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Big Data as a Service: A
Neo-Metropolis Model
Approach for Innovation
Hong-Mei Chen, Rick Kazman
University of Hawaii
Serg...
Motivation
 Success in big data analytics depends on
having an infrastructure for:
 ingesting,
 processing,
 storing,
...
Motivation
 According to a 2013 Infochimps survey, 55%
of big data projects were not completed, due
to:
 technical roadb...
Solution?
 Many vendors are offering BDaaS platforms.
 However these are mostly proprietary, closed-
world.
 Choosing a...
Solution
 An open world model for developing a BDaaS
platform to
 integrate different open source technologies
 ease pr...
The Neo-Metropolis
Model
 Metropolis is the Greek word for “city.”
 The analogy is deliberate.
 The Metropolis Model, i...
Metropolis Model
Structure
Kernel
Periphery
Masses
Kernel
Periphery: Developers
Masses: Users
Open Source
Kernel
Periphery...
Neo-Metropolis Purpose
 A Neo-Metropolis (N-M) system reflects a
larger scale: it is a system of systems
platform.
 Inte...
N-M Characteristics
 Mashability
 Providing constituent systems as services.
 “Lego-blocks” approach: platform users cr...
N-M Characteristics
 Conflicting, unknowable requirements
 Requirements will always emerge from the
periphery => the ope...
N-M Characteristics
 Continuous Evolution
 Metropolis projects are never in a stable state
 The kernel might have tradi...
N-M Characteristics
 Focus on Operations
 Cloud services are called “the fifth utility”
 This requires a "DevOps" minds...
N-M Characteristics
 Sufficient Correctness
 Perpetual beta of the periphery is the norm
 But the kernel must be stable...
N-M Characteristics
 Scalable Resources
 The platform, hosted on a cloud (or
intercloud), provides scalable resources
 ...
N-M Characteristics
 Gated Behaviors
 A Metropolis system is subject to emergent
behaviors.
 This is often desirable.
...
N-M Principles
1. Community Engagement and Negotiation
2. Bifurcated Requirements
3. Bifurcated Architecture
4. Fragmented...
N-M Innovation
 These principles and characteristics support:
 Open innovation: participants—from the periphery
and the ...
Case Study: Cisco's
BDaaS Platform
 Cisco's mission is to increase their customer base via
a platform and vendor-agnostic...
An Example: Cisco
Realizing N-M Principles
 Community engagement and negotiation:
 for the edge, BDaaS customers are initially drawn
from ...
Realizing N-M Principles
 Bifurcated architecture / Bifurcated
requirements / Fragmented
implementation:
 Cisco is using...
Realizing N-M Principles
 Distributed testing:
 Cisco manages the testing of its kernel.
 Also exerts oversight on the ...
Realizing N-M Principles
 Distributed delivery/maintenance:
 automating repetitive and error-prone tasks (e.g.,
build, t...
Realizing N-M Principles
 Ubiquitous Operations:
 automating as much of operations as possible
 employing performance d...
N-M Innovation
 Innovation is supported by the characteristics
and principles of the Neo-Metropolis model.
 In particula...
N-M Innovation
 Components for big data applications (microservices)
developed so far include:
 Data Storage as a servic...
Conclusions
 This is just a single case study.
 However it is the evolution of trends that are driving
our software ecos...
Questions?
Big Data as a Service: A Neo-Metropolis Model Approach for Innovation
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Big Data as a Service: A Neo-Metropolis Model Approach for Innovation

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Presented at The Hawaii International Conference on System Sciences by Hong-Mei Chen and Rick Kazman (University of Hawaii), Serge Haziyev and Valentyn Kropov (SoftServe), Dmitri Chtchoutov.

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Big Data as a Service: A Neo-Metropolis Model Approach for Innovation

