Developers, Test Engineers, QA Engineers, Network Engineers, Operations Managers, Production Managers and Solution Architects joined us in Singapore to learn more about APM Lifecycle

1. Faster Apps, Faster Time to Market,
Faster Mean Time to Repair
Brad Goddard
Director of APM Pre-Sales Engineering - Asia and India
Compuware
Ardeshir Arfaian
Solution Director dynaTrace APAC
Compuware

2. Compuware Application Performance Management
We help organizations optimize the performance of
their business-critical applications
• Web, non-Web, mobile, streaming, cloud-based applications
• Across all customers, users, browsers, devices, infrastructure, and
geographies
• Rapid issue notification with actionable diagnostics
• Insight into how these issues affect your business (revenue, brand, cost)
SaaS, 4,000+ Customers Global Reach Recognized as
Cloud-Based and Worldwide • Over 80 offices in Industry Leader
On-Premises • 2,500+ enterprise 29 countries • Gartner:
Offerings customers worldwide Leader in APM magic
• Rapid startup and • 1,500+ SMB • Strategic service quadrant
payback customers delivery • Forrester Research:
• 12 of top 20 “…a complete view of
US sites end user
experience”*
• Ovum:
“Game-changing”
*”Trends: The Diversification Of End User Experiencing Monitoring”, Forrester Research, Inc., July 5, 2011

3. Your world is changing
Application visibility and optimization of the customer
experience are more important than ever.
Customers: Global New Devices: Proliferating
Applications: Distributed and loosely coupled Virtualization/Cloud: Exploding

4. Impact of to the business

5. The Problem Lifecycle

6. Why Agile Development took off

7. Story Points
It‘s Sprint Time!
Development Testing
Estimate Sprint Timeline
Remaining Production
Team Velocity

8. Story Points
You are in control!
Developme Testing
Estimate nt Sprint Timeline
Remaining Production
Team Velocity

9. Story Points
What happened?
Developme Testing
Estimate nt Sprint Timeline
Remaining Production
Team Velocity

10. Story Points Missed Goals and Estimates
Missed
Developme Testing
Estimate nt
Production Missed
Remaining
Goal
Team Velocity

11. 4 of 5 projects run over
time and/or budget.
Oxford University Regarding ITÂ Project Success (Saur & Cuthbertson, 2003) 11

12. Problem #1: Different Mindset
Source: http://dev2ops.org/blog/2010/2/22/what-is-devops.html

13. Problem #2: Dislocated Teams
Source: http://dev2ops.org/blog/2010/2/22/what-is-devops.html

14. Problem #3: Different Tools
Source: http://dev2ops.org/blog/2010/2/22/what-is-devops.html

15. Problem #4: Over the Fence Attitude
Source: http://dev2ops.org/blog/2010/2/22/what-is-devops.html

16. These Problems lead to …
Source: http://dev2ops.org/blog/2010/2/22/what-is-devops.html

17. A potential Solution
Source: http://dev2ops.org/blog/2010/2/22/what-is-devops.html

18. Real World Perf Test in
Feedback CI
ONE
Cloud based Toolset Architecture
Validation
Testing
Test in
Production Traditional
Load
Testing

19. Minimize and automate real Load Tests
Developing
Test Run Reproduction Refine Capturing
Re Run Tests Reproduction Refine Capturing Multiple Test Iterations
needed to analyze
Root-cause
Re Run Tests Reproduction Problem Analysis
Problem Solving
time
Developing
Test Run Reproduction Refine Capturing
Re Run Tests Reproduction Refine Capturing
•Eliminates Test Iterations
•Go directly to problem analysis
•Frees up resources for other proje
Re Run Tests Reproduction Problem Analysis
Problem Solving
time

20. Why Web Performance Matters: Impact of Poor
Performance
found that a 2 second
slowdown 4.3 % reduction in
revenue/user*
determined
that a
400
millisecond delay
0.59 %
fewer searches/user*
Source: Steve Souders @ Velocity Conference 2009
http://radar.oreilly.com/2009/07/velocity-making-your-site-fast.html

21. 21

22. ….
10000 Smart Phones
Sold
22

23. ….
80000 electronic
accessories sold
23

24. eBay Marketplace = Economy of Scale
22B 10B
10B page views/day
URL Requests / day
40
40M
9
9 Petabytes of data storage
$62
$62B
lines of code
2010 gross merchandise volume
100 5 300
100M 300M
active users
live listings
10000 75
10,000
5K
75B
search engine nodes
application servers database calls/day
24
Commercial data warehouse 100x larger than the research library of
US Congress

25. Pertinent Problems to be solved @ eBay
• Search
• Trust, Fraud and Risk
• Shipping and Logistics
• Ease of Payments
• User Experiences & Site Speed
• Data , Analytics and Business Intelligence
• Performance …
• … and many more 25

26. Benchmark Criteria
S No eBay Requirements Status
1 Deeper insight into the application very quickly, identifying the areas of 
code where the majority of each transaction's time is spent.
2 Integrate with Silk Performer / JMeter 
3 Java Diagnosis at method/class level. 
4 API Breakdown chart 
5 Memory Analysis graph 
6 Dashboard showing a comparison between 2 different test runs 
7 Trace export for QA, Dev 
8 Business and Technical dashboards 
9 Execution time / Time spent in individual methods of the Application 
code base
10 Time Spent on Service calls. (Entry/Exit times only) 
11 Performance of SQL Queries. 
26
12 Reports that would help identify the slow parts of the Application 
13 To be able to configure and monitor performance of specific business 
flows.

27. Link to Compuware APM
27

28. Selected
transactions opens
in Compuware APM
28

29. How much time is
spent on which
tier?
29
Are all my tiers
healthy?

30. Detailed view of transaction and flow
Each individual
transaction listed
Selected transaction
spent 42.77
milliseconds
Layers Transaction
spent time in
30

31. API level Drill down to
identify the method and
the call path having
maximum performance
impact
31

32. Global Solution Provider
Financial Services

33. Transaction Breakdown
<1sec, 1-2sec, 2-3sec, 3-4sec, 4-5sec, >5sec
With increasing load number of
Outliers >5sec is increasing

34. Only 85.44% of transactions under 1 second
Goal is to have 90% of transactions
under 1 second.

35. High Connection Checkin/Checkout
time
High RMI execution time

36. JDBC Connection Check-in/Check-out (1)
High Avg wait time for a connection
(10 seconds)

37. Low CPU / Low Memory consumption / High GC
Memory Utilization never climbs
above 25 % on certain JVMs.
Even though GC is high.

38. High GC JVM is spending 5.75 minutes per
minute on GC

39. GC versus Exec Time ratio
common.dbservices
JVM is spending 96% of it’s time on
GC
Further analysis showed that most
of GC time are major GCs

40. Root-Cause
JVM is running in Client mode

41. GC versus Exec Time ratio
common.dbservices
After switching JVM to server
mode, GC time is drastically
reduced.
Further analysis showed only minor
GCs

42. Before (client-mode JVM) / After (server-mode JVM)
SLA levels restored
With increasing load number of
Outliers >5sec is increasing
Moving production load to other
datacenter & applying –server
option in meantime

43. Innovation…
…and Getting Acquired

45. Faster Apps, Faster Time to Market,
Faster Mean Time to Repair
Brad Goddard
Director of APM Pre-Sales Engineering - Asia and India
Compuware
Ardeshir Arfaian
Solution Director dynaTrace APAC
Compuware