Architecting and Tuning IIB/eXtreme Scale for Maximum Performance and Reliability, Featuring TBC

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Architecting & Tuning IIB /
eXtreme Scale for Maximum
Performance and Reliability
AJ Aronoff
Infrastructure Practice Director, Prolifics
Robert Gus Fort
Manager, Integration Development

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Agenda
 Speaker Introduction
 Challenge: The need for Speed & Scalability
 Extreme Scale Basics
 Use Cases
 Performance Tuning
 Measurement - Bottlenecks
 Infrastructure
 Maximizing Reliability and Reducing Downtime
 References & What’s Next
2

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Speaker Introduction
A.J. Aronoff
Infrastructure Practice Director,
Prolifics
AJ Aronoff is a Practice Director covering The IBM Integration Product Suite
(IIB, Extreme Scale, MQ, WAS, SmartCloud APM, Data Power) for Prolifics.
During his twenty plus years at Prolifics he has focused on reliability (Zero
Downtime, High Availability, Disaster Recovery), scalability, performance and
monitoring. He is a frequent speaker on IIB, MQ, Security as well as industry
specific topics.
Robert Gus Fort
Manager, Integration Development
Prolifics Customer
Gus Fort learned about the need for speed and 100% reliability in
the U.S. Air Force. Since then he has been applying that same
quest for reliability and performance in his current role with a leading
automotive services retailer. His current projects use eXtreme Scale
to give customers a satisfying and rewarding experience on a high
speed and reliable system. Nearly doubling the number of stores
while reducing risk and increasing customer satisfaction
3

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5-Years Compound
Annual Growth Rate
19%
Employees
Worldwide
1,500
Global Presence
United States, United Kingdom, Germany, India
20+
Technology
Accelerators
550+
Technical
Certifications
Over 10 Technology and
Solutions Awards since 2009
including Business Agility,
Customer Integration and Digital
Experience, the first ever
Beacon Laureate for Business
Agility
Over 160 global customers
are currently Fortune
1000 companies
Best-in-class architects and
specialty experts:
BPM, Integration, Digital
Experience, Security, Testing,
Business Analytics and
Enterprise Content Management
End-to-End Project
Expertise
Rate of Repeat
Engagements*
91%
Prolifics at a Glance
Years in
Business
35+
Offices
14
Awards
Technology Expertise
Fortune 1000
*based on % revenue Source – December 2013 internal revenue metrics

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Extreme Scale Caching & The Need for
Speed
“As the world becomes more instrumented, interconnected
and intelligent, Internet-based activities, online
transactions and data volumes increase. Further, these
increasing amounts of data, along with rising consumer
expectations and the need to maintain a competitive edge
require fast and reliable performance…. Elastic caching is
the answer.”
- IBM Software Technical White Paper
- ftp://ftp.software.ibm.com/software/au/data/pdf/Elastic_CachingWP.pdf
3/5/2015
5

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Challenge: The Need For Speed &
Scalability
6
• How scalable is your System?
• When the peak load doubles does response time:
• A) stay the same, B) double C) quadruple D) fail
• Have you tested your system to destruction?
• How high can the load go before failure
• Where are the bottlenecks and single points of failure
• Focus on Extreme Scale
• Benefit - the approach taken for measurement,
monitoring, bottleneck identification will work on many
systems.

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Extreme Scale Basics: Traditional Cache
Operation
App
App
App
App
EIS
A
A
A
A
App
Invalidationchatter
New Server with
cold cache
Redundant copies of data at
different versions
Invalidation load
increases with
cluster size
High load on EIS
Invalidationchatter
• Traditional in JVM cache
• Cache capacity determined by
individual JVM Size
• Invalidation load per server
increases as cluster grows
• Cold start servers hit the
information system even when
data is cached in cluster
• Lower performance as load
increases due to invalidation
chatter
• No redundancy of cached data

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Basics: WXS based Cache Operation
App
App
App
App
EIS
A
B
D
C
C’
D’
A
A
AppA
B’
A’
Cache is
4x larger!
Cache is
5x larger!
• Cluster Coherent cache
•Cache capacity determined by total
cluster size
Size of each cache = M
# JVMs = N
Total Cache = M x N
• No invalidation chatter
• Linearly scalable
• Less load on database and
no cold start spikes
• Predictable performance as load
increases
• Cached data can be stored
redundantly
Cache cluster can be co-
located with the application or
run in it’s own tier.

