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2121: WebSphere eXtreme Scale
and Distributed Caching in
Commerce Solutions
2
Smarter Planet Solutions Require a Dynamic
Application Infrastructure
• Scale quickly and efficiently
• Optimize workload performance
• Flexibly flow resources
• Avoid downtime
• Save energy
• Automate management tasks
Smart
regions
Smart
weather
Smart
countries
Smart supply
chains
Smart
cities
Smart
industries
3
Business Needs Adoption Patterns
“Meet business
objectives
consistently, nimbly,
cost-effectively”
Application
Foundation
“Enable applications
to adapt to changing
market conditions”
Intelligent
Management
“Address extreme
demands of clients &
business models”
Extreme
Transaction
Processing
Dynamic Application Infrastructure
Builds on Smart SOA
4
4
Dynacache Disk Offload
• This allows a JVM to have a private disk based cache.
• It’s a feature heavily exploited by WebSphere Commerce
Server and other stack products.
• It allows caches much larger than is possible with a memory
only conventional cache.
• This is a 3 tier cache. The JVM has a small local cache, then
there is the file system cache and finally the disk itself.
4
5
5
Dynacache disk offload Server diagram
5
Disk
File
Cache
File
system
cache
App
Cache
File
system
cache
App
Cache
File
system
cache
App
Disk
File
Disk
File
6
6
WebSphere eXtreme Scale
• Organizes the memory from a number of JVMs as a single
logical shared cache.
• Clients can attach to the ‘cache’ using the network and can
also have an in process cache to reduce trips to the remote
cache when possible.
• No dependency on a large file system cache.
• No disk dependency, no SAN required.
• Cache is as large as the memory in the ‘grid’.
• Each record is stored once in the grid and shared by all
clients.
6
7
7
WebSphere eXtreme Scale Server
7
WXS
Near
Cache
App
WXS
Near
Cache
App
WXS
Near
Cache
App
WXS Container
WXS Container
WXS Container
WXS Container
Network
8
8
Test description
• WebSphere Application Server 6.1.0.26
• WebSphere eXtreme Scale V7.0
• Hardware: Two Socket Unix box, 16GB RAM and normal
disk.
• Gigabit ethernet
• Servlet generates a 72kbyte page.
• Dynacache being used to cache servlet page.
• 20Gb of data, 10% of which is ‘hot’.
8
9
9
Topology of test
9
Rational
Load
Driver
Rational
Load
Driver
ND
WXS
ND
ND
ND
WXS
WXSWXS
All boxes are 2 socket
with 16GB RAM
Network is Gigabit
10
10
Results using Dynacache disk offload
• File system cache too small:
– 273 pages/sec @ 730ms and 16% CPU
– 400 Disk IOPS
• File system cache large enough to stop all disk I/O
– 1620 page/sec @ 121ms and 42% CPU
– Network bottlenecks on HTTP side
10
11
11
Results: Remote WXS grid, no local cache AT ALL
• WXS
– 1700 pages/sec @ 116ms 73% CPU
– Network bottlenecked on the HTTP side
– No file system cache needed per JVM
– Data is compressed (2.5:1)
– Cost of fetching data from grid is therefore:
• 73%-42% = 31% of CPU
– Using a WXS Near cache will eliminate this ‘cost’.
11
12
12
WXS CPU usage
• The box running the WXS grid used 15% CPU at this load of
1700 page views/sec.
• This was with no near cache. A near cache will lower this
CPU significantly.
• BUT, 1700 pages view/sec is a lot of page views. One similar
box can serve up 11k cached page views/sec but would
require 10Gb ethernet.
12
13
13
Scaling Disk offload versus WXS
• WXS runs on commodity boxes and manages them so that
it’s fully fault tolerant in software, it doesn’t need expensive
reliable hardware to run on reliably.
• WXS can be scaled incrementally simply by adding another
box while it’s running. Perfect linear scaling.
• Disk offload almost always uses a SAN.
• SAN has a per gigabyte charge. You can’t incrementally
scale a SAN, you replace it.
13
14
14
Cache warmup is faster and cheaper with WXS
• The cache is shared between all WAS servers.
• Each cached entry is only generated ONCE, not ONCE PER
JVM as with disk offload.
• It’s about 2x faster to load the WXS cache versus a disk
offload based cache.
14
15
15
Invalidation/update once versus Invalidate/update all
• When the cache is invalidated with disk off load, the entry
must be regenerated on EVERY JVM in the cluster.
• WXS invalidates the cache entry ONCE per cluster.
• Only one WAS JVM needs to update the invalidated entry for
EVERY JVM as the cache is shared!
• This allows more frequent invalidates whilst cutting CPU and
disk I/O by 1/N over before.
15
16
16
Benefits summary
• Invalidation can occur more frequently as they cost less to do
using WXS than disk offload.
• No need for SAN costs for disk offload. Use the existing
boxes for memory/CPU/network.
• Faster/more efficient warm up and JVM instance starting
because of shared rather than private cache.
• Modern Web 2.0 like architecture.
16
17
Learn More About Dynamic Application Infrastructure!
