Goal Driven Performance Optimization, Peter Zaitsev
-
Upload
fuenteovejuna -
Category
Technology
-
view
1.093 -
download
2
description
Transcript of Goal Driven Performance Optimization, Peter Zaitsev
![Page 1: Goal Driven Performance Optimization, Peter Zaitsev](https://reader034.fdocuments.in/reader034/viewer/2022051817/547c1ad8b37959822b8b4e96/html5/thumbnails/1.jpg)
Goal Driven Performance Optimization
Highload++,October 25-26,2010Moscow, RussiaPeter ZaitsevPercona Inc
![Page 2: Goal Driven Performance Optimization, Peter Zaitsev](https://reader034.fdocuments.in/reader034/viewer/2022051817/547c1ad8b37959822b8b4e96/html5/thumbnails/2.jpg)
Goal Driven Performance Optimization
What is this all about ?
• First step to successful performance optimization is setting right goals
• In most cases goals are not set (or unclear) and a lot of resources wasted on not important things
• This presentation is about setting the right goals and using them to optimize performance of existing system
![Page 3: Goal Driven Performance Optimization, Peter Zaitsev](https://reader034.fdocuments.in/reader034/viewer/2022051817/547c1ad8b37959822b8b4e96/html5/thumbnails/3.jpg)
Goal Driven Performance Optimization
When is it Applicable ?• Optimizing Performance for Existing Applications• Can be used with load testing for scaling application
and testing new features• A way to implement monitoring and spot problems
before users start complain
![Page 4: Goal Driven Performance Optimization, Peter Zaitsev](https://reader034.fdocuments.in/reader034/viewer/2022051817/547c1ad8b37959822b8b4e96/html5/thumbnails/4.jpg)
Goal Driven Performance Optimization
Understanding Performance
• Latency/Response Time– Always Important– Tolerance can be very different
• 50ms of Ajax Request• 30minutes for report
• Throughtput– Often important for multi-user systems– System can do 1000 transactions/second
![Page 5: Goal Driven Performance Optimization, Peter Zaitsev](https://reader034.fdocuments.in/reader034/viewer/2022051817/547c1ad8b37959822b8b4e96/html5/thumbnails/5.jpg)
Goal Driven Performance Optimization
Throughput/Latency Relation
• Response time tends to increase with throughput– When system overload response time goes to infinity
• Call Center analogy– Fewer people servicing calls = better utilization
• Same as throughput per person– More people servicing calls = better response time
• Calls spend less time waiting in the queue
• Classical Performance Optimization Goal– Maximizing Throughput/Utilization while maintaining
Response time within a guidelines
![Page 6: Goal Driven Performance Optimization, Peter Zaitsev](https://reader034.fdocuments.in/reader034/viewer/2022051817/547c1ad8b37959822b8b4e96/html5/thumbnails/6.jpg)
Goal Driven Performance Optimization
Response Time Metrics
• Average/Medium/Response Time– Not a good metric for adequate performance– Same as average person temperature in hospital– Can be helpful for historical trending
• Maximum Response Time– Good in theory. We want No requests taking longer than X– Hard to work in practice – some requests will take too long
• Define Percentile response time– 95% or requests serviced within 500ms – 99% or requests serviced within 1000ms
![Page 7: Goal Driven Performance Optimization, Peter Zaitsev](https://reader034.fdocuments.in/reader034/viewer/2022051817/547c1ad8b37959822b8b4e96/html5/thumbnails/7.jpg)
Goal Driven Performance Optimization
Alternative Measurments
• 95 percentille response time is hard/expensive to compute in SQL– Can use other metrics
• APDEX– http://en.wikipedia.org/wiki/Apdex
• Portion where response time is within response time– SUM(response_time<0.5)/count(*) – Returning 0.95 Is same as 95% response time of 0.5 sec
![Page 8: Goal Driven Performance Optimization, Peter Zaitsev](https://reader034.fdocuments.in/reader034/viewer/2022051817/547c1ad8b37959822b8b4e96/html5/thumbnails/8.jpg)
Goal Driven Performance Optimization
Even Response Time
• 95% response time goal will allow your system to be non responsive for an hour every day– Ie extremely bad performance when taking backup
• You want to ensure there is no stalls/performance dips.
