Globally Distributed Modern Apps using Azure Cosmos DB and Azure Functions

In this session we discussed ,how we can develop modern applications using Cosmos DB & Azure Functions. Cosmos DB’s capabilities and Azure Function’s ability to trigger logic in real time without the need to manage any servers.

Transcript

1. Globally Distributed Modern Apps with Azure Cosmos DB & Azure Functions Mohammad Asif Waquar @asifwaquar
2. 2 about me Solution Architect at ABN AMRO https://www.linkedin.com/in/mohammad-asif-6a6153111/
3. Agenda Modern Apps ? Use cases of Global Distributed Apps with Cosmos DB Data Triggers using Azure Functions Demo Global Replication of Apps Demo SQL API
4. Modern Apps ? ✓ Variety ✓ Velocity ✓ Volume
5. Order Goods Inventory Ship Goods Print Invoice ✓ Tight Coupling ✓ Integration with Other System ✓ CRUD Application Read/Writes Performance ✓ Update Conflicts
6. Order Goods Inventory Ship Goods Print Invoice Queue Order received ✓ Decoupling Event Driven Apps ✓ Auditing ✓ Debugging ✓ Integration
7. Order Goods Inventory Ship Goods Print Invoice Queue Order received ✓ Decoupling Event Driven Apps ✓ Auditing ✓ Debugging ✓ Integration
8. Order Goods Inventory Ship Goods Print Invoice ✓ Decoupling ✓ Fault Tolerance ✓ Stability ✓ Auditing Microservices ✓ Easy Update ✓ Versioning
9. Applications
10. Applications
11. Turnkey global distribution Elastic scale out of storage & throughput Comprehensive SLAs Guaranteed low latency at the 99th percentile Five well-defined consistency models Azure Cosmos DB A globally distributed, massively scalable, multi-model database service
12. Turnkey global distribution Elastic scale out of storage & throughput Comprehensive SLAs Guaranteed low latency at the 99th percentile Five well-defined consistency models Azure Cosmos DB A globally distributed, massively scalable, multi-model database service Column-family Document Graph Key-value
13. Column-family Document Graph Turnkey global distribution Elastic scale out of storage & throughput Comprehensive SLAs Guaranteed low latency at the 99th percentile Five well-defined consistency models TableAPI Key-value Cosmos DB’s API for MongoDB Azure Cosmos DB A globally distributed, massively scalable, multi-model database service
14. Features • Multi-model data paradigm: key-value, document, graph, family of columns; • Low latency for 99% of queries: less than 10 ms for read operations and less than 15 ms for (indexed) write operations; • Designed for high throughput; • Ensures availability, consistency of data, delay at SLA level of 99.999%; • Configurable throughput; • Automatic replication (master-slave); • Automatic data indexing; • Configurable levels of consistency of data. Five different levels (Strong, Bounded Staleness, Session, Consistent Prefix, Eventual);
15. Resource Model
16. Account Database Database Database Database Database Container Database Database Item Creating Account
17. Account Database Database Database Database Database Container Database Database Item Database Representations
18. Account Database Database Database Database Database Container Database Database Item = Collection Graph Table Container Representations
19. Account Database Database Database Database Database Container Database Database Item Document Vertices/Edges Row Collection Graph Table Item Representations
20. Account Database Database Database Database Database Container Database Database Item Conflict Stored procedure Trigger UDF Container-Level Resources
21. Data Modelling: Relational vs. Document UserID Name Dob 1 John Smith 8/30/1964 StockID UserID Qty Symbol 1 1 100 MSFT 2 1 75 WMT Document { "id": 1, "name": "John Smith", "dob": "1964-30-08", "holdings": [ { "qty": 100, "symbol": "MSFT" }, { "qty": 75, "symbol": "WMT" } ] } User Table Holdings Table Relational Store Document Store Rows Documents Columns Properties Strongly-typed schemas Schema-free Highly normalized Typically denormalized
22. Replication ,Consistency and Partitioning
23. How do you ensure consistent reads across replicas? - Define a consistency level Replication within aregion - Data moves extremely fast (typically, within1ms) between neighboring racks Global replication - Ittakeshundreds of milliseconds to move data across continents Strongerconsistency Higherlatency Loweravailability Weakerconsistency Lower latency Higher availability Replication and Consistency
24. Logical partition: Stores all data associated with the same partition key value Physical partition: Fixed amount of reserved SSD-backed storage + compute. Cosmos DB distributes logical partitions among a smaller number of physical partitions. From your perspective: define 1 partition key per container Partitioning
25. Data Triggers using Azure Functions
26. ❑ Triggering a notification or a call to an API, when an item is inserted or updated. ❑ Real-time stream processing for IoT or real-time analytics processing on operational data. ❑ Additional data movement by either synchronizing with a cache or a search engine or a data warehouse or archiving data to cold storage.
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30. Customer Checkout Jet.Com Microservices Item Added Cart Created Item Added Cart Checkout Inventory Shipping Customer Input Binding DB Trigger Output Binding
32. 911 Scenario
33. Let’s see in action
36. Application uses
37. Important Links https://azure.microsoft.com/en-us/pricing/calculator/?service=cosmos-db#cosmos-db7aed2059-b457-48cc- a0e9-6744ce81096b Pricing Calculator https://docs.microsoft.com/en-us/azure/cosmos-db/sql-query-getting-started Azure Cosmos Emulator https://docs.microsoft.com/en-us/azure/cosmos-db/local-emulator#controlling-the-emulator SQL API Query http://www.microsoft.com/en-us/download/details.aspx?id=46436 Data Migration Tool
38. Questions?
39. Thank you