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Transforming The Customer Experience With Real-Time Insights

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Streaming data pipelines allow almost any organization to deliver higher value, faster, to customers. Delivering on the real-time element of the customer experience, however, necessitated a major overhaul to HPE's architecture.

In this Gartner Catalyst 2018 session, Jeff Dutton, Data Platform Architect for HPE, will share his journey developing a new architecture to deliver real-time insights from billions of IOT sensors, trillions of metrics, and petabytes of data.

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Transforming The Customer Experience With Real-Time Insights

  1. 1. Transforming The Customer Experience With Real-Time Insights Lessons learned at HPE InfoSight
  2. 2. Situation Vision Strategy Struggles Roadmap
  3. 3. The Situation IoT AI Scale Beyond Batch
  4. 4. Vision 1 2 3 4 5 Scale Development Real-Time Broad Insights Diverse Use Cases Agile Infrastructure
  5. 5. Strategy Streaming data architecture with Fast Data processing Microservice architecture for scaling development and deployment of services Polyglot Persistence using tiered and diverse data stores matched to the use cases Orchestrated Container Platform for flexible, agile infrastructure to enable fast time to market Inner Source with social coding to enable development teams throughout the organization
  6. 6. Reactive Manifesto Goal Principles Means http://reactivemanifesto.org
  7. 7. Streaming and Fast Data IoT Core Domain API Query DB Data Warehouse or Data Mart Device Shadow Service Device Shadows Device Streaming Load Streaming Load Stateless API Microservice Data Science KafkaSubscribe to Event Streams from other Domains Domain-Produced Event Stream Config Rule Checking Device Device Shadow Commands / Queries Status, Metrics, Events, Logs Streaming Analytics / ML
  8. 8. Kafka Device Auth Federated ID Entitlement CRM Cases IoT Core Domains Installed Base Notification Rule Registry API Gateway Device Shadow Wellness Tagging Microservices
  9. 9. Polyglot Persistence * Customers Support R&D Data Warehouse SQL Data Lake Tiered Data Transactions vs. Query Streaming No “best DB”
  10. 10. Container Orchestration Registry Networking Storage Security Telemetry = Orchestration Containers
  11. 11. Inner Source to Scale Development Goal Principles Means
  12. 12. Struggles Overwhelming Thinking differently Last 20% Divergence Organizational immune system
  13. 13. Pro-Tips 1. Rationalize your buzzwords 2. Domain-Driven Design 3. Stream all the things… 4. But not all at once 5. POC the hard parts 6. Get help early on 7. Keep going 8. Fail fast
  14. 14. Questions

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