• If page loads slow and user presses reload and it loads quickly it is OK – there are always network glitches.
• Define your performance goals at short intervals. – Goals should be met at ALL 5 minutes intervals.
![Page 9: Goal Driven Performance Optimization, Peter Zaitsev](https://reader034.fdocuments.in/reader034/viewer/2022051817/547c1ad8b37959822b8b4e96/html5/thumbnails/9.jpg)
Goal Driven Performance Optimization
Even Response Time math
• If you only can work with long intervals you can define stricter performance goals – 99.9% metrics means 2 min slow response will affect it
• 86400/1000~=86 (sec) – assuming uniform traffic
• The longer response time is OK the larger intervals you can have – 1min allowed response time in 99% cases means 1 hour
check interval should be enough
![Page 10: Goal Driven Performance Optimization, Peter Zaitsev](https://reader034.fdocuments.in/reader034/viewer/2022051817/547c1ad8b37959822b8b4e96/html5/thumbnails/10.jpg)
Goal Driven Performance Optimization
Response Time and an Object
• Not all the pages are created Equal• Complexity and User Requirement Differ• Ajax Pop Ups
– 50ms• Profile Page Generation
– 150ms• Search
– 300ms• Site Usage Report
– 1000ms
![Page 11: Goal Driven Performance Optimization, Peter Zaitsev](https://reader034.fdocuments.in/reader034/viewer/2022051817/547c1ad8b37959822b8b4e96/html5/thumbnails/11.jpg)
Goal Driven Performance Optimization
Responses by Type of Client
• Human Being– Actual Human waiting and being impatient– Response Time critical
• Bots– Some systems have over 80% of bot traffic– Bot response time is less critical
• Though should be good enough to be indexed
• Interactive Web Services– Can be used to generate pages on other sites– Low Response time is even more critical
![Page 12: Goal Driven Performance Optimization, Peter Zaitsev](https://reader034.fdocuments.in/reader034/viewer/2022051817/547c1ad8b37959822b8b4e96/html5/thumbnails/12.jpg)
Goal Driven Performance Optimization
Different kinds of Slowness
• System “randomly” responds slowly– OK as long as rare enough. – Users will write it off as Internet/computer slowness
• Sustained Slowness is bad– Search request which is always slow– User with many friends which is “always” slow
• Are these users/cases important ?– Track them separately. They may be invisible with 99%
alone. ie Performance per customer – Consider Firing users/Blocking cases otherwise
![Page 13: Goal Driven Performance Optimization, Peter Zaitsev](https://reader034.fdocuments.in/reader034/viewer/2022051817/547c1ad8b37959822b8b4e96/html5/thumbnails/13.jpg)
Goal Driven Performance Optimization
Where to measure performance
• Client Side (the actual data)– http://code.google.com/p/jiffy-web/– Firebug etc (but only for development)
• External Performance Monitoring– Gomez, Keynote etc– Selected pages from selected locations
• Web Server Performance Analyses– Focused on one dynamil request response time– http://code.google.com/p/instrumentation-for-php/– Mk-query-digest; tcprstat
![Page 14: Goal Driven Performance Optimization, Peter Zaitsev](https://reader034.fdocuments.in/reader034/viewer/2022051817/547c1ad8b37959822b8b4e96/html5/thumbnails/14.jpg)
Goal Driven Performance Optimization
Summary of the Goal
• Define 95%, 99% etc response time• For each User Interaction/Class, each application
instance/user• Measured/Monitored each 5 minutes• From Front End and Backend observation• Avoiding Performance Holes
– Some actions or users which are rare but often slow
![Page 15: Goal Driven Performance Optimization, Peter Zaitsev](https://reader034.fdocuments.in/reader034/viewer/2022051817/547c1ad8b37959822b8b4e96/html5/thumbnails/15.jpg)
Goal Driven Performance Optimization
Performance Black Swans
• Queries can be intrinsically slow or caused to be slow by side load (queueing)
• You can ignore outliers only if their impact to system performance is limited.