Application Foundation
ibm.com/appfoundation
Intelligent Management
ibm.com/intellmgmt
Extreme Transaction Processing
ibm.com/xtp
ibm.com/appinfrastructure
18
Thank you for Attending. We Value Your Feedback !
• Please complete the session survey for this session by:
• Accessing the SmartSite on your smart phone or computer
at: http://imp2010.confnav.com
– Surveys / My Session Evaluations
• Visiting any onsite event kiosk
– Surveys / My Session Evaluations
• Each completed survey increases your chance to win an
Apple iPod Touch with daily drawing sponsored by
Alliance Tech
19
Questions?
20
Copyright and Trademarks
© IBM Corporation 2009. All rights reserved. IBM, the
IBM logo, ibm.com and the globe design are
trademarks of International Business Machines
Corporation, registered in many jurisdictions
worldwide. A current list of IBM trademarks is
available on the Web at "Copyright and trademark
information" at www.ibm.com/legal/copytrade.shtml.
Other company, product, or service names may be
trademarks or service marks of others.

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Initial deck on WebSphere eXtreme Scale with WebSphere Commerce Server

  • 1. 2121: WebSphere eXtreme Scale and Distributed Caching in Commerce Solutions
  • 2. 2 Smarter Planet Solutions Require a Dynamic Application Infrastructure • Scale quickly and efficiently • Optimize workload performance • Flexibly flow resources • Avoid downtime • Save energy • Automate management tasks Smart regions Smart weather Smart countries Smart supply chains Smart cities Smart industries
  • 3. 3 Business Needs Adoption Patterns “Meet business objectives consistently, nimbly, cost-effectively” Application Foundation “Enable applications to adapt to changing market conditions” Intelligent Management “Address extreme demands of clients & business models” Extreme Transaction Processing Dynamic Application Infrastructure Builds on Smart SOA
  • 4. 4 4 Dynacache Disk Offload • This allows a JVM to have a private disk based cache. • It’s a feature heavily exploited by WebSphere Commerce Server and other stack products. • It allows caches much larger than is possible with a memory only conventional cache. • This is a 3 tier cache. The JVM has a small local cache, then there is the file system cache and finally the disk itself. 4
  • 5. 5 5 Dynacache disk offload Server diagram 5 Disk File Cache File system cache App Cache File system cache App Cache File system cache App Disk File Disk File
  • 6. 6 6 WebSphere eXtreme Scale • Organizes the memory from a number of JVMs as a single logical shared cache. • Clients can attach to the ‘cache’ using the network and can also have an in process cache to reduce trips to the remote cache when possible. • No dependency on a large file system cache. • No disk dependency, no SAN required. • Cache is as large as the memory in the ‘grid’. • Each record is stored once in the grid and shared by all clients. 6
  • 7. 7 7 WebSphere eXtreme Scale Server 7 WXS Near Cache App WXS Near Cache App WXS Near Cache App WXS Container WXS Container WXS Container WXS Container Network
  • 8. 8 8 Test description • WebSphere Application Server 6.1.0.26 • WebSphere eXtreme Scale V7.0 • Hardware: Two Socket Unix box, 16GB RAM and normal disk. • Gigabit ethernet • Servlet generates a 72kbyte page. • Dynacache being used to cache servlet page. • 20Gb of data, 10% of which is ‘hot’. 8
  • 10. 10 10 Results using Dynacache disk offload • File system cache too small: – 273 pages/sec @ 730ms and 16% CPU – 400 Disk IOPS • File system cache large enough to stop all disk I/O – 1620 page/sec @ 121ms and 42% CPU – Network bottlenecks on HTTP side 10
  • 11. 11 11 Results: Remote WXS grid, no local cache AT ALL • WXS – 1700 pages/sec @ 116ms 73% CPU – Network bottlenecked on the HTTP side – No file system cache needed per JVM – Data is compressed (2.5:1) – Cost of fetching data from grid is therefore: • 73%-42% = 31% of CPU – Using a WXS Near cache will eliminate this ‘cost’. 11
  • 12. 12 12 WXS CPU usage • The box running the WXS grid used 15% CPU at this load of 1700 page views/sec. • This was with no near cache. A near cache will lower this CPU significantly. • BUT, 1700 pages view/sec is a lot of page views. One similar box can serve up 11k cached page views/sec but would require 10Gb ethernet. 12
  • 13. 13 13 Scaling Disk offload versus WXS • WXS runs on commodity boxes and manages them so that it’s fully fault tolerant in software, it doesn’t need expensive reliable hardware to run on reliably. • WXS can be scaled incrementally simply by adding another box while it’s running. Perfect linear scaling. • Disk offload almost always uses a SAN. • SAN has a per gigabyte charge. You can’t incrementally scale a SAN, you replace it. 13
  • 14. 14 14 Cache warmup is faster and cheaper with WXS • The cache is shared between all WAS servers. • Each cached entry is only generated ONCE, not ONCE PER JVM as with disk offload. • It’s about 2x faster to load the WXS cache versus a disk offload based cache. 14
  • 15. 15 15 Invalidation/update once versus Invalidate/update all • When the cache is invalidated with disk off load, the entry must be regenerated on EVERY JVM in the cluster. • WXS invalidates the cache entry ONCE per cluster. • Only one WAS JVM needs to update the invalidated entry for EVERY JVM as the cache is shared! • This allows more frequent invalidates whilst cutting CPU and disk I/O by 1/N over before. 15
  • 16. 16 16 Benefits summary • Invalidation can occur more frequently as they cost less to do using WXS than disk offload. • No need for SAN costs for disk offload. Use the existing boxes for memory/CPU/network. • Faster/more efficient warm up and JVM instance starting because of shared rather than private cache. • Modern Web 2.0 like architecture. 16
