Microsoft Windows Server AppFabric

Windows Server AppFabric
Speaker: Ron Jacobs
Senior Technical Evangelist, Microsoft
Silicon Valley SQL Server User Group
April 2010
Mark Ginnebaugh, User Group Leader, mark@designmind.com

AppFabric is a set of integrated technologies that make it easier to build, scale, and manage Web and composite applications that run on IIS.

Ron Jacobs of Microsoft
Ron Jacobs
Senior Technical Evangelist
Microsoft Platform Evangelism Group in Redmond
Current focus
Windows Communication Foundation (WCF)
Windows Workflow Foundation (WWF)
For more information about this meeting: http://www.meetup.com/The-SiliconValley-SQL-Server-User-Group/calendar/12626266

Designing and Delivering Scalable and Resilient Web Services
Ron Jacobs
Sr. Technical Evangelist, Microsoft
http://blogs.msdn.com/rjacobs
Video of this session:
http://live.visitmix.com/MIX10/Sessions/FT11

Agenda

Simple
Do the simplest thing that will possibly work

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

Typical Web Architecture

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

Agenda

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

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

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

AppFabric
CACHING
WORKFLOW HOSTING
SERVICE HOSTING
MONITORING
SCALE OUT
HIGH AVAILABILITY
MANAGEMENT
AppFabric Cache – Formerly known as Code Name “Velocity”

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

AppFabric Cache

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

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

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

Add Third Cache Server
Load
Caching Tier
Throughput
Latency

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

System.Web.Cache

AppFabricDataCache

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

Usage Pattern – Cache Aside (Explicit Caching)
// Read from Cache
Toy toyObj = (Toy)
catalog.Get("toy-101");
Application
// 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

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

Hello AppFabric Cache
Demo

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

AppFabric Cache Codeplex Tool
http://mdcadmintool.codeplex.com/
Demo

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 RedDomainMachine1$
grant-cacheallowedclientaccount RedDomainJohn

AppFabric Caching Logical Hierarchy
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 -> Cache Host -> Named Caches -> Regions -> Cache Items -> Objects
Host
Physical processes hosting AppFabric Caching instance.
Named Caches
Can span across machines
Defined in the configuration file
Cache Item
Key, Payload (Object ), Tags, TTL, Timestamps, Version
Regions
Physically co-located Container of Cache Items
May be implicit or explicitly created

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");

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);

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

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
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

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”);

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
…
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

Application
Application
Activity Data - Availability
PUT
Get(K2)
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

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

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

Data Race
GET
GET
GET

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

Composite Race
CALL
WAIT
WAIT
Cache Service
Cache Service
Caching Service

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

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);

Register Notification for Key “K3"
Call Delegate
Store Last LSN
Application
Map Keys to Partition
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

Agenda

Data Center
Pre-Fetch
Hospital

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

Pre-Fetch
Hospital
Remote Clinic
Cache Service
Data Center
WAN

Agenda

Web Platform Installer

Select Enterprise

Install AppFabric

endpoint.tv

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

To learn more or inquire about speaking opportunities, please contact:
Mark Ginnebaugh, User Group Leader
mark@designmind.com

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Microsoft Windows Server AppFabric

by Mark Ginnebaugh on May 07, 2010

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Microsoft Windows Server AppFabric — Presentation Transcript