. Research Questions
 Which are the concepts and relationships to take into account
in QoS management?
 subjective and objective
 Which services must be provided to exploit domain
knowledge and which algorithms are necessary to afford
those services?
 How can we deal with the processing of heterogeneous data
streams (Big Data) in real-time?
 How can we find services according to customer profile
(matchmaking)?
 How can we exploit the historical information and feedback
the domain knowledge?
#2516/04/2013 Prague, Czech Republic

26. Next Steps
1. Design and deploy a complete example (iteratively)
1. Design a simple model covering some QoS features
2. Map the model and QoS features to 1 service and n providers
3. Deploy (semi-automatically) the quality function in the monitoring tool
4. Improve the monitoring tool
5. Check results
2. Go in-depth in the concept of “Quality” and “Measured
service”
3. Look for synergies
4. Design of experiments and writing
1. Can I easily extend the QoS model? (extensibility)
2. Can I design and deploy quality analytic functions more fast? (expressivity)
3. Can I meet (first) the “customer” requirements? (flexibility & scalability)
#2616/04/2013 Prague, Czech Republic

27.  Publications
 Rodríguez, J. M. A; Kourtesis, D.; Paraskakis, I. Semantic- based QoS management in
Cloud Systems: Current Status and Future Challenges. Future Generation Computer
Systems, Special Issue on Semantic Technologies and Linked Data over Grid and Cloud
Architectures. IF: 1.978 (2012). (Under review).
 Others derivate of previous works (SCP and CHB journals)
 Talks
 Seminar at SEERC on the topic: “Towards a Pan – European E-Procurement Platform to
aggregate, publish, and search public procurement notices powered by Linked Open
Data: The Moldeas Approach”. 22 February 2013.
 PC member and reviewer
 PC member DATAWEB (PCI 2013), ETAS 2013, ICOHT 2013 and DMoLD workshop
 Reviewer of JCR Journals: FGCS, ESWA and Current Topics in Medicinal Chemistry
 Technical Development Editor in Manning Co.
 Member of the Advisory Board in two books of IGI-Global.
 Training
 Seminar on OpenTosca
 Prototypes
 An early prototype of a real-time platform for dealing with data streams and execute simple rules is
now available (documentation and source code).
#27
Activities
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28. Summary

29.  M. Maiya, S. Dasari, R. Yadav, S. Shivaprasad, and D.S.
Milojicic, "Quantifying Manageability of Cloud
Platforms", ;in Proc. IEEE CLOUD, 2012, pp.993-995.
 “A Runtime Quality Measurement Framework for Cloud
Database Service Systems”, 8th Int. Conf. on the Quality of
Information and Communications Technology //
Lisbon, Portugal, 2012
 N. Marz and J. Warren, “Big Data Principles and best practices
of scalable realtime data systems”, Manning
Publications, 2013.
#29
Main References
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30. Questions
Thank you for
your attention!

31. Credits
• Acknowledgements
– SEERC
• CONTACT AND RESOURCES
– E-MAIL: JMALVAREZ@SEERC.ORG
– WWW: http://josemalvarez.es
– http://www.slideshare.net/josemalvarez
• Pictures
– https://moqups.com
– NIST, Gartner, FP7 Europe, FLICKR
– Cloud vendors
• License
– http://creativecommons.org/licenses/by-nc-sa/3.0/es/

32. #32
Public Hybrid Private
SaaS
PaaS
IaaS
Control and governance
Abstraction
Economies of scale
Flexibility
16/04/2013 Prague, Czech Republic

33. #33
Private
(On-Premise)
Storage
Server HW
Networking
Servers
Databases
Virtualization
Runtimes
Applications
Security & Integration
Youmanage
Data / Users
Infrastructure
(as a Service)
Storage
Server HW
Networking
Servers
Databases
Virtualization
Runtimes
Applications
Security & Integration
Managedbyvendor
Youmanage
Data / Users
Platform
(as a Service)
Storage
Server HW
Networking
Servers
Databases
Virtualization
Runtimes
Applications
Security & Integration
Managedbyvendor
Youmanage
Data / Users
Software
(as a Service)
Storage
Server HW
Networking
Servers
Databases
Virtualization
Runtimes
Applications
Security & Integration
Managedbyvendor
Data / Users
Youmanage
Source: “Cloud Manageability”, Michael Epprecht , Microsoft Corp.
16/04/2013 Prague, Czech Republic