• Discover Such Queries– Mk-query-digest will report outliers by default– Check SHOW PROCESSLIST for never completing
queries– Optimize; Build protection to kill overly slow queries.
![Page 16: Goal Driven Performance Optimization, Peter Zaitsev](https://reader034.fdocuments.in/reader034/viewer/2022051817/547c1ad8b37959822b8b4e96/html5/thumbnails/16.jpg)
Goal Driven Performance Optimization
Production Instrumentation
• Many People Instrument Test System– Option to print out Queries/Web Service Requests– Great for Debugging/Testing– Will not show a lot of performance problems
• Cold vs hot requests• Contention happening in production• Special User Cases
• Run Instrumented App in Production and Store Data– Can instrument only one of Web servers if overhead is
large.– Can log only 1% of user sessions if can't handle all data
![Page 17: Goal Driven Performance Optimization, Peter Zaitsev](https://reader034.fdocuments.in/reader034/viewer/2022051817/547c1ad8b37959822b8b4e96/html5/thumbnails/17.jpg)
Goal Driven Performance Optimization
What to Instrument
• Total Response Time• CPU Time• “Wait Time”
– Connections/Database Queries– MemCache– Web Services Request– Other Network Requests
• Additional Information– Number and Nature of different queries– Hits/Misses for Queries– Options which can affect performance
![Page 18: Goal Driven Performance Optimization, Peter Zaitsev](https://reader034.fdocuments.in/reader034/viewer/2022051817/547c1ad8b37959822b8b4e96/html5/thumbnails/18.jpg)
Goal Driven Performance Optimization
Where to Store
• Plain old log files– Or directly to the database for smaller systems
• Load them to the database• Or Hadoop on the larger scale• Generate standard reports • Provide Ad-Hoc way to do deep data analyses
![Page 19: Goal Driven Performance Optimization, Peter Zaitsev](https://reader034.fdocuments.in/reader034/viewer/2022051817/547c1ad8b37959822b8b4e96/html5/thumbnails/19.jpg)
Goal Driven Performance Optimization
Start from what is most important
• Optimize Most important User Interactions first• Pick What case to focus in
– Queries which do not meet response time– But not Worse Case Scenario
• Unless outliers kill your system• There are always going to be outliers
• Do not analyze just queries above response time threshold– It is much easier to reach 95% of 1 second if 50% of the
queries are below 500ms.
![Page 20: Goal Driven Performance Optimization, Peter Zaitsev](https://reader034.fdocuments.in/reader034/viewer/2022051817/547c1ad8b37959822b8b4e96/html5/thumbnails/20.jpg)
Goal Driven Performance Optimization
Benefits of Such Approach
• Direct connection to the business goals• High Priority problems targeted first• Focus on real stuff
– No guess work like “is my buffer pool hit ratio bad?” or “am I doing too much full table scans ?”
– If these there the issues you will find and fix them anyway.• Understandable and predictable result
– If MySQL contributes 15% to the response time I can't possibly double performance focusing on MySQL optimization.
![Page 21: Goal Driven Performance Optimization, Peter Zaitsev](https://reader034.fdocuments.in/reader034/viewer/2022051817/547c1ad8b37959822b8b4e96/html5/thumbnails/21.jpg)
Goal Driven Performance Optimization
Final Notes
• Spikes; Special Cases should not be discarded– They are the most interesting/challenging are
• Understand what you're trying to achieve– The method is best for optimization of current scale for
system already in production.• Check out goal driven performance optimization
whitepaper– http://www.percona.com/files/white-papers/goal-driven-
performance-optimization.pdf
![Page 22: Goal Driven Performance Optimization, Peter Zaitsev](https://reader034.fdocuments.in/reader034/viewer/2022051817/547c1ad8b37959822b8b4e96/html5/thumbnails/22.jpg)
Goal Driven Performance Optimization
Thanks for Coming
• Questions ? Followup ?– [email protected]
• Yes, we do MySQL and Web Scaling Consulting– http://www.percona.com
• Check out our book– Complete rewrite of 1st edition– Available in Russian Too
• And Yes we're hiring– http://www.percona.com/contact/careers/
-22-