1. © 2010 Ariba, Inc. All rights reserved. The contents of this document are confidential and proprietary information of Ariba, Inc.

2. What is scalability?
© 2010 Ariba, Inc. All rights reserved. The contents of this document are confidential and proprietary information of Ariba, Inc.

3. Some standard definitions
The ability of a system, network, or process to
handle a growing amount of work in a
capable manner or its ability to be enlarged to
accommodate that growth. (Wikipedia)
The ability to handle increased workload by
repeatedly applying a cost effective strategy
for extending a system’s capacity (SEI)
© 2010 Ariba, Inc. All rights reserved. The contents of this document are confidential and proprietary information of Ariba, Inc.

4. Consider a simple web application
© 2010 Ariba, Inc. All rights reserved. The contents of this document are confidential and proprietary information of Ariba, Inc.

5. Load v/s Performance of a nonscalable system
© 2010 Ariba, Inc. All rights reserved. The contents of this document are confidential and proprietary information of Ariba, Inc.

6. Scalability Bottlenecks
Memory
 Out of memory
 Disk thrashing
 Fragmentation
CPU
 Overload
 Context switches
 I/O waits
Others
 Disk
 Network
© 2010 Ariba, Inc. All rights reserved. The contents of this document are confidential and proprietary information of Ariba, Inc.

7. Load v/s performance of a scalable
system (Ideal)
© 2010 Ariba, Inc. All rights reserved. The contents of this document are confidential and proprietary information of Ariba, Inc.

8. © 2010 Ariba, Inc. All rights reserved. The contents of this document are confidential and proprietary information of Ariba, Inc.

9. Improve application performance…
© 2010 Ariba, Inc. All rights reserved. The contents of this document are confidential and proprietary information of Ariba, Inc.

10. Improve application performance
Identify and fix performance bottlenecks
Algorithms
 DB queries
 Thread Deadlocks
 I/O
Why is it important
When you use less resources per task (processor
time, memory, N/W round trips etc)…
…You can handle a lot more load
© 2010 Ariba, Inc. All rights reserved. The contents of this document are confidential and proprietary information of Ariba, Inc.

11. Loose coupling paradigms - SOA
Loosely coupled interactions
One-to-one communications
Consumer-based trigger
Synchronous
© 2010 Ariba, Inc. All rights reserved. The contents of this document are confidential and proprietary information of Ariba, Inc.

12. Loose coupling paradigms - EDA
Decoupled interactions
Many-to-many communications
Event-based trigger
Asynchronous
© 2010 Ariba, Inc. All rights reserved. The contents of this document are confidential and proprietary information of Ariba, Inc.

13. Distribute work, data
Motivations:
Can scale independently
Failures are isolated
Segment Functionality
application pools
Segment Data
Based on functional areas
Horizontal split
© 2010 Ariba, Inc. All rights reserved. The contents of this document are confidential and proprietary information of Ariba, Inc.

14. Asynchronous communication
Motivations
Can scale components independently
 Can decouple availability
 Can spread peak load over time
Integrate different services asynchronously
 Point to point / publish subscribe
 Staged event driven architecture (SEDA)
© 2010 Ariba, Inc. All rights reserved. The contents of this document are confidential and proprietary information of Ariba, Inc.

15. Point to point
messaging
Publish-Subscribe
messaging
© 2010 Ariba, Inc. All rights reserved. The contents of this document are confidential and proprietary information of Ariba, Inc.

16. Aggressive Caching
Motivations:
Save processing cycles
 Save on network round-trip delays
Content caching on CDNs
Caching on clients (browsers/mobile devices)
Caching at application layer
Distributed caching
© 2010 Ariba, Inc. All rights reserved. The contents of this document are confidential and proprietary information of Ariba, Inc.

17. Cache Everywhere
Distributed In
memory Cache
Proxy
App Server
Web Browser
LRU Cache
Browser Cache
Page Cache
Query Cache
CDN
Resource
Cache
© 2010 Ariba, Inc. All rights reserved. The contents of this document are confidential and proprietary information of Ariba, Inc.
Database
Result Cache

18. Avoid or distribute state
Motivations:
Save memory and processing cycles
 Reduce machine affinity
Strive for statelessness
Maintain session data in browsers if possible
Store session state in distributed cache
© 2010 Ariba, Inc. All rights reserved. The contents of this document are confidential and proprietary information of Ariba, Inc.