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Extreme Scale Basics: How it Works
9

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Extreme Scale Basics: Architecture
10
Back End Services
 Elastic Cache
Application or IIB Tier
Web Server Tier

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Use Case 1: Universal Application State
11
 Single replacement for multiple local caches
 Consistent response times
 Reduces Application Server JVM heap size
 Improved memory utilization - more memory
for applications
 Faster Application Server start-up
 Removes invalidation chatter of local caches
 Applications move application state to grid
 Stateless applications scale elastically
 Application state can be shared across data
 centers for high availability

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Use Case 2: Side Cache Pattern
12
 Client first checks the grid before using the
data access layer to connect to a back end
data store
 If an object is not returned from the grid (a
cache “miss”), the client uses the data access
layer as usual to retrieve the data
 The result is put into the grid to enable faster
access the next time
 The back end remains the system of record,
and usually only a small amount of the data is
cached in the grid
 An object is stored only once in the cache,
even if multiple clients use it
 Thus, more memory is available for caching,
more data can be cached, which increases
the cache hit rate
 Improve performance and offload
unnecessary workload on backend systems

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Use Case 2: ESB - Side Cache Pattern
13
 Easily integrates into the existing
business process
 No code changes to the client application or
backend application
 Simply add the side cache mediation at the ESB
layer
 Significantly reduces the load on the
back-end system by eliminating
redundant requests
 Eliminates costly MIPS by eliminating redundant
request
 Allows for more “REAL” work to be performed
 Improves overall response time
 Minimizes the need to scale hardware to
increase processing capacity since the back-
end system no longer has to handle redundant
requests
 Response time from elastic cache is
in milliseconds

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Use Case 2: ESB - Side Cache Pattern
14
 Product Search
 Existing performance without cache
 Targeted SLA
 Full Load of cache data
 Delta processing
 Crash preparation

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Performance Tuning - Measurement
15
 Several useful tools include:
 For MQ performance - the MS0P Support Pac - allows us to
see which Queues had buildup
 For IIB WebAdmin - interfaces with the Flow Statistic to
identify nodes in a flow indentifying slow (high elapse time), or
inefficiency from a CPU usage point of view
 For DP, am AJAX Web "Dashboard" - helps us to track
Overall CPU, TPS, Memory and specific MPG nodes and their
respective elapse times
 Captured CPU time for all servers, the TPS rate (end to end
as well as per product) and by performing multiple runs, using
the IBM Performance harness

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SupportPac MS0P: MQ Explorer plug-ins
 A variety of WMQ Explorer plug-ins are provided
 Format event messages into human-readable text
 Trace route function to determine the path messages take
 Export WMQ Explorer display panels to CSV
 Remote management of Windows, UNIX and Linux systems
 Utilities
 Qtune
 MQIDecode turns codes into symbolic names
 OAM logging utility records PCF commands sent to CMDSVR
16

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SupportPac MS0P: Event Message
Context Menu
After installing SupportPac MS0P, new context menu items appear
in WebSphere MQ Explorer. The "Format Event Message" option
shows up when right-clicking on an event queue.
17

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SupportPac MS0P: GUI Display
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Details of Extreme Scale running
inside WAS 8.5
 Use PMI for monitoring
 WebSphere Application Server provides a sophisticated performance
monitoring infrastructure (PMI). It can be used to gather performance
statistics of all components inside an application server. WebSphere eXtreme
Scale takes advantage of this infrastructure to collect performance statistics
relevant to the grid. Metrics are grouped within the following PMI modules:
 objectGridModule
 Provides metrics about transaction response time.
 mapModule
 Provides metrics about map and index count and time statistics. These
include hit rate per map, # of entries per map, # of results per index
 agentManagerModule
 Provides statistics related to map-based agents. These include number of
agent executions, number of partitions involved, time required to run map
and reduce operations, time required to serialize agents, and related
results.
 queryModule
 Provides statistics about query processing and execution. These include
the amount of time to create a query plan and run the query, the number of
times that a query has been run, and so on.
19

