Real Life Java EE Performance Tuning
Download as PPT, PDF6 likes3,481 views
The document discusses several case studies of performance issues with Java EE applications and provides solutions. It emphasizes the importance of understanding the entire system, including infrastructure components, and using tools like monitoring, thread dumps, and logging to observe problems before hypothesizing and testing solutions. The first case study found a server with debug logging enabled slowing it down. The second was due to firewalls terminating idle database connections. The third involved inefficient AJAX and an underpowered load tester.
![Real Life Java EE Performance Tuning Matt Brasier Principal Consultant C2B2 Consulting LTD [email_address]](https://image.slidesharecdn.com/reallifeperformancetssjseuropepresentation-110715110642-phpapp02/85/Real-Life-Java-EE-Performance-Tuning-1-320.jpg)
Real Life Java EE Performance Tuning
- 1. Real Life Java EE Performance Tuning Matt Brasier Principal Consultant C2B2 Consulting LTD [email_address]
- 2. About Me Professional Services Consultant Customers include Red Hat (JBoss) BEA Cape Clear Government/Finance/Telecoms C2B2 Consulting SOA and Java EE consultancy Fast, Reliable, Manageable, Secure
- 3. What we will cover Philosophy How I approach a performance problem situation Enterprise Java Performance What kind of things affect performance of Enterprise Systems Case Study 1 A new version of the application runs slowly Case Study 2 Logging in takes a long time in the live environment Case Study 3 The application does not scale
- 4. What we will learn Philosophy Suggestions to keep in mind when looking at a performance problem Tools Suggested tools for looking at a performance problem Techniques How to use the tools, knowledge and skills to solve your performance problem
- 5. Philosophy ‘ A good understanding’ is the best performance tuning tool Prefer common and open source tools Observe, Hypothesize, Tweak, Test ‘ Trust no-one’
- 6. Classic Java performance problems Memory leaks Increased GC Time Poor GC or JVM Memory configuration CPU bound code IO bound code Memory bound code Increased GC time
- 7. Enterprise Java Performance CAVEAT: Consultancy Selection Bias 80/20: 80% of time finding, 20% fixing Many ‘Enterprise’ Java performance problems turn out not to be ‘classic’ performance bottlenecks Infrastructure/Middleware performance There are many factors that can affect the performance of an enterprise system Not just code
- 8. Enterprise Java Performance Not all Java EE performance problems are classical ‘Java performance problems’ Common types of Java EE performance problem Resource starvation Threading problems ‘ Suboptimal configuration’ Network related problems Scalability problems
- 9. A Good Understanding Consider the system as a whole Know how infrastructure components work Not just what they do, but how they do it How do the Java EE specifications say they should work?
- 10. Approach Understand the system Understand the environment Understand the situation Talk to people who know But trust no-one Take a look for myself Observe, Hypothesize, Tweak, Test Rinse and repeat
- 11. Case Study 1
- 12. Case Study 1 Existing customer calls “ We deployed a new version of the application, and it is running a lot slower” The Environment Sun Java 5 WebLogic Server 9.2 Cluster (3 nodes) WebLogic Integration 9.2 Cluster (3 nodes) Documentum Document Management Oracle Database Solaris OS
- 13. Case Study 1 The System Web Application WLI based workflow system The situation New version deployed into the performance testing environment Automated performance tests indicate the application is approximately 30% slower
- 14. Case Study 1 Observe No monitoring in place Some alerting, but no historical data Hypothesize If we had more monitoring, we would stand a better chance Tweak Put some monitoring in place Hyperic HQ from SpringSource
- 15. Case Study 1 Test Re-run tests Observe Monitoring indicates that one server is slower Handling less requests per second Lots of transaction timeouts Higher CPU Less network traffic Tweak Add more monitoring to the slow server Examine log files Thread dumps!
- 16. Case Study 1 Hypothesize Thread dumps show lots of threads in logging code waiting to write to the log file Log files for the slow server have DEBUG messages in them The other servers don’t “ The logging configurations are identical, the servers are configured with Maven” Trust no one Test Log in to the server and manually check the logging configuration
- 17. Case Study 1 Solution Debug logging was enabled on one server Turned debug logging off - the system was then about the same speed as the old release
- 18. Hyperic HQ
- 19. Hyperic HQ Monitoring tool Not a profiling tool Historical data Trends Abnormal behaviour ‘ Hot’ spots Wide variety of data JVM level statistics JMX statistics OS statistics
- 20. Thread Dumps My Number 2 tool for finding performance problems CTRL-BREAK in windows Kill -3 on Unix/Linux Jstack tool Available from consoles of many application servers All threads in the VM and what they are doing at that moment
- 21. Thread Dumps A number of thread dumps over time gives a good picture Any operation that appears a lot is a suspect Understand what ‘normal’ thread dumps look like http://java.sun.com/developer/technicalArticles/Programming/Stacktrace/
- 22. Thread Dump
- 23. Thread Dumps Look near the top of each stack Look for stacks with your code in them Look for long stacks Look for deadlocks and other threading issues
- 24. The Understanding What does a normal WebLogic thread dump look like? It is not normal to see logging code frequently in a thread dump Lots of threads all waiting on a single lock object is a Bad Thing™ If three servers are supposed to do the same thing, their thread dumps should look similar Over time
- 25. Lessons Thread dumps hold a lot of information Infrastructure configuration faults are more common than infrastructure bugs Automated/continuous build and deploy solutions are no silver bullet Check the results yourself Believe your ‘instincts’
- 26. Case Study 2
- 27. Case Study 2 Customer Call “ We deployed our application into the live environment and it takes several minutes for users to log in” Environment Apache web servers WebLogic Portal 8.1 Cluster (2 nodes) Oracle Database Windows Server 2003 Bespoke Single Sign On server
- 28. Case Study 2 The System Web application based on WSRP portlets Oracle database storing user data The Situtation The first users to log-in in the morning find that it takes several minutes After the first few log-ins, the application runs fine
- 29. Case Study 2 Hypothesize The bespoke Single Sign On server makes me suspicious Bespoke code is tested less Test Turn on debug logging for the SSO implementation Observe timings of log messages
- 30. Case Study 2 Observe The logs indicate that the SSO log-in is proceeding as expected It appears that loading the users profile data from the database is taking a long time Hypothesize TCP timeouts when connecting to the database due to a firewall
- 31. Case Study 2 Test Observe the connection pool statistics in the WebLogic console The console indicates that a large number of connections have been opened during the time the application has been running Connections are not normally closed and re-opened See how long you need to leave the system before the problem occurs
- 32. Case Study 2 Solution Discussions with the networking team indicated that there was a firewall, configured to silently terminate network connections that were Idle for 60 minutes Set WebLogic to test connections after they have been idle for 50 minutes.
