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Rail Ticketing Assistance from the Graph Way, KCOM

GraphConnect Europe 2017
Andy Smale, KCOM

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Rail Ticketing Assistance from the Graph Way, KCOM

  1. 1. Rail Ticketing Assistance from the Graph Way Andy Smale
  2. 2. 2 Agenda KCOM and Me - Introduction The challenges in transport Solutions and why neo4j?
  3. 3. 3 Provides communications services and IT solutions to organisations and consumers £350m turnover, 1700 employees Head Office: Hull, UK City of Culture 2017 Development Base: Ipswich, East Anglia
  4. 4. 4 Contact & Collaboration Cloud Development Integration AWS Azure I&AM API Java Microsoft UI/UX Project Management Security Business Analysis Testing Digital Databases Data Voice Video Architecture
  5. 5. 5 “A bit of a Geek” Farmer in Devon Got a Sinclair ZX80 kit. BASIC! Developed in C, Pascal and Prolog Student of Artificial Intelligence Solution Architect Work in Mobile and Transport Sectors neo4j Certified Architect
  6. 6. 6 Transport ticketing - Functional Overview
  7. 7. 7 Transport Service Challenges Multiple businesses Thousands of locations Flexible retailing of products Fulfilled in different formats (paper, barcode, ITSO) >30,000 Services per day, 1.7billion journeys/year Layers of complexity It even looks like a graph!
  8. 8. 8 API challenges Flexible bookings - File-based - Existing APIs are fine-grained - Aligned with entity/table - Clients relate data - Personal Identifiable Data
  9. 9. 9 Integration and APIs Fast imports of file-based data feeds Design new, richer APIs • Unrestricted by underlying data models • More “graph-friendly” Adapt legacy APIs in service layer Migrate clients to richer APIs Data Protection
  10. 10. 10 Demand Management Best Product at the right Price at the right Time Capacity DemandPrice products Yield Management products
  11. 11. 11 Demand Management Solutions Nests, groups, hierarchies, rules… all configurable • “Sweet spot” for graph technology Decision Support System integration Dynamic updates • Ripple through the graph • “What if…?” modelling Secure, role-based access protects strategies
  12. 12. 12 Reporting Real-time Operational Reports Data exports Scheduled reports Ad hoc Reports Data Analysis Streaming Updates
  13. 13. 13 Reporting Solutions Delivered in real time through published interfaces Ability to monitor and update based on changes Dedicated read replicas serving operational reports Analytic tool integration Visualisation tooling Integration with AWS Kinesis for streaming of data
  14. 14. 14 Technical Architecture Challenges 100% Availability Targets Fast Recovery from Failure Resilient to Network Issues Redundancy built in to Components Automated build and deploy Fast Performance (<50ms writes) Consistently scalable for reads (<30ms, 10k TPS) Thousands of Client systems
  15. 15. 15 Software Engineering Solution Highly Relational Complex Data Model Thousands of queries per second Consistent Writes (hundreds/sec) Security of Commercial Strategies (Yield) Break the problem into bounded domains Autonomous Software Components Continuous Integration and Load Testing Proactive Monitoring and Alerting
  16. 16. 16 Why do we choose Neo4J? Data Model Transactional Scalable Reliable Highly Available Consistent Fast Query Response Enterprise Grade Support
  17. 17. 17 How did we validate Neo4J? Building cluster (on v2.6) Early Load Test Simple data model Created using Stored Procedure Load injectors 10,000 TPS @ <3ms reads
  18. 18. 18 And What’s Next? Full-Scale Automated Load Testing • Adding demand management Causal Clustering • Write performance impact Edge services • Replication lag monitoring Blue-Green Application Upgrades ->3.2 • Aim for zero downtime upgrades
  19. 19. Thank you Contact Andy Smale E andrew.smale@kcom.com T 01473 421421

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