19. Database
Simplify entity relationships to aid split
Use the right kind of Database lock
Avoid distributed transactions
Don’t select everything, read only as much
data as you can use
Consider NoSQL storage
© 2010 Ariba, Inc. All rights reserved. The contents of this document are confidential and proprietary information of Ariba, Inc.

20. © 2010 Ariba, Inc. All rights reserved. The contents of this document are confidential and proprietary information of Ariba, Inc.

21. How do we scale…
Individual community
© 2010 Ariba, Inc. All rights reserved. The contents of this document are confidential and proprietary information of Ariba, Inc.

22. Scaling storage: Multi SID
Goal: To be able to scale out DB storage as required
Application
Realm-Schema map
Persistence Layer
DB Instance #1
Schema 1
Schema 2
Schema 20
DB Instance #2
Schema 1
Schema 2
Schema 20
© 2010 Ariba, Inc. All rights reserved. The contents of this document are confidential and proprietary information of Ariba, Inc.

23. Clustering v/s Sharding
Clustering
 Oracle RAC, Hbase
 Automatically scale datastore
 Rebalances to distribute capacity
 Nodes communicate with each other
 Very complicated
 Cluster manager failure!
Sharding
 Data distributed manually
 Split database to add capacity
 Data does not move
 Nodes are unaware of each other
 Custom algorithm based on functional / key distribution
© 2010 Ariba, Inc. All rights reserved. The contents of this document are confidential and proprietary information of Ariba, Inc.

24. Scaling search: Arches
Goal: To be able to scale up search/publish activities linearly
© 2010 Ariba, Inc. All rights reserved. The contents of this document are confidential and proprietary information of Ariba, Inc.

25. Arches goals…
 Elastic architecture with ability to add capacity on the fly
 Sub-second search performance
 Improving indexing performance with customer isolation
 Eventually be used to build the global search service
all across Ariba
Arches interfaces…
 Pub API: Publish endpoint exposed over one way
messaging
 Search API: REST based search endpoint
 Pull API: REST based data pull endpoint to be
implemented by applications
 Manage API: REST based management endpoint
© 2010 Ariba, Inc. All rights reserved. The contents of this document are confidential and proprietary information of Ariba, Inc.

26. Lightweight Metadata: Overcoming
memory bottleneck
Problem:
All realms, even realms with no customization and
no activity consume lots of system resources
 Realms with no customization have the same foot
print as realms with lots of customization
Important for mid-market offering
Goals
© 2010 Ariba, Inc. All rights reserved. The contents of this document are confidential and proprietary information of Ariba, Inc.

27. Light weight metadata solution
Shape of a Class is now shared across
Variants
Sub Types computed dynamically
© 2010 Ariba, Inc. All rights reserved. The contents of this document are confidential and proprietary information of Ariba, Inc.

28. Dynamic capacity realms project
Goal: Remove downtimes for scaling our products.
Dynamic scalability
Tolerate change to cluster topology
Central connection manager
Goal: Improve database connection usage.
Central connection manager to distribute
database connections based on usage
Local pools & Global pool
© 2010 Ariba, Inc. All rights reserved. The contents of this document are confidential and proprietary information of Ariba, Inc.

29. ADE (Ariba data enrichment) scalability
Instance 1
Weblogic
Managed
Server
ADE
Client
Weblogic
Administrative
Server
Load balancing
(EJBs & RMI)
Weight based sticky
session
JMS
Product
Product
Engines
Engines
Instance 2
Weblogic
Managed
Server
JDBC
Clustering
JMS
Product
Product
Engines
Engines
Instance 3
Weblogic
Managed
Server
JMS
Product
Product
Engines
Engines
ADE
DB
© 2010 Ariba, Inc. All rights reserved. The contents of this document are confidential and proprietary information of Ariba, Inc.
SDB
(Ops)

30. © 2010 Ariba, Inc. All rights reserved. The contents of this document are confidential and proprietary information of Ariba, Inc.