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Cloud Crowd - Mobile Sync Cloud

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These are the slides presented by Alejandro Ramallo & Phil Shotton at the GigaSpaces hosted CloudCrowd event in the UK on November 11th 2009. ...

These are the slides presented by Alejandro Ramallo & Phil Shotton at the GigaSpaces hosted CloudCrowd event in the UK on November 11th 2009.

The slides how ho Gigaspaces was used to build a global mobile sync cloud on top of Siebel.

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Cloud Crowd - Mobile Sync Cloud Cloud Crowd - Mobile Sync Cloud Presentation Transcript

  • Mobile Sync Cloud
    • Alejandro M. Ramallo - Group Head of Technology, BAT
    • Phil Shotton - Cloudscape
  • Background
    • The MARTINI Project is a global initiative to provide a flexible, extensible TM&D system
    • A System-of-systems (SOA) aimed at replacing the existing regional/local solutions.
    • More than 10,000 Sales Reps worldwide will use hand-held devices (Smart-phones, PDAs etc) to manage sales fulfilment and order delivery functions
    • The hand-held will run a bespoke application accessing a local database holding an extract from the BAT backend’s master database
  • Objectives
    • Robust, resilient synchronisation capability
    • Full database load
    • Bi-directional delta synchronisation
    • Background scheduling of data retrieval and synchronisation
    • Field-level delta updates to minimise network bandwidth requirements and backend system load
  • Requirements
    • Provide bi-directional, asynchronous, delta synchronisation
    • Conflict resolution at field level
    • Minimise mobile connect time
    • Plug-in architecture, extensible
    • Scalability
    • Performance
    • Hub-and-spoke capabilities
  • Scale
    • 2,500,000 outlets visited every week more than once ~ 4 million visits
    • 10,000 Sales Reps * 77 Mb per user = 752 Gb
  • Alternatives considered COTS Bespoke using RDBMS Bespoke Space-based
    • Stateless engine
    • State in RDBMS or Queues
    • No hub-and-spoke
    • High availability is costly
    • RDBMS requires administration
    • Development platform lock-in
    • Not really made for our data volumes
    • Stateless engine
    • Bespoke caching
    • State in RDBMS
    • Hub-and-spoke more difficult to implement
    • High availability is costly
    • RDBMS requires administration
    • Development platform lock-in
    • Not really made for our data volumes
    • 100% in-memory
    • Distributed
    • Partitioning
    • Hub-and-spoke
    • Cleaner/Better programming model
    • Multi-platform support
    • Resilience
    • Performance
  • A space-based sync engine
  • Challenges
    • Data Mapping
    • Data extraction, visibility, 'invisible' delete
    • Support multiple models simultaneously
    • Decouple sync clients
    • Memory and Performance requirements
  • Scale
    • 2,500,000 outlets visited every week more than once ~ 4 million visits
    • 10,000 Sales Reps * 77 Mb per user = 752 Gb
    • 53 Sales Reps per space @ 4 Gb per space
    • 188 spaces + backup
    • @10 spaces per machine = 38 machines
  • Design Principles
    • Decompose problem into discrete tasks
    • Tasks model process flow
    • Pluggable services provide business logic
    • Extraction, Upload and Mapping driven by externally-managed configuration
    • Highly-scalable, resilient, space-based architecture
  • High Level Architecture Mobile Software Data Centre ERP Services Service Bus Space Bus (Hub) Messaging Bus CRM Sync Engine Space Bus (Spoke) Sync Engine Mobile Software WAN Sync Gateway
  • High Level Architecture
  • Internal Architecture
  • Downward flow
  • Upward flow
  • Backend extract
  • Reconciliation
  • Backend upload
  • Lessons learned
    • GigaSpaces can be used to create a Mobile Data Cloud
    • Volumes of scale with resiliency can be achieved 
    • You are only as fast as your slowest link / bottleneck
    • Monolithic Back Office systems present challenges that can be overcome although it would be nice if vendors migrate to SOA (really)
  • Questions