I have no frame of reference in terms of what's considered "fast"; I'd always wondered this but have never found a straight answer...
This question is related to
optimization
You can search "slashdot effect analysis" for graphs of what you would see if some aspect of the site suddenly became popular in the news, e.g. this graph on wiki.
Web-applications that survive tend to be the ones which can generate static pages instead of putting every request through a processing language.
There was an excellent video (I think it might have been on ted.com? I think it might have been by flickr web team? Does someone know the link?) with ideas on how to scale websites beyond the single server, e.g. how to allocate connections amongst the mix of read-only and read-write servers to get best effect for various types of users.
Note that hit-rate graphs will be sinusoidal patterns with 'peak hours' maybe 2x or 3x the rate that you get while users are sleeping. (Can be useful when you're scheduling the daily batch-processing stuff to happen on servers)
You can see the effect even on 'international' (multilingual, localised) sites like wikipedia
That is a very open apples-to-oranges type of question.
You are asking 1. the average request load for a production application 2. what is considered fast
These don't neccessarily relate.
Your average # of requests per second is determined by
a. the number of simultaneous users
b. the average number of page requests they make per second
c. the number of additional requests (i.e. ajax calls, etc)
As to what is considered fast.. do you mean how few requests a site can take? Or if a piece of hardware is considered fast if it can process xyz # of requests per second?
personally, I like both analysis done every time....requests/second and average time/request and love seeing the max request time as well on top of that. it is easy to flip if you have 61 requests/second, you can then just flip it to 1000ms / 61 requests.
To answer your question, we have been doing a huge load test ourselves and find it ranges on various amazon hardware we use(best value was the 32 bit medium cpu when it came down to $$ / event / second) and our requests / seconds ranged from 29 requests / second / node up to 150 requests/second/node.
Giving better hardware of course gives better results but not the best ROI. Anyways, this post was great as I was looking for some parallels to see if my numbers where in the ballpark and shared mine as well in case someone else is looking. Mine is purely loaded as high as I can go.
NOTE: thanks to requests/second analysis(not ms/request) we found a major linux issue that we are trying to resolve where linux(we tested a server in C and java) freezes all the calls into socket libraries when under too much load which seems very odd. The full post can be found here actually.... http://ubuntuforums.org/showthread.php?p=11202389
We are still trying to resolve that as it gives us a huge performance boost in that our test goes from 2 minutes 42 seconds to 1 minute 35 seconds when this is fixed so we see a 33% performancce improvement....not to mention, the worse the DoS attack is the longer these pauses are so that all cpus drop to zero and stop processing...in my opinion server processing should continue in the face of a DoS but for some reason, it freezes up every once in a while during the Dos sometimes up to 30 seconds!!!
ADDITION: We found out it was actually a jdk race condition bug....hard to isolate on big clusters but when we ran 1 server 1 data node but 10 of those, we could reproduce it every time then and just looked at the server/datanode it occurred on. Switching the jdk to an earlier release fixed the issue. We were on jdk1.6.0_26 I believe.
When I go to the control panel of my webhost, open up phpMyAdmin, and click on "Show MySQL runtime information", I get:
This MySQL server has been running for 53 days, 15 hours, 28 minutes and 53 seconds. It started up on Oct 24, 2008 at 04:03 AM.
Query statistics: Since its startup, 3,444,378,344 queries have been sent to the server.
Total 3,444 M
per hour 2.68 M
per minute 44.59 k
per second 743.13
That's an average of 743 mySQL queries every single second for the past 53 days!
I don't know about you, but to me that's fast! Very fast!!
Note that hit-rate graphs will be sinusoidal patterns with 'peak hours' maybe 2x or 3x the rate that you get while users are sleeping. (Can be useful when you're scheduling the daily batch-processing stuff to happen on servers)
You can see the effect even on 'international' (multilingual, localised) sites like wikipedia
When I go to the control panel of my webhost, open up phpMyAdmin, and click on "Show MySQL runtime information", I get:
This MySQL server has been running for 53 days, 15 hours, 28 minutes and 53 seconds. It started up on Oct 24, 2008 at 04:03 AM.
Query statistics: Since its startup, 3,444,378,344 queries have been sent to the server.
Total 3,444 M
per hour 2.68 M
per minute 44.59 k
per second 743.13
That's an average of 743 mySQL queries every single second for the past 53 days!
I don't know about you, but to me that's fast! Very fast!!
less than 2 seconds per user usually - ie users that see slower responses than this think the system is slow.
Now you tell me how many users you have connected.
You can search "slashdot effect analysis" for graphs of what you would see if some aspect of the site suddenly became popular in the news, e.g. this graph on wiki.
Web