SQL Data Services A lap around

1. BB23 SQL Data ServicesA lap around  Soumitra Sengupta Software Architect Microsoft Corporation

2. Talk Outline • Azure Services Platform and SQL Services • Value Proposition and Scenarios • Architecture • Building Applications using SQL Data Services • Release Plans • Conclusion and Takeaways

3. Azure Services Platform Azure™ Services Platform

4. SQL Services FuturesExtending the SQL Data Platform to the cloud • Data services tier of the Azure Services Platform • Built on SQL Server foundation • Broad data platform capabilities as a service • Friction-free provisioning, scaling • Significant investments in scale, HA, lights-out operation and TCO Database Reporting Data Sync Data Mining Reference Data ETL

5. Scalable, Available Data ServicesStorage and Database Services Windows Azure Storage SQL Data Services “Premium database service in the cloud” Extends the rich capabilities of the SQL data platform to the cloud at scale Relational data processing over structured and unstructured data Integrate with key data platform capabilities – e.g. Data Analytics, Reporting, ETL • “Essential storage service in the cloud” • Provides a core set of non-relational storage and retrieval abstractions at massive scale

6. Talk Outline • Azure Services Platform and SQL Services • Value Proposition and Scenarios • Architecture • Building Applications using SQL Data Services • Release Plans • Conclusion and Takeaways • Azure Services Platform and SQL Services • Value Proposition and Scenarios • Architecture • Building Applications using SQL Data Services • Release Plans • Conclusion and Takeaways

7. SQL Data Services (SDS)“Database as a Service” SDS is built on three key pillars • Storage for all data types frombirth to archival • Rich data processing services • Operational excellence • Scale-free • High availability • Geo replication • On-demand service • Easy to use • Easy to manage • Data privacy • Competitive pricing

8. Key Scenarios • Line of Business Applications Delivered as a Service • Collaborative Web Applications • Shared Data Hub • Data Warehousing and Business Intelligence

9. Trey Research Media Marketplace • Normalized relational data and unstructured data • Complex relational queries across all data • Query/processing on rich data types; e.g., spatial • Business Data Analytics on/off premise Photos Media Buyer Search CustomerWeb App Trey Research Photos andMetadata SearchAnalytics Photographer Trey Exec Photo ManagementWPF App Corporate ManagementSharePoint App Photos • Scale-free • High availability • Geo distribution • Broad reach • Agile development • Multi-master data synchronization • Occasionallyconnected clients PhotographerIn FieldMobile App Photographer

10. demo Trey Research Media Marketplace  Soumitra Sengupta

11. partner K2http://www.k2.com (USE THIS SPACE FOR PRODUCT LOGOS WHEN WHITE BACKGROUND IS REQUIRED) DELETE WHITE RECTANGLES IF NOT BEING USED Adriaan Van Wyk CEO

12. K2 Background • Founded in 2000 – Microsoft Global ISV Partner • Over 1,700 customers across 45 countries • Strategic relationship with Microsoft across23 technologies • K2 enables composition, implementation,and management of • Enterprise Workflow and Process Applications… • That integrates people, processes and line ofbusiness information… • Visually designed and assembled from reusable entities… • Maximizing developer productivity, improving application lifecycle management, and maximizing agility in application change…

13. Business ScenarioOrder management Process New Sales Order Form Completed • Business Challenges • Create an order processing application that integrates Salesforce.com customer data with order and product data • Criteria • Many orders are fulfilled by a 3rd party, so needed separate data location • Product catalog is maintained by adifferent group • Did not want to put all in SF.com • Approach • Chose SDS for orders and products database because of its enterprise class approach to Cloud database services and ease of integration with K2 into K2 SmartObject layer • Benefits • Achieved goals at lowest possible price pointand highest ROI • Quick time to market with app orchestration across multiple cloud services • Achieved the best of a software + services model Create View K2 SMART Objects Look up Sales Mgr and send for Approval create delete update Approval View List Rejected Approved Record Order and update Order Status to Approved Delete Order and send e-mail REPORT Sales Mgrs SharePoint list Customers (SF.com) Sales Mgr Orders SDS Products SDS

14. demo K2  Adriaan Van Wyk

15. Talk Outline • Azure Services Platform and SQL Services • Value Proposition and Scenarios • Architecture • Building Applications using SQL Data Services • Release Plans • Conclusion and Takeaways

16. Architecture SQL Data Services Front End REST / SOAP REST / SOAP REST / SOAP REST / SOAP REST / SOAP REST / SOAP REST / SOAP SDS Runtime SDS Runtime SDS Runtime SDS Runtime SDS Runtime SDS Runtime SDS Runtime Data Access Lib Data Access Lib Data Access Lib Data Access Lib Data Access Lib Data Access Lib Data Access Lib Master Cluster Data Cluster SQL Data Services Back End SQL Server SQL Server SQL Server SQL Server SQL Server SQL Server SQL Server Distributed Data Fabric Distributed Data Fabric Distributed Data Fabric Distributed Data Fabric Distributed Data Fabric Distributed Data Fabric Distributed Data Fabric Mgmt. Services Mgmt. Services Mgmt. Services Mgmt. Services Mgmt. Services Mgmt. Services Mgmt. Services

