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Mobile Sync Cloud Alejandro M. Ramallo - Group Head of Technology, BAT Phil Shotton - Cloudscape.

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Presentation on theme: "Mobile Sync Cloud Alejandro M. Ramallo - Group Head of Technology, BAT Phil Shotton - Cloudscape."— Presentation transcript:

1 Mobile Sync Cloud Alejandro M. Ramallo - Group Head of Technology, BAT Phil Shotton - Cloudscape

2 2 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

3 3 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

4 4 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

5 5 Scale 2,500,000 outlets visited every week more than once ~ 4 million visits 10,000 Sales Reps * 77 Mb per user = 752 Gb

6 6 Alternatives considered COTSBespoke using RDBMSBespoke 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

7 7 A space-based sync engine

8 8 Challenges Data Mapping Data extraction, visibility, 'invisible' delete Support multiple models simultaneously Decouple sync clients Memory and Performance requirements

9 9 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 4 Gb per space 188 spaces + spaces per machine = 38 machines

10 10 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

11 11 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 Gatewa y

12 12 High Level Architecture

13 13 Internal Architecture

14 14 Downward flow

15 15 Upward flow

16 16 Backend extract

17 17 Reconciliation

18 18 Backend upload

19 19 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)

20 20 Questions


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