This document discusses managing performance for Java applications. It defines key performance metrics like response time, throughput, and availability. It describes different types of measurements that can be taken, such as cyclic and event-based measurements. It also discusses challenges in measuring performance across different systems and tools. Finally, it outlines common operations tasks for monitoring performance, detecting issues, and diagnosing problems.

1. Managing Java Applications
@AloisReitbauer

2. 3

4. DevOps
to the rescue?

5. Don’t just build
software that runs

6. Build software that
somebody else can
run

7. What is performance
and how do we
measure it?

8. How we define Performance
• Response Time
The time it takes for an application to respond to a user request.
• Throughput
The amount of concurrently processed request in a given time period.
e.g.: requests/minute.
• Availability
Status of our systems. Are they up and running for us and our users?
• Accuracy
Is the response what the user actually expected? Are there any errors

9. Performance Pyramid
Business
Application
Container
System Performance

10. Types of Measurement
• Cyclic Measurements
– Are collected ar regular time intervals
– Are time based
– JMX, CPU, Memory
• Event-based measurements
– Are collected as a request occurs
– Are transactional
– Response Times, CPU consumption

11. Blind Men and
Elephants again

12. How can this happen?
A: Our response time is 2.3 seconds
B: Our response time is 1.5 seconds
C: Our response time is 6 seconds

13. Measurement Aggregation
• Minimum and Maximum
The best and the worst request. Beware of outliers.
• Average
Sum/Count. Uses in many cases. Quality depends on actual values.
• Median
What 50 percent of our users see.
• Percentile
What n percent of our users see.

14. Use percentiles for
event-based
measures

15. Use averages for
cyclical measures

16. Agree on Measurement Approach
Page Load Time HTTP Request Time 95 % Servlet Time
Network
Browser Firewall Sniffer Web Server Application
Server
Request Time (max)

17. System and Container Metrics

18. Time-Based vs. Event-Based Measurement

19. Transactional Measurement

20. Transaction Flow Visualization

21. Focus on a specific transaction

22. Visual Problem Identification

23. How do we manage
performance and
solve problems?

24. Types of Problems
• Data-Driven Problems
Problems which occur for specific users, scenarios and which
depend on (input) parameters e.g.: a search query
• Load Driven Problems
Problems which depend on the current system load. Usually
occur at higher load. In most cases resource dependent. e.g.:
increased response time with more users.
• Environment Driven Problems
Problems caused by factors outside the application. e.g.:
hardware, network connectivity, etc.

25. Operations Main Tasks
• Monitoring
Collect all relevant KPIs and check against SLAs and
baselines?
• Alerting/Incident Management
Inform ops about problems
• Impact Analysis
Analyze the impact of issues. Who is affected?
• Isolation
What is the cause of a problem and who must I talk to?
• Diagnosis
Why is there a problem and how can we fix it?

26. Key Performance Indicators/Metrics
• Visitors and Requests
How many people are using our site?
• Response Times
How fast do we service requests.?
• Errors and Failed Transactions
How many problems do we see and how often do they affect
functionality?
• Availability
Can our systems currently be reached?
• Utilization Metrics
Do we have enough resources and are we using them
efficiently?

27. … and in the real
world?

28. Large-scale shopping platform

29. Performance Pyramid
Business
Application
Container
System Performance

30. System/Container Performance

31. Technical Response Time View

32. Page Category Performance

33. Performance of Key Transactions

34. Business View wit Performance Data

35. You can do even
more (aka. Goodies)

36. Page Error Tracking

37. Third Party Management

38. Amazon EC2 Cost Monitoring

39. Alois Reitbauer
@AloisReitbauer
http://book.dynatrace.com
http://blog.dynatrace.com

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