  1. 1. Big Data as a Service: A Neo-Metropolis Model Approach for Innovation Hong-Mei Chen, Rick Kazman University of Hawaii Serge Haziyev, Valentyn Kropov SoftServe Dmitri Chtchourov Cisco Systems
  2. 2. Motivation  Success in big data analytics depends on having an infrastructure for:  ingesting,  processing,  storing,  integrating, and  visualizing data  However, many companies fail to achieve this...
  3. 3. Motivation  According to a 2013 Infochimps survey, 55% of big data projects were not completed, due to:  technical roadblocks,  system complexity,  talent shortages,  heavy up-front costs
  4. 4. Solution?  Many vendors are offering BDaaS platforms.  However these are mostly proprietary, closed- world.  Choosing among them may limit the potential for innovation.
  5. 5. Solution  An open world model for developing a BDaaS platform to  integrate different open source technologies  ease prototyping and  broaden choices  allowing organizations to innovate while managing risk.  A model that we call Neo-Metropolis
  6. 6. The Neo-Metropolis Model  Metropolis is the Greek word for “city.”  The analogy is deliberate.  The Metropolis Model, introduced in 2009, helps us reason about system creation that is commons-based and peer produced.
  7. 7. Metropolis Model Structure Kernel Periphery Masses Kernel Periphery: Developers Masses: Users Open Source Kernel Periphery: Prosumers Masses: Customers Open Content
  8. 8. Neo-Metropolis Purpose  A Neo-Metropolis (N-M) system reflects a larger scale: it is a system of systems platform.  Intent: to make it easy for projects at the periphery to adopt, deploy, and scale systems.  A N-M system is an enabler.
  9. 9. N-M Characteristics  Mashability  Providing constituent systems as services.  “Lego-blocks” approach: platform users create systems by plugging together, configuring, and provisioning open-source components in cloud infrastructures.
  10. 10. N-M Characteristics  Conflicting, unknowable requirements  Requirements will always emerge from the periphery => the open source projects.  And they will always conflict.
  11. 11. N-M Characteristics  Continuous Evolution  Metropolis projects are never in a stable state  The kernel might have traditional releases, but the periphery is continually changing  …like a city…
  12. 12. N-M Characteristics  Focus on Operations  Cloud services are called “the fifth utility”  This requires a "DevOps" mindset.
  13. 13. N-M Characteristics  Sufficient Correctness  Perpetual beta of the periphery is the norm  But the kernel must be stable and backwards compatible.
  14. 14. N-M Characteristics  Scalable Resources  The platform, hosted on a cloud (or intercloud), provides scalable resources  These resources are managed by the kernel.
  15. 15. N-M Characteristics  Gated Behaviors  A Metropolis system is subject to emergent behaviors.  This is often desirable.  But gated behaviors are desirable in a Neo- Metropolis environment.
  16. 16. N-M Principles 1. Community Engagement and Negotiation 2. Bifurcated Requirements 3. Bifurcated Architecture 4. Fragmented Implementation 5. Distributed Testing/V&V 6. Distributed Delivery/Maintenance 7. Ubiquitous Operations
  17. 17. N-M Innovation  These principles and characteristics support:  Open innovation: participants—from the periphery and the edge—can interact dynamically, via the kernel, to generate “collective intelligence”.  The numbers game and “Lego” innovation: interoperability allows rapid mashups of services. More Lego blocks => more possible combinations.
  18. 18. Case Study: Cisco's BDaaS Platform  Cisco's mission is to increase their customer base via a platform and vendor-agnostic (primarily open source) approach to big data analytics.  “We don’t compete directly with Amazon; our strategy is to develop technology for microservices (higher up the stack) so that it can be deployed anywhere.”  “Public product cloud offering is not our core business; we want to invest in the internet in general, providing the capabilities for B2B interactions, e.g., Cisco’s Intercloud network.”
  19. 19. An Example: Cisco
  20. 20. Realizing N-M Principles  Community engagement and negotiation:  for the edge, BDaaS customers are initially drawn from their existing customer base  Cisco provides cost/benefit analyses for these enterprise clients  for the periphery, they draw participation from vendors of open-source products  Through collaboration, sub-contracting, partnering
  21. 21. Realizing N-M Principles  Bifurcated architecture / Bifurcated requirements / Fragmented implementation:  Cisco is using a traditional top-down, plan-driven process to create the kernel of its platform  The requirements, architectures, and implementations of the products at the periphery are (largely) independent.
  22. 22. Realizing N-M Principles  Distributed testing:  Cisco manages the testing of its kernel.  Also exerts oversight on the quality of constituent projects via automated acceptance testing.
  23. 23. Realizing N-M Principles  Distributed delivery/maintenance:  automating repetitive and error-prone tasks (e.g., build, testing, and deployment maintain consistent environments)  employing automated testing analysis tools
  24. 24. Realizing N-M Principles  Ubiquitous Operations:  automating as much of operations as possible  employing performance dashboards.  using tools like Apache Mesos to better manage and deploy resources.
  25. 25. N-M Innovation  Innovation is supported by the characteristics and principles of the Neo-Metropolis model.  In particular:  mashability,  bifurcated requirements,  bifurcated architecture and implementation,  continuous operations
  26. 26. N-M Innovation  Components for big data applications (microservices) developed so far include:  Data Storage as a service (e.g., HDFS),  Data Processing as a Service (e.g., MR, Spark),  Data Insights as a Service (pre-processed data as Data Marts and Data Insights ready for consumption),  Data Visualization as a service (e.g., Zoomdata).  They believe everything can be a service: making it easy for others to create new ones, moving towards the vision of a “data mall” (e.g., IoT with a collection of data marts).
  27. 27. Conclusions  This is just a single case study.  However it is the evolution of trends that are driving our software ecosystem: 1. the increasing prominence of cloud computing, 2. the proliferation of open source products 3. sufficiently mature interoperability technologies  Neo-Metropolis instances are the future of service platform development.
  28. 28. Questions?

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