Upgrade to Pro — share decks privately, control downloads, hide ads and more …

Enabling Telco to Build and Run Modern Applications

Enabling Telco to Build and Run Modern Applications

See how new databases like MongoDB enable Telco Enterprises to Build and Run Modern Applications.

This presentations was delivered in Tel Aviv in Jan-2015 during a Telco round table organized by Matrix.

Aab9ac774f61c5d9bf143b5a1bfe901b?s=128

Tugdual Grall

January 06, 2015
Tweet

More Decks by Tugdual Grall

Other Decks in Technology

Transcript

  1. Enabling Businesses to Build and Run Modern Applications Tugdual Grall

    Technical Evangelist tug@mongodb.com @tgrall
  2. { “about” : “me” } Tugdual “Tug” Grall • MongoDB

    – Technical Evangelist • Couchbase – Technical Evangelist • eXo – CTO • Oracle – Developer/Product Manager – Mainly Java/SOA • Developer in consulting firms • Web – @tgrall – http://blog.grallandco.com – tgrall • NantesJUG co-founder • Pet Project – http://www.resultri.com tug@mongodb.com tugdual@gmail.com
  3. Agenda • The Need for a Next Generation Database •

    MongoDB Overview • The Company • The Technology • The Community • MongoDB in Telco
  4. Agenda • The Need for a Next Generation Database •

    MongoDB Overview • The Company • The Technology • The Community • MongoDB in Telco
  5. Your Industry Has Changed Upfront subscribe Business Years Months Applications

    PC Mobile Customers Ads social Engagement servers Cloud Infrastructure
  6. Your Data Has Changed • 90% of the world’s data

    was created in the last two years • 80% of enterprise data is unstructured • Unstructured data growing 2x faster than structured
  7. You’re Not Alone What are the primary data issues driving

    you to consider Big Data?* *  From  Big  Data  Executive  Summary  of  50+  execs  from  F100,  gov  orgs “Of  Gartner's  "3Vs"  of  big  data  (volume,  velocity,  variety),   the  variety  of  data  sources  is  seen  by  our  clients  as  both   the  greatest  challenge  and  the  greatest  opportunity.”                     -­‐  Forrester,  2014 Diverse, streaming or new data types Greater than 100TB Less than 100TB
  8. Development – Methods are Changing Requirements Analysis Design Build Test

    Acceptance Business  Input Features
  9. Development – Agile Development Feature Backlog Working Product Analysis Design

    Build Test 2 - 4 Weeks Cycle
  10. Software Has Changed • High up-front costs • High TCO

    • Low up-front costs • Low TCO
  11. The Database is the last technology in the stack to

    be modernized
  12. Analytics & BI Integration

  13. Agenda • The Need for a Next Generation Database •

    MongoDB Overview • The Company • The Technology • The Community • MongoDB in Telco
  14. MongoDB, Inc. 400+ employees 1,000+ customers Over $231 million in

    funding 13 offices around the world
  15. MongoDB Partners (600+) Software & Services Cloud & Channel Hardware

  16. Agenda • The Need for a Next Generation Database •

    MongoDB Overview • The Company • The Technology • The Community • MongoDB in Telco
  17. Data Types   Unstructured data   Semi-structured data   Polymorphic

    data   Agile Development   Iterative   Short development cycles   New workloads Relational Database Challenges Volume of Data   Petabytes of data   Trillions of records   Millions of queries/sec   New Architectures   Horizontal scaling   Commodity servers   Cloud computing
  18. Operational Database Landscape Scalability & Performance Depth of Functionality key/value

    stores wide column RDBMS MongoDB
  19. Changing Mindsets Relational Centralized Document Distributed

  20. Removing Unneeded Complexity { name: ‘John Doe’, id: ‘X2312-BC’, cell:

    ‘+447557505611’ city: ‘London’, location: [45.123,47.232], plans: [ { type : ‘mobile’ label: ‘30G+’, price: 29.99, … }, { type : ‘internet’ label: ‘Cable’, price: 39.99, … } } }
  21. Document Data Model Relational MongoDB {   first_name: ‘Paul’,  

    surname: ‘Miller’,   city: ‘London’,   location: [45.123,47.232],   cars: [   { model: ‘Bentley’,   year: 1973,   value: 100000, … },   { model: ‘Rolls Royce’,   year: 1965,   value: 330000, … }   }   }
  22. No SQL But Still Flexible Querying MongoDB {   first_name:

    ‘Paul’,   surname: ‘Miller’,   city: ‘London’,   location: [45.123,47.232],   cars: [   { model: ‘Bentley’,   year: 1973,   value: 100000, … },   { model: ‘Rolls Royce’,   year: 1965,   value: 330000, … }   }   } Rich Queries Find Paul’s cars   Find everybody in London with a car built between 1970 and 1980 Geospatial Find all of the car owners within 5km of Trafalgar Sq. Text Search Find all the cars described as having leather seats Aggregation Calculate the average value of Paul’s car collection Map Reduce What is the ownership pattern of colors by geography over time? (is purple trending up in China?)
  23. MongoDB - Scalability • High Availability • Auto Sharding •

