Power-up NoSQL with Cosmos DB
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The document discusses a presentation by Radu Vunvulea about using Azure Cosmos DB to improve various solutions. It begins with an introduction and then provides an overview of what Azure Cosmos DB is, including its key features like global distribution, support for multiple data models, elastic scaling, choice of consistency levels, and latency and availability guarantees. The presentation then demonstrates how Azure Cosmos DB can be used to improve the performance and scalability of command management, command tracking, payload metadata storage, payload assignment, device topology storage, and payload delivery status aspects of a transport platform solution compared to previous implementations that used multiple Azure data services. It concludes by thanking the audience.
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Power-up NoSQL with Cosmos DB
- 1. 16 – 17 November, SofiaISTACON.ORG Power-up NoSQL with Cosmos DB By @RaduVunvulea
- 3. 16 – 17 November, SofiaISTACON.ORG RADU VUNVULEA Technology Enthusiast Dreamer Microsoft Azure MVP Speaker & Trainer Writer & Blogger Idealist Software Architecture Crafter
- 4. 16 – 17 November, SofiaISTACON.ORG Purpose Understand where and how Azure Cosmos DB can improve our solutions
- 5. 16 – 17 November, SofiaISTACON.ORG What is Azure Cosmos DB?
- 6. 16 – 17 November, SofiaISTACON.ORG Azure Cosmos DB Global distribution Multi-model Elastic scale-up Choice of consistency Guaranteed single-digit latency Enterprise-level SLA
- 7. 16 – 17 November, SofiaISTACON.ORG Azure Cosmos DB Global distribution Multi-model Elastic scale-up Choice of consistency Guaranteed single-digit latency Enterprise-level SLA Key Value Column Family Document Graph
- 8. 16 – 17 November, SofiaISTACON.ORG Azure Cosmos DB Global distribution Multi-model Elastic scale-up Choice of consistency Guaranteed single-digit latency Enterprise-level SLA Cross regions Independ and elastic scale
- 9. 16 – 17 November, SofiaISTACON.ORG Azure Cosmos DB Global distribution Multi-model Elastic scale-up Choice of consistency Guaranteed single-digit latency Enterprise-level SLA Strong Bounded Staleness Session Consistent Prefix Eventual
- 10. 16 – 17 November, SofiaISTACON.ORG Consistency levels Strong • Reads are guaranteed to return the most recent version of an item. Bounded Staleness • Consistent Prefix. Reads lag behind writes by k prefixes or t interval Session • Consistent Prefix. Monotonic reads, monotonic writes, read- your-writes, write-follows- reads Consistent Prefix • Updates returned are some prefix of all the updates, with no gaps Eventual • Out of order reads
- 11. 16 – 17 November, SofiaISTACON.ORG Azure Cosmos DB Global distribution Multi-model Elastic scale-up Choice of consistency Guaranteed single-digit latency Enterprise-level SLA Read <10ms Write <15ms 99%
- 12. 16 – 17 November, SofiaISTACON.ORG Azure Cosmos DB Global distribution Multi-model Elastic scale-up Choice of consistency Guaranteed single-digit latency Enterprise-level SLA Guaranteed Consistency &Throughput HA 99.99% Latency <10ms
- 13. 16 – 17 November, SofiaISTACON.ORG Demo
- 14. 16 – 17 November, SofiaISTACON.ORG Context
- 15. Business Scenario • Transport platform between devices and business systems • Device management • Command handling • Payload assignment • Payload delivery
- 16. 16 – 17 November, SofiaISTACON.ORG Command Management
- 17. 16 – 17 November, SofiaISTACON.ORG Command Management Azure Table for each device High throughput on R/W Millions of commands per second Multiple storage accounts
- 18. 16 – 17 November, SofiaISTACON.ORG Command Management Table used to store commands No more cross storage partitioning Reduce deployment complexity Removed storage resolver
- 19. 16 – 17 November, SofiaISTACON.ORG Command Tracking
- 20. 16 – 17 November, SofiaISTACON.ORG Command Tracking Each command has multiple states High throughput on write operations Low latency Timeout detection Reporting capabilities
- 21. 16 – 17 November, SofiaISTACON.ORG Command Tracking Table used to store commands Reduce the load on Azure SQL Scale more easily Timeout detection using Spark Generate reports using Hadoop and PowerBI
- 22. 16 – 17 November, SofiaISTACON.ORG Payload Metadata
- 23. 16 – 17 November, SofiaISTACON.ORG Payload Metadata Multiple Azure Tables High number of read operations Never delete a metadata Replicate across Azure Region Custom logic for replication Risk of inconsistency
- 24. 16 – 17 November, SofiaISTACON.ORG Payload Metadata Table used to stored payload metadata information Replication across regions Removed custom syncronization layer Reduce load on internal Service Bus instances
- 25. 16 – 17 November, SofiaISTACON.ORG Payload assignment
- 26. 16 – 17 November, SofiaISTACON.ORG Payload assignment Real time calculation Result caching is not allowed Requiring computation power Relies on indexes and virtual tables
- 27. 16 – 17 November, SofiaISTACON.ORG Payload assignment Doesn’t make sense to migrate SQL engine is optimized for this kind of operations Azure SQL can scale pretty nice using partitioning
- 28. 16 – 17 November, SofiaISTACON.ORG Device Topology
- 29. 16 – 17 November, SofiaISTACON.ORG Device Topology Documents inside MongoDB There are arround 700.000 different combinations New devices appear every month Synchronization cross region Risk of inconsistency after a few years Writes operations in all nodes
- 30. 16 – 17 November, SofiaISTACON.ORG Device Topology Documents inside Cosmos DB Remove the custom synchronization layer No more inconsistency risk Support for future devices
- 31. 16 – 17 November, SofiaISTACON.ORG Payload Delivery Status
- 32. 16 – 17 November, SofiaISTACON.ORG Payload Delivery Status One Azure Table per device Multiple storage accounts Low throughput No synchronization cross region Reporting capabilities (hot discussions) Storage account resolver capabilities
- 33. 16 – 17 November, SofiaISTACON.ORG Payload Delivery Status Tables inside Cosmos DB No need for multiple storage accounts anymore Reduce deployment complexity Good reporting capabilities Replicate all content to a central location
- 34. 16 – 17 November, SofiaISTACON.ORG Final thoughts
- 35. Azure Cosmos DB
- 36. 16 – 17 November, SofiaISTACON.ORG Thank you! @RaduVunvulea vunvulearadu.blogspot.com https://www.linkedin.com/in/raduvunvulea/ vunvulear@outlook.com
Editor's Notes
- Image sourcehttps://pixabay.com/en/milky-way-universe-person-stars-1023340/