The distributed in-memory caching capabilities of Windows Server AppFabric will change how you think about scaling your Microsoft .NET-connected applications. Come learn how the distributed nature of the AppFabric cache allows large amounts of data to be stored in-memory for extremely fast access, how AppFabric's integration with Microsoft ASP.NET makes it easy to add low-latency data caching across the web farm, and discover the unique high availability features of AppFabric which will bring new degrees of scale and resilience to your data tier and your web applications.

1. Scale Your Data Tier with Windows Server AppFabric Chris Dufour, ASP MVP Software Architect, Compuware chris.dufour@wigets.net

2. Agenda

3. Simple Do the simplest thing that will possibly work

4. Scalability Able to support the required quality of service as the system load increases -Wiktionary

5. Typical Web Architecture

6. Web Explosion Web Site’s too slow!! Where did my shopping cart go? IIS/ASP.NET IIS/ASP.NET IIS/ASP.NET Application Application Application Servers are crashing Database Database is hot!! Services are slow

7. Agenda

8. Data Near Processing Cache Cache Browser Smart Client Cache Web Service Cache ASP.NET Cache Database

9. Good but… Cache is scoped to machine / process Machines die Processes recycle Cache memory is limited

10. What if? You could have as much cache as you wanted? You could share a giant cache across servers, services and even clients? What if this was something you could simply add to the platform for 1free? 1Some features may require certain editions of Windows Server

11. Windows Server AppFabric AppFabric CACHING WORKFLOW HOSTING SERVICE HOSTING MONITORING SCALE OUT HIGH AVAILABILITY MANAGEMENT

12. Unified Cache View What is AppFabric Caching? An explicit, distributed, in-memory application cache for all kinds of data Caching clients can be across machines or processes Clients Access the Cache as if it was a large single cache Cache Layer distributes data across the various cache nodes

13. AppFabric Cache

14. Data Distribution - Partitioned Cache … Web Tier ASP.Net App ASP.Net App ASP.Net App Caching Client Caching Client Caching Client G H I D E F A B C Cache Service Cache Service Cache Tier Cache Service E G B D H A I C F Scale on Data Size More machines => More memory to cache Scale on Cache Throughput More machines => keys distributed across more machines => better throughput

15. Scale Test Output Load 1 Cache Server As load increases, throughput fails to scale latency increases Caching Tier Throughput Latency

16. Add a Second Cache Server Load Load Max Throughput increases Latency decreases Caching Tier Throughput Latency

17. Add a Second Cache Server Load Caching Tier Throughput Latency

18. Associated Press Caches metadata and news Serves 16 million hits per day Increased the amount of cached data 6 times.

19. System.Web.Cache

20. AppFabricDataCache

21. Copy Client DLLs Update Web.config … .NET 3.5 SP1 OR .NET 4 <hosts> <host name="BL1CDB8083714“ cachePort="22233" cacheHostName="DistributedCacheService"/> ….. </hosts> <localCacheisEnabled=“true" ../> <security … /> Application Application Application Caching Access Layer Caching Access Layer Caching Access Layer .NET 4 Install AppFabric Configure AppFabric Caching Service Caching Service Caching Service Configuration Store Deployment

22. Usage Pattern – Cache Aside (Explicit Caching) // Read from Cache Toy toyObj = (Toy) catalog.Get("toy-101"); Application Caching Access Layer // If Not present in the cache if (toyObj == null) { // Read from backend.. toyObj = ReadFromDatabase(); // Populate Cache catalog.Put("toy-101", toyObj); return toyObj; } Caching Service Database

23. Administration PowerShell cmdlets are used to administer the cache cluster Rich set of cmdlets for Cache cluster management Cache creation and monitoring

24. Hello AppFabric Cache

25. Using PowerShell Remember – PowerShell can also be called from .NET Code!

26. Security Domain Based Security Option Domain Account / Local Account based Authentication Only authorized servers can join the cluster Only authorized clients can connect to the cluster Transport Level Security Turn on/off Signing or Encryption Can turn off Cache Security Use Firewalls, IPSec, VLANs to protect cache grant-cacheallowedclientaccount RedDomainachine1$ grant-cacheallowedclientaccount RedDomainohn

27. Logical Hierarchy AppFabric Caching Service AppFabric Caching Service AppFabric Caching Service AppFabric Caching Service Named Cache : Product Catalog Named Cache : Electronics Inventory Regions Key Payload Tags Region A 121 xxxx “Toy” “Child” 123 yyyy “Toy” “Chair”.. Machine Host Physical processes hosting AppFabric Caching instance. Named Caches Can span across machines Defined in the configuration file Regions Physically co-located Container of Cache Items May be implicit or explicitly created Cache Item Key, Payload (Object ), Tags, TTL, Timestamps, Version

