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Azure Services Platform and SQL Services Value Proposition and Scenarios Architecture Building Applications using SQL Data Services Release Plans Conclusion and Takeaways
Talk Outline
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
Reference Data
Reporting Data Sync
ETLData Mining
Scalable, Available Data ServicesStorage and Database Services
Windows Azure Storage “Essential storage service in
the cloud”
Provides a core set of non-relational storage and retrieval abstractions at massive scale
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
Azure Services Platform and SQL Services Value Proposition and Scenarios Architecture Building Applications using SQL Data Services Release Plans Conclusion and Takeaways
Talk Outline
Azure Services Platform and SQL Services Value Proposition and Scenarios Architecture Building Applications using SQL Data Services Release Plans Conclusion and Takeaways
SDS is built on three key pillars1. Storage for all data types from
birth to archival2. Rich data processing services3. Operational excellence
SQL Data Services (SDS)“Database as a Service”
Scale-free
High availability
Geo replication
On-demand service
Easy to use
Easy to manage
Data privacy
Competitive pricing
Line of Business Applications Delivered as a Service
Collaborative Web Applications Shared Data Hub Data Warehousing and
Business Intelligence
Key Scenarios
Trey Research Media Marketplace
Photos andMetadata
SearchAnalytics
Photos
Photographer
Photographer Trey Exec
Media BuyerPhotos
Search
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
Scale-free High availability Geo distribution Broad reach Agile development
Multi-master data synchronization
Occasionallyconnected clients
Photo ManagementWPF App
Corporate ManagementSharePoint App
PhotographerIn FieldMobile App
CustomerWeb App
Trey Research
K2http://www.k2.com
partner
(USE THIS SPACE FOR PRODUCT LOGOS WHEN WHITE BACKGROUND
IS REQUIRED)DELETE WHITE RECTANGLES IF NOT
BEING USED
Adriaan Van WykCEO
K2 Background
Founded in 2000 – Microsoft Global ISV Partner Over 1,700 customers across 45 countries Strategic relationship with Microsoft across
23 technologies K2 enables composition, implementation,
and management of Enterprise Workflow and Process Applications… That integrates people, processes and line of
business information… Visually designed and assembled from reusable entities… Maximizing developer productivity, improving application
lifecycle management, and maximizing agility in application change…
Business ScenarioOrder management
Business ChallengesCreate an order processing application that
integrates Salesforce.com customer data with order and product data
CriteriaMany orders are fulfilled by a 3rd party,
so needed separate data location Product catalog is maintained by a
different group Did not want to put all in SF.com
ApproachChose 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
BenefitsAchieved goals at lowest possible price point
and highest ROIQuick time to market with app orchestration
across multiple cloud servicesAchieved the best of a software + services model
create
delete
update
List
Customers(SF.com) Orders
SDS
ProductsSDS
Sales MgrsSharePoint list
K2 SMART Objects
New Sales Order Form Completed
Look up Sales Mgr and send for Approval
Delete Order and send e-mail
Approval View Sales Mgr
Approved
Create View
Record Order and update Order Status
to Approved
Rejected
REPORT
Process
Talk Outline
Azure Services Platform and SQL Services Value Proposition and Scenarios Architecture Building Applications using SQL
Data Services Release Plans Conclusion and Takeaways
Architecture
Data Access Lib
SDS Runtime
REST / SOAP
Data Access Lib
SDS Runtime
REST / SOAP
Data Access Lib
SDS Runtime
REST / SOAP
Data Access Lib
SDS Runtime
REST / SOAP
Data Access Lib
SDS Runtime
REST / SOAP
Data Access Lib
SDS Runtime
REST / SOAP
Data Access Lib
SDS Runtime
REST / SOAP
Mgmt. Services
Distributed Data Fabric
SQL Server
Mgmt. Services
Distributed Data Fabric
SQL Server
Mgmt. Services
Distributed Data Fabric
SQL Server
Mgmt. Services
Distributed Data Fabric
SQL Server
Mgmt. Services
Distributed Data Fabric
SQL Server
Mgmt. Services
Distributed Data Fabric
SQL Server
Mgmt. Services
Distributed Data Fabric
SQL Server
SQL Data Services Front End
SQL Data Services Back End Master ClusterData Cluster
SDS - Reliable Master Cluster Manager
SDS – Data Nodes
SDS - Back-end
SQL Server
Database
Data And Master Nodes
Data Node 105
Data Node 104
Data Node 103
Data Node 102
Data Node 101
P1
S1
P2S2
S1S2
P6 S6P5
S5S6
P3
S5
S3
P3
P4 S4S4
P1P2P3P4P5P6
Partition Manager