  • 17. 17 Learn More About Dynamic Application Infrastructure! Application Foundation ibm.com/appfoundation Intelligent Management ibm.com/intellmgmt Extreme Transaction Processing ibm.com/xtp ibm.com/appinfrastructure
  • 18. 18 Thank you for Attending. We Value Your Feedback ! • Please complete the session survey for this session by: • Accessing the SmartSite on your smart phone or computer at: http://imp2010.confnav.com – Surveys / My Session Evaluations • Visiting any onsite event kiosk – Surveys / My Session Evaluations • Each completed survey increases your chance to win an Apple iPod Touch with daily drawing sponsored by Alliance Tech
  • 20. 20 Copyright and Trademarks © IBM Corporation 2009. All rights reserved. IBM, the IBM logo, ibm.com and the globe design are trademarks of International Business Machines Corporation, registered in many jurisdictions worldwide. A current list of IBM trademarks is available on the Web at "Copyright and trademark information" at www.ibm.com/legal/copytrade.shtml. Other company, product, or service names may be trademarks or service marks of others.

Editor's Notes

  • #3: Main point: IBM believes it is time to build a smarter planet because the world is more instrumented, interconnected and intelligent than ever before. To take advantage of the new opportunities that a smarter planet presents, organizations need to be agile while optimizing their costs. That requires having a Dynamic Application Infrastructure. which can scale quickly and efficiently to meet changing demands. Workload performance must be optimized and resources need to flow flexibly to where they are needed. Reliability and integrity of transactions is paramount. And being able to efficiently manage IT infrastructure while simultaneously managing and saving energy usage are critical.
  • #4: A Smart SOA Application Infrastructure consists of 3 common Adoption Patterns (Smarter Planet messaging for each adoption pattern): Application Foundation – IBM WebSphere provides Application Foundations that are designed from the ground up to enable company IT operations and development to increase business agility and optimize costs through the efficient delivery of innovative, high-performing business applications. To help ensure your applications can keep up with the demands of a Smarter Planet, regardless of the situation, the WebSphere Application Server Family provides a choice of foundations for building, deploying and managing all types of applications. From business-critical and key enterprise-wide applications to the smallest departmental-level applications IBM provides the right-size foundation to balance key considerations such as security, scalability and manageability with cost and simplicity in homogenous or, especially, mixed environments. 2. Intelligent Management – to thrive in a smarter planet, companies to intelligently manage their application infrastructures. The cost of managing and running today’s business applications - from enterprise wide to departmental level - is far exceeding the cost of the software itself. At the same time, the need to rapidly adapt to changing marketplace conditions and address higher service level expectations has never been greater. Organizations need to ensure that their businesses become smarter, controlling costs and optimizing the management of their business applications to create new possibilities across the enterprise and to seize tomorrow’s opportunities.The IBM WebSphere® portfolio provides a powerful and comprehensive set of cloud computing and virtualization solutions for intelligently managing the infrastructure for SOA applications, services and environments, ultimately enabling smarter business outcomes. These solutions are designed to deliver robustness and agility to business applications, enabling organizations to adapt to changing marketplace conditions while lowering costs. They enable the rollout of innovative new SOA services and support the faster pace of change that business and society demand. 3. Extreme Transaction Processing – Our planet is becoming increasingly smart: interconnected, instrumented and intelligent. As more people around the planet join the digital world, they drive exponential growth of business and non-business transactions for everything from web commerce and RFID processing in dynamic supply chains to real-time financial interactions to on-line social networking and gaming. Organizations need to ensure that their critical applications can meet the requirements of rapid increases in demand, can deliver immediate, consistent responses, and can scale as necessary. Additionally, there is a need to enhance application performance to meet rising customer expectations around application response times while managing the costs of your infrastructure. The IBM WebSphere® portfolio offers extreme transaction processing (XTP) capabilities that ensure, you have a SMART SOA™-based application infrastructure which can support your most demanding business-critical applications. WebSphere improves your business agility by allowing you to overcome traditional IT performance limitations to generate the levels of global scale, process efficiencies, and business intelligence needed for smarter business outcomes, like sustainable competitive advantage, maximized revenues and avoidance of potential fines stemming from inconsistent response and Service Lifecycle Agreement violations.
  • #18: Speakers: you can change the content of this slide to more specific follow up links if you’d like