28. AppFabric Caching API // Create instance of cachefactory (reads appconfig) DataCacheFactory fac = new DataCacheFactory(); // Get a named cache from the factory DataCache catalog = fac.GetCache("catalogcache"); // Simple Get/Put catalog.Put("toy-101", new Toy("Puzzle", .,.)); // From the same or a different client Toy toyObj = (Toy)catalog.Get("toy-101"); // Region based Get/Put catalog.CreateRegion("toyRegion"); // Both toy and toyparts are put in the same region catalog.Put("toy-101", new Toy( .,.), “toyRegion”); Catalog.Put("toypart-100", new ToyParts(…), “toyRegion”); Toy toyObj = (Toy)catalog.Get("toy-101“,"toyRegion");

29. Access APIs – Tagging Items Tag hotItem = new Tag("hotItem"); catalog.Put("toy-101", new Toy("Puzzle"), new Tag[]{hotItem}, “toyRegion”); catalog.Put("toy-102", new Toy("Bridge"), “toyRegion”); // From the same or a different client List<KeyValuePair<string, object>> toys = catalog.GetAnyMatchingTag("toyRegion", hotItem);

30. Types of Data Grocery Shop Web Tier Shopping Cart Grocery Inventory Distributed Cache Grocery Catalog

31. Reference Data – Performance Catalog data doesn’t change often Unnecessary network cost to access from different machines Solution – Local Cache Application Application Get(K2) Get(K2) Put(K2, v3) AppFabric Caching Client AppFabric Caching Client Local Cache RoutingTable Routing Table Cache2 Cache3 Cache1 K2, V2 K2, V2 Primary for K1,V1 Primary for K3,V3 Primary for K2,V2 K1, V1 K2, V3 K3, V3

32. Reference Data – Bulk Get Bulk Fetch from region 200-300k ops per second Fewer network calls Catalog.BulkGet( new List<string>(){“toy-101”, “toy-102”} , “toyRegion”);

33. Activity Data – Session Integration Load Balance Requests No more sticky routing <sessionState mode="Custom“ customProvider="SessionStoreProvider"> <providers> <add name="SessionStoreProvider" type=“Microsoft.Data.Caching.DataCacheSessionStoreProvider, ClientLibrary“ cacheName="<YourNamedCache>"/> </providers> </sessionState> Drop in AppFabric Caching SessionStoreProvider … Caching Access Layer Caching Access Layer Session State stored in AppFabric Caching Allows session state to be shared amongst multiple applications Scale your Session Store Dynamically Cache Service Caching Service Caching Service Highly Available Application Application Application Caching Access Layer

34. Application Application Activity Data - Availability PUT Get(K2) AppFabric Caching Client AppFabric Caching Client Routing Table Routing Table Cache1 Cache2 Cache3 Primary for Primary for Primary for Replication Agent K3, V3 K1, V1 K2, V2 (K2, V2) K2, V2 Secondary for Secondary for Secondary for K2, V2 K2, V2 K3, V3 K1, V1

35. Resource Data - Optimistic Locking GetCacheItem returns a version object Every update to an object internally increments it's version Supply the version obtained along with the Put/Remove Put/Remove will succeed only if the passed in version matches the version in the cache Two clients access the same item Both update the item Second Client gets in first; put succeeds because item version matches; atomically increments the version First client tries put; Fails because the versions don’t match

36. Resource Data - Pessimistic Locking Client1: GetAndLock ("k1") Client3: Get ("k1") Client2: GetAndLock ("k1") GetAndLock gets lock handle Regular Get succeeds Other GetAndLock on same item fails Take locks on non-existent keys Allows you to co-ordinate calls for data K1

37. Data Race GET GET GET

38. Lock Non-Existent Key GET/LOCK GET/LOCK GET/LOCK Cache Service Cache Service Caching Service

39. Composite Race CALL WAIT WAIT Cache Service Cache Service Caching Service

40. Composite Race PUT UNLOCK GET GET Cache Service Cache Service Caching Service

41. Resource/Activity Data – Tracking Changes Cache Event notifications Register on any client to notify changes Batched Notifications DataCache.RegisterCacheLevelCallback( int filter, DataCacheChangeCallback delegate); DataCache.RegisterRegionLevelCallback( String region, int filter, DataCacheChangeCallback delegate); DataCache.RegisterKeyLevelCallback( String region, String key, int filter, DataCacheChangeCallback delegate);

42. Register Notification for Key “K3" Call Delegate Store Last LSN Application Map Keys to Partition AppFabric Caching Client Partition: P2 Last LSN: 19 Routing Table Poll Required Nodes Nodes Return List of Changes LSN Order Cache2 Cache3 Cache1 K2, V2 Primary for Primary for Primary for Change Log (Partition P2) Del K32 Del K43 Change Log Partition P1 Add K2 Del K32 Change Log 33 Add K1 34 Del K22 K1, V1 K3, V3 Scalable Notifications

43. Agenda

44. Pre-Fetch Hospital Data Center

45. Pre-Fetch Remote Clinic Hospital Slow!! Data Center WAN

46. Pre-Fetch Hospital Remote Clinic Data Center Cache Service WAN

47. Agenda

48. Web Platform Installer

49. Select Enterprise

50. Install AppFabric

51. Install AppFabric

52. endpoint.tv

53. AppFabric on MSDN http://msdn.microsoft.com/AppFabric

54. Thanks to our contributors