    Enterprise Monitoring • Grid file storage
  24. Morphia MEAN  Stack Java Python Perl Ruby Support for the

    most popular languages and frameworks Drivers & Ecosystem
  25. What We Sell MongoDB Enterprise Advanced   The best way

    to run MongoDB in your data center   MongoDB Management Service (MMS)   The easiest way to run MongoDB in the cloud.   Production Support   In production and under control   Development Support   Let’s get you running.   Consulting   We solve problems.   Training   Get your teams up to speed.
  26. ‹#› DO YOU NEED: YES NO Advanced security? ✓ Disaster

    Recovery? ✓ Monitoring for system performance and availability? ✓ Automated lifecycle management? ✓ Guaranteed response time? ✓ Platform certification ✓ Enterprise Decision Checklist
  27. How MMS helps you Scale  Easily Meet  SLAs Best  Practices,

      Automated Cut  Management   Overhead
  28. What MMS can do Provision Upgrade Scale Continuous  Backup Point-­‐in-­‐Time

     Recovery Performance  Alerts
  29. Agenda • The Need for a Next Generation Database •

    MongoDB Overview • The Company • The Technology • The Community • MongoDB in Telco
  30. THE LARGEST ECOSYSTEM 9,000,000+
 MongoDB Downloads 250,000+
 Online Education Registrants

    35,000+
 MongoDB User Group Members 40,000+
 MongoDB Management Service (MMS) Users 750+
 Technology and Services Partners 2,000+
 Customers Across All Industries
  31. Agenda • The Need for a Next Generation Database •

    MongoDB Overview • The Company • The Technology • The Community • MongoDB in Telco
  32. Removing Impedance Mismatches Object Relational Mapping (ORM) Extraction Transformation and

    Loading (ETL) Change Management Features vs Complexity Platform Agility
  33. MongoDB Use Cases Single View Internet of Things Mobile Real-Time

    Analytics Catalog Personalization Content Management
  34. Challenge: Achieve Cross Asset View Batch Batch Batch Issues  

    •Yesterday’s  data   •Details  lost   •Inflexible  schema   •Slow  performance Batch Impact   •What  happened  today?   •Worse  customer  satisfaction •Missed  opportunities   •Lost  revenue   Batch Batch Reporting Customers Payments Products Data   Mart Data   Mart Data   Mart Datawarehouse
  35. .  .  .  .   Solution: Use New Database Customers

    Payments Products .  .  .  .   Operational   Data  Layer Customers   Service Operational   Reporting Open  Data  API Datawarehouse Strategic   Reporting Benefits   • Real-­‐time   • Complete  details   • Agile   • Higher  customer  retention • New  products   • …
  36. Single View of Customer Insurance leader generates coveted 360-degree view

    of customers in 90 days – “The Wall” Problem Why MongoDB Results • No single view of customer • 145 yrs of policy data, 70+ systems, 15+ apps • 2 years, $25M in failing to aggregate in RDBMS • Poor customer experience • Agility – prototype in 9 days; • Dynamic schema & rich querying – combine disparate data into one data store • Hot tech to attract top talent • Production in 90 days with 70 feeders • Unified customer view available to all channels • Increased call center productivity • Better customer experience, reduced churn, more upsell opps • Dozens more projects on same data platform
  37. Single View of Customer Adding Flexibility and Scalability to Bouygues

    Telecom Problem Why MongoDB Results • No single view of customer • Perfomance and complexity • 2 years delay • Poor customer experience • Agility • Scalability • Dynamic schema & rich querying – combine disparate data into one data store • Easy data integration • Developed in 6 months • Unified customer view available to all channels • Increased call center productivity • New projects • Devops
  38. Product Catalog Serves variety of content and user services on

    multiple platforms to 7M web and mobile users Problem Why MongoDB Results • MySQL reached scale ceiling – could not cope with performance and scalability demands • Metadata management too challenging with relational model • Hard to integrate external data sources • Unrivaled performance • Simple scalability and high availability • Intuitive mapping • Eliminated 6B+ rows of attributes – instead creates single document per user / piece of content • Supports 115,000+ queries per second • Saved £2M+ over 3 yrs. • “Lead time for new implementations is cut massively” • MongoDB is default choice for all new projects
  39. Personnalisation Server Accelerate Time To Market Problem Why MongoDB Results

    • Expensive Oracle Based Solution • 20 people, 16 months • Performance issues • 3 iterations • Cannot take new requirements • Mature Technology • Dynamic Schema • Fault Tolerance • Performance • 4 Developers • 4 months • Add new features • Faster • Smaller • Easier
  40. Mobile / Open Data API PIM Database • Legacy Application

    • Product Information NoSQL • REST API • Product Data • Additional Metadata
  41. And many more… Opening  new  possibles

  42. Turning your Network into Insights for resellers

  43. Smartsteps

  44. Ideas?

  45. Conclusion • World has changed • Time To Market •

    Cost Reduction • New Possibles
  46. Enabling Businesses to Build and Run Modern Applications Tugdual Grall

    Technical Evangelist tug@mongodb.com @tgrall