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Page 1: Faster apps. faster time to market. faster mean time to repair

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

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Compuware Application Performance Management

• 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)

We help organizations optimize the performance of their business-critical applications

SaaS, Cloud-Based and

On-Premises Offerings

• Rapid startup and payback

4,000+ Customers Worldwide

• 2,500+ enterprise customers

• 1,500+ SMB customers

• 12 of top 20 US sites

Global Reach • Over 80 offices in

29 countries worldwide

• Strategic service delivery

Recognized as Industry Leader

• Gartner: Leader in APM magic quadrant

• Forrester Research: “…a complete view of end user experience”*

• Ovum: “Game-changing”

*”Trends: The Diversification Of End User Experiencing Monitoring”, Forrester Research, Inc., July 5, 2011

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Your world is changing

Customers: Global

Applications: Distributed and loosely coupled

New Devices: Proliferating

Virtualization/Cloud: Exploding

Application visibility and optimization of the customer experience are more important than ever.

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Impact of to the business

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The Problem Lifecycle

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Why Agile Development took off

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It‘s Sprint Time!

Story Points

Sprint Timeline Estimate

Remaining

Team Velocity

Development Testing

Production

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You are in control!

Story Points

Sprint Timeline Estimate

Remaining

Team Velocity

Developme

nt

Testing

Production

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What happened?

Story Points

Sprint Timeline Estimate

Remaining

Team Velocity

Developme

nt

Testing

Production

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Missed Goals and Estimates Story Points

Estimate

Remaining

Team Velocity

Developme

nt

Testing

Production Missed

Goal

Mis

se

d

Es

tim

ate

s

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4 of 5 projects run over

time and/or budget.

11 Oxford University Regarding ITÂ Project Success (Saur & Cuthbertson, 2003)

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Problem #1: Different Mindset

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

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Problem #2: Dislocated Teams

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

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Problem #3: Different Tools

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

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Problem #4: Over the Fence Attitude

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

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These Problems lead to …

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

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A potential Solution

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

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Perf Test in

CI

Cloud based Testing

ONE Toolset Architecture

Validation

Test in Production

Real World Feedback

Traditional Load Testing

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Minimize and automate real Load Tests Developing

Test Run Reproduction Refine Capturing

Re Run Tests Reproduction Refine Capturing

Re Run Tests Reproduction Problem Analysis

Problem Solving

Multiple Test Iterations

needed to analyze

Root-cause

time

Reproduction Refine Capturing

Re Run Tests Reproduction Refine Capturing

Re Run Tests Reproduction

Problem Solving

•Eliminates Test Iterations

•Go directly to problem analysis

•Frees up resources for other projects

Developing

Test Run

time

Problem Analysis

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21

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…. 10000 Smart Phones

Sold

22

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…. 80000 electronic accessories sold

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10B

eBay Marketplace = Economy of Scale

300 300M live listings 100 100M active users

9 9 Petabytes of data storage

2 2B page views/day

75 75B database calls/day 10000 10,000 application servers

$62 $62B 2010 gross merchandise volume

40 40M lines of code

10B URL Requests / day

5 5K search engine nodes

24

Commercial data warehouse 100x larger than the research library of

US Congress

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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

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26

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.

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.

Benchmark Criteria

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27

Link to Compuware APM

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28

Selected transactions opens in Compuware APM

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29 Are all my tiers healthy?

How much time is spent on which

tier?

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Detailed view of transaction and flow

30

Layers Transaction

spent time in

Each individual

transaction listed

Selected transaction

spent 42.77

milliseconds

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31

API level Drill down to

identify the method and

the call path having

maximum performance

impact

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Global Solution Provider

Financial Services

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Transaction Breakdown <1sec, 1-2sec, 2-3sec, 3-4sec, 4-5sec, >5sec

With increasing load number of

Outliers >5sec is increasing

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Only 85.44% of transactions under 1 second

Goal is to have 90% of transactions

under 1 second.

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High RMI execution time

High Connection Checkin/Checkout

time

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JDBC Connection Check-in/Check-out (1)

High Avg wait time for a connection

(10 seconds)

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Low CPU / Low Memory consumption / High GC

Memory Utilization never climbs

above 25 % on certain JVMs.

Even though GC is high.

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High GC JVM is spending 5.75 minutes per

minute on GC

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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

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Root-Cause JVM is running in Client mode

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GC versus Exec Time ratio common.dbservices

After switching JVM to server

mode, GC time is drastically

reduced.

Further analysis showed only minor

GCs

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Before (client-mode JVM) / After (server-mode JVM)

With increasing load number of

Outliers >5sec is increasing

Moving production load to other

datacenter & applying –server

option in meantime

SLA levels restored

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Innovation…

…and Getting Acquired

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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