17. Data And Master Nodes SDS - Back-end SDS - Reliable Master Cluster Manager Partition Manager Partition Placement Advisor SQL Server SQL Server Global Partition Map Leader Elector Database P1 Distributed Data Fabric P2 SDS – Data Nodes P3 Data Node 102 Data Node 103 Data Node 104 P4 P5 Data Node 101 Data Node 105 P6 S5 P3 P1 P2 S1 P5 S6 S5 S2 S2 P6 S6 P4 S4 S1 S3 P3 S4

18. Data Partitioning Request for Container X Extreme scale is achieved through partitioning data into containers • SDS apps are container-aware • Requests include a target container • Implementation is opaque to users • Containers – unit of consistency • Replicated for reliability and HA • Reconfigured during failover • Used for load balancing Trade off app transparency and latency for scale, throughput and better TCO • Rich SQL-like operations withina container • Some operations cross-containers • Container size limitations SDS Front End Fetch container map Container look-up Master Cluster Manager Connect to BE server holding Container X SDS Back End Container X

19. Talk Outline • Azure Services Platform and SQL Services • Value Proposition and Scenarios • Architecture • Building Applications using SQL Data Services • Release Plans • Conclusion and Takeaways

20. Unit ofgeo-location and billing Tied toDNS name Collectionof Containers Data Model And ACE Concepts Authority Container Entity • Unit of Consistency • Scope for Query and Update • Collectionof Entities • Unit of Storage • Property Bagof Name/Value pairs • No Schema Required

21. Entity properties may differ in type and instance ConceptsEntity DifferentKinds DifferentInstanceTypes Additional Property

22. demo Creating Authorities, Containers & Entities  Soumitra Sengupta

23. SDSQuery language • Textual query language through web-service head, passed in as literal text string • Language patterned after C# LINQ syntaxfrom e in container wheree.Kind == “FunCar” && e[“Zip”] == 98053 && e[“Model”] == “Mini Cooper” select e • Operator semantics handles lack of schema contract • e[“Zip”] could be number in one entity and string in another • e[“Tag”] == “CUSTOMER” means look for instances where Tag is a string and has value “CUSTOMER”; i.e., type inference using literal syntax • Query supported over metadata and data properties

24. All orders for customers in the stateof Washington, ordered by value from c inentities.OfKind(“Customer”) where c[“State”] == “WA” from o inentities.OfKind(“Order”) where o[“CustomerId”] == c.Id orderby o[“Value”] descending select o Finally, A Data Service With JOIN Customer { Id; Kind; Version; Name; Address; State; } Order { Id; Kind; Version; CustomerId; ItemId; Value; }

25. demo SDS Queries  Soumitra Sengupta

26. Application Design Considerations • Designing for scale using multiple containers • Entity and Containers limited in size • Number of properties/size of entity (MB) • Number of entities within a container (GB) • Containers map to single replica in SDS BE • Each container has limited IOPs and CPU capacity • Designing for latency • Code (biz logic) has higher latency todata service • Batching to reduce service request latency • Use of authorities to provide geo-location

27. Gomez Monitoring Results • Time Period : 10 a.m., Sunday, 26th to 10:30 a.m. Monday, 27th • Average Response Time : 0.099 s • Availability : 100 %

28. demo Metering  Soumitra Sengupta

29. Authentication And Authorization • Basic authentication – username and password • Integrate with .NET Access Control Services for richer authentication models • Basic Authentication • Claims based access control • Role based authorization – Future

30. Talk Outline • Azure Services Platform and SQL Services • Value Proposition and Scenarios • Architecture • Building Applications using SQL Data Services • Release Plans • Conclusion and Takeaways

31. announcing Public CTP Of SQL Data ServicesMid November

32. Transition to Public CTP • When you register for Azure Services Platform at PDC • You will be notified when we open Public CTP • Your credentials will work on Public CTP • If you already have an account for private beta • Your credential and data will be migrated • You will be notified via email about the new endpoints

33. Talk Outline • Azure Services Platform and SQL Services • Value Proposition and Scenarios • Architecture • Building Applications using SQL Data Services • Release Plans • Conclusion and Takeaways

34. Conclusions And Key Takeaways • Cloud Computing is here . . . • Play with the bits in the Hands on Labs • Watch our partners at Bar Chat in the Lounge • Get registration code to start using service • Azure Service Platform is a comprehensive services platform in the cloud • SQL Data Services is the data tier ofAzure Services Platform • SQL Server is the foundation • Rich data services over time • Public Community Technology Preview in mid November

35. Resources • Azure Services Platform Home http://www.microsoft.com/azure/default.mspx • SQL Services Homehttp://www.microsoft.com/azure/sql.mspx • SQL Data Services Dev Centerhttp://msdn.microsoft.com/en-us/sqlserver/dataservices/default.aspx • SQL Data Services Documentationhttp://msdn.microsoft.com/en-us/library/cc512417.aspx • SQL Services Team Blog http://blogs.msdn.com/ssds • SQL Services Labshttp://www.microsoft.com/azure/sqllabs.mspx

36. Related Sessions

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