Global Partition
Map
SQL Server
Partition Placement
Advisor
Leader Elector
Distributed Data Fabric
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 within
a container Some operations cross-containers Container size limitations
Data Partitioning
Container X
MasterClusterManager
Container look-up
SDS Back End
SDS Front End
Request forContainer X
Fetch container map
Connect to BEserver holdingContainer X
Talk Outline
Azure Services Platform and SQL Services Value Proposition and Scenarios Architecture Building Applications using SQL
Data Services Release Plans Conclusion and Takeaways
Data Model And ACE Concepts
Unit ofgeo-location and billing
Tied toDNS name
Collectionof Containers
Authority Container Entity
Unit of Consistency
Scope for Query and Update
Collectionof Entities
Unit of Storage Property Bag
of Name/Value pairs
No Schema Required
ConceptsEntity
Entity properties may differ in type and instanceProperty Type Value
Metadata ID EntityId VWGOLF-01
Kind EntityKind Car
FlexProps Description String Reliable, one owner, …
Price Numeric 12000.00
ListingDate Datetime 01-01-2008
LocationZip String 98052
Property Type Value
Metadata ID EntityId MINICOOPER-264
Kind EntityKind FunCar
FlexProps Description String Reliable, one owner, …
Price Numeric 12000.00
ListingDate String 1st January, 2008
LocationZip String 98052
EngineSize Numeric 1600
DifferentKinds
DifferentInstance
Types
Additional Property
SDSQuery language
Textual query language through web-service head, passed in as literal text string
Language patterned after C# LINQ syntax
from e in container where e.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
Finally, A Data Service With JOIN
All orders for customers in the stateof Washington, ordered by valuefrom c in entities.OfKind(“Customer”)
where c[“State”] == “WA”
from o in entities.OfKind(“Order”)
where o[“CustomerId”] == c.Id
orderby o[“Value”] descending
select o
Customer{ Id; Kind; Version; Name; Address; State;}
Order{ Id; Kind; Version; CustomerId; ItemId; Value;}
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 to
data service Batching to reduce service request latency Use of authorities to provide geo-location
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 %
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
Talk Outline
Azure Services Platform and SQL Services Value Proposition and Scenarios Architecture Building Applications using SQL Data Services Release Plans Conclusion and Takeaways
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
Talk Outline
Azure Services Platform and SQL Services Value Proposition and Scenarios Architecture Building Applications using SQL Data Services Release Plans Conclusion and Takeaways
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
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 Labs
http://www.microsoft.com/azure/sqllabs.mspx
Related SessionsCode Title Room Time
BB23 SQL Data Services : A Lap Around 502A 10/28/2008 3:30PM-4:45PM
BB03 SQL Data Services : Under the Hood 404A 10/30/2008 8:30AM-9:45AM
BB14 SQL Data Services: Futures 408B 10/29/2008 10:30AM-11:45AM
BB52 SQL Data Services: Tips and Tricks for High-Throughput Data-Driven Applications 411 10/28/2008 12:45PM-1:30PM
BB40 Sync Framework: Enterprise Data in the Cloud and on Devices 408A 10/28/2008 5:15PM-6:30PM
TL30 Microsoft Sync Framework Advances 515B 10/27/2008 1:45PM-3:00PM
BB16 SQL Server 2008: Beyond Relational 406A 10/28/2008 1:45PM-3:00PM
BB26 SQL Server 2008: Business Intelligence and Data Visualization 515A 10/28/2008 1:45PM-3:00PM
BB24 SQL Server 2008: Deep Dive into Spatial Data 404A 10/29/2008 3:00PM-4:15PM
BB07 SQL Server 2008: Developing Large Scale Web Applications and Services 411 10/28/2008 1:45PM-3:00PM
BB37 SQL Server 2008: Developing Secure Applications 515A 10/29/2008 12:00PM-12:45PM
BB25 SQL Server 2008: New and Future T-SQL Programmability 515A 10/29/2008 1:15PM-2:30PM
PC40 SQL Server Compact: Embedding in Desktop and Device Applications 402A 10/29/2008 3:00PM-4:15PM
TL42 Microsoft SQL Server 2008: Powering MSDN 411 10/29/2008 12:00PM-12:45PM
TL14 Project "Velocity": A First Look 403AB 10/28/2008 1:45PM-3:00PM
TL56 Project "Velocity": Under the Hood 403AB 10/28/2008 3:30PM-4:45PM
PC44 Windows 7: Programming Sync Providers That Work Great with Windows 408B 10/28/2008 12:45PM-1:30PM
Evals & Recordings
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© 2008 Microsoft Corporation. All rights reserved. Microsoft, Windows, Windows Vista and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries.The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market
conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.