- 33. Lessons Consider the system as a whole Hardware Networking OS Middleware Application
- 34. The Understanding Firewalls are often configured to silently terminate idle TCP connections The TCP protocol requires that a connection is closed by both sides, or times out The time out is several minutes In a healthy WebLogic connection pool, the number of connections opened since the server started = the maximum number in the pool
- 35. Case Study 3
- 36. Case Study 3 Customer call “ It takes about 20 seconds to render a page, and the performance does not scale” Environment WebLogic Portal 9.1 Cluster (2 nodes) Oracle 10g Database Red Hat Enterprise Linux
- 37. Case Study 3 The System Online content delivery system WebLogic Portal with a commercial set of portlets The Situation Two problems Running the performance tests with 20 threads in JMeter is twice as slow as running the tests with 10 threads Viewing a content item takes around 20 seconds
- 38. Case Study 3 Handle the two problems separately They may be related, they may not be
- 39. Case Study 3 Observe Viewing a content item takes around 16 seconds on my laptop Test Is the rendering speed dependent on the browser used? Is the rendering speed dependent on the client machine? What does the page source look like?
- 40. Case Study 3 Observe In Opera the page renders quickly except for the table of contents on the left In Firefox, the whole page renders at the same time The page renders faster in IE and Opera than firefox The page renders faster on faster machines There is a lot of Javascript, and AJAX is used to load the table of contents
- 41. Case Study 3 Hypothesize The AJAX rendering of the TOC is taking a long time, and slowing down the whole page load Tweak Remove the TOC from the page Disable JavaScript in the browser Test The page renders in less than 2 seconds
- 42. Case Study 3 Hypothesize JMeter does not execute the javascript, so the poor performance of JMeter is not related to the poor page load speed
- 43. Case Study 3 Solution 1 The portlet developers have used AJAX to render the table of contents for a content item, this is much slower than just constructing the table of contents on the server side Rewrite the portlet to construct the table of contents on the server side Developers sometimes select a technology to enhance their CVs, not to implement a business requirement
- 44. Case Study 3 Problem 2 – Scalability Observe Running the tests on JMeter with 10 users, each page response takes 5s Running the test with 20 users each page response takes 12s JMeter is being run on an old laptop, which is at 100% CPU in both cases
- 45. Case Study 3 Hypothesize As the test machine is at 100% CPU, it is the performance of JMeter that is being measured, not the performance of WebLogic Observe WebLogic is running at around 2% CPU usage, with many idle threads
- 46. Case Study 3 Tweak Run the test from a number of more modern machines, and make sure each one does not exceed 70% CPU Observe Four machines can each run 20 threads and get responses in 1.5 seconds, and WebLogic is still running at around 5% CPU and not struggling
- 47. Case Study 3 Solution The problem was that the test client was not able to generate the loads requested, resulting in the performance of the test client being measured Use a larger test client
- 48. Useful tools Ethereal/Wireshark Network traffic sniffer See when requests/responses were sent/received Firebug + YSlow Firefox plugin for performance analysis
- 49. Lessons Separate problems should initially be prioritised and investigated separately Keep in mind that they may be related Ensure the test system can generate the required load It should have plenty of free resources available
- 50. Lessons The consultant effect Take a step back Get a fresh perspective
- 51. The Understanding A slow test client will give slow results Client side rendering is usually less efficient than server side WebLogic is normally fast!
- 52. What did we learn? Simple tools can provide a lot of information Understanding how the system should behave will help highlight possible causes Experience is vital Write a log of what you find Take a step back from the problem Use a second pair of eyes
- 53. What did we learn? Philosophy Understand they system as a whole A deep understanding of how it should work Tools Thread dumps Monitoring tools Packet sniffing Techniques Observe, Hypothesize, Tweak, Test
- 54. Questions
- 55. Session Evaluation Please complete a session evaluation and turn it into any conference staff member or at the registration desk. Thank you.