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Infrastructure: Avoid Single Points of
Failure
20
 Fast network: 10 gigabit +
 Multiple Nics
 Nearby Catalogs
 Fast Disk Drives: The new slid state
drives (SSDs) are incredible.
 Trace route: On multiple occasions
we have found very unexpected
network delays. Measure early and
often

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Erasmus: Prevention is Better than Cure
 WXS 8.6 makes it easier to recover from crashes.
 Log analysis was done exploring the cause of those crashes
The next few slides show how WAS 8.5 can
prevent some of those crashes
21

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WebSphere Application Server V8.5
 Three primary goals:
 Provide intelligent management and enhanced resiliency for your
application server environment
 Improve operation, security, control
 Integration of the application server - providing a fast, flexible, and simplified
application development environment that allows you to deliver rich user experience
faster
22

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Intelligent management
23

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Health Management
24
 Automatically detect and handle application health problems
 Without requiring administrator time, expertise, or intervention
 Intelligently handle health issues in a way that will maintain continuous availability
 Each health policy consists of a condition, one or more actions, and a target set of processes
 Includes health policies for common application problems
 Customizable health conditions and health actions
 WebSphere Application Server Version 8.5 can monitor servers for common health
problems and take corrective action. There are several health conditions that can be defined
using health policies. When a violation of a health policy is detected, an action plan can be put
into effect automatically – including sending email, capturing diagnostic data, and restarting the
application server. Application server restarts are smart and done in a way to prevent outage and
service policy violations.

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Benefits of Extreme Scale running inside WAS 8.5
 Catalog and container servers as managed application
servers
 Catalog service domain configuration
 Simplified connection to the grid
 Simplified grid container management
 Simplified administration and management
 Use PMI for monitoring
25

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Details of Extreme Scale running inside WAS 8.5
 Catalog and container servers as managed application servers
 Catalog and container servers are defined as standard application server instances
within a WebSphere Application Server cell. They receive all the health/resiliency
benefits of running inside WAS 8.5
 For high availability reasons, use dedicated clusters for catalog and container servers.
Best results can be achieved by having at least three catalog server instances that are
in different physical locations
 Also, use a distinct WebSphere cluster to host the grid infrastructure (container
servers) to decouple it from catalog servers and applications
 Catalog service domain configuration
 Catalog service domains define a group of catalog servers that are associated to a
grid infrastructure. Catalog service domains can be easily defined as administered
resources within a WAS ND environment
 Simplified connection to the grid
 In a stand-alone environment, connecting to the grid requires knowledge of the host
name and port of the catalog servers. In an integrated environment, this requirement
can be simplified by using a catalog service domain. More specifically, the catalog
service domain can be queried to obtain the list of catalog service endpoints that client
uses to establish a connection to the catalog service
26

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Details of Extreme Scale running inside WAS 8.5
 Simplified grid container management
 Catalog and container servers are Grid configurations can be packaged
within a Java Platform, Enterprise Edition module (Web or EJB module)
and deployed as a standard enterprise archive (EAR) file. When a Java
Platform, Enterprise Edition application starts, WebSphere eXtreme Scale
checks for grid configuration files (objectGrid.xml and
objectGridDeployment.xml) within the META-INF folder of the EJB and
WEB modules. If only objectGrid.xml is found, the application server is
assumed to be a grid client. If both objectGrid.xml and
objectGridDeployment.xml are present, the application server acts as a
container by implementing the specified deployment policies
 Simplified administration and management
 Catalog service domains define a group of catalog servers that are
associated to a grid infrastructure. Catalog service domains can be easily
defined as administered resources within a WebSphere Application Server
Network Deployment environment
27

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Monitoring helps find problems
Monitor for operational exceptions and to maintain health of
the system:
 Expand the default size of error logs
 Check error logs for exceptions
 Archive error logs for forensic analysis
 Alert on messages in DLQ or error queue
 Distinguish between operational vs. Application alerts
28

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FFSTSummary
 Why learn to use the tools that summarize FFST and
error files?
 “Because that’s where the errors are.”
 FFST files contain useful information on serious
problems
 http://hursleyonwmq.wordpress.com/2007/05/04/introduction-to-ffsts/
 What is FFST?
 FFST stands for First Failure Support Technology, and is
“designed to create detailed reports for IBM Service with
information about the current state of a part of a queue
manager together with historical data”
 FFSTSummary is a tool that produces one line summaries of
these serious problems, arranged in chronological order
29

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Lesson Learned
 Install and Use the best tools for measurement
 Identify bottlenecks (flows, queuries)
 Use the best available hardware:
 Solid State Drives
 Fast network: 10 gigabit +
 Multiple Nics
 Tune one thing at a time
 It is a capital crime to theorize in advance of your data
30

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Learn More… Prolifics at InterConnect
31
Monday How Broadcast Music, Inc.
Devised and Enabled Enterprise
Architecture from Corporate
Strategy
12:15 PM - 1:15 PM
Integrating Salesforce.com and
Oracle ERP Using IBM WebSphere
Cast Iron
2:00 PM - 3:00 PM
Recommended Design
Considerations for Enterprise
Monitoring using SCAPM and
Netcool OMNIbus
5:00 PM - 6:00 PM
Tuesday Smarter Integration Using the IBM
SOA Foundation Stack: Best
Practices and Lessons Learned
8:00 AM - 9:00 AM
Best Practices for Monitoring Your
Cloud Environment and
Applications
9:30 AM - 10:30 AM
Applicability of IBM SOA Approach
In Manual Processes Automation
11:30 AM-11:50 AM
Leveraging Governance in the
IBM WebSphere Service Registry
and Repository for IIB and
DataPower
12:30 PM - 1:30 PM
Broadcast Music Inc. Release
Rockstars: Program-Wide DevOps
Success with UrbanCode Deploy
3:30 PM - 4:30 PM
Empowering SmartCloud APM -
Predictive Insights and Analysis: A
Use Case Scenario
5:30 PM - 6:30 PM
Wednesday Architecting and Tuning
IIB/eXtreme Scale for Maximum
Performance and Reliability,
Featuring TBC
8:00 AM - 9:00 AM
MasterCard's Modeling and
Governance of Decisions and
Processes for Improved Fraud
11:00 AM - 12:00 PM
How BMI is Revolutionizing the
Music Business Using IBM’s BPM
and Integration Technology
2:00 PM - 3:00 PM
Integrating IBM Pure Application
Systems and IBM Urbancode
Deploy: A GE Capital Case Study
2 :00 PM – 3:00 PM
Thursday Aetna’s Vision for a Healthier
World: Smarter Architecture and a
Scalable Integration Bus
9:00 AM - 10:00 AM
Meet the Expert - Delivering
Enterprise Applications: Faster.
Cheaper. Better
Thursday 12:00 PM – 12:50 PM
Using the Power of IBM Tivoli
Common Reporting to Make Smart
Decisions: The Untold Story
2:30 PM - 3:30 PM

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Let’s Continue the
Conversation….
A.J. Aronoff
aj@prolifics.com
Visit these useful links on the Prolifics website:
Case Studies http://www.prolifics.com/resources/case-studies
Webcasts http://www.prolifics.com/resources/webcasts
Videos http://www.prolifics.com/resources/videos
Solution Briefs http://www.prolifics.com/resources/solution-briefs
Blog http://www.prolifics.com/blog
Twitter http://www.twitter.com/prolifics
Facebook http://www.facebook.com/ProlificsTech
Prolifics TV http://www.youtube.com/prolificstv

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Architecting and Tuning IIB/eXtreme Scale for Maximum Performance and Reliability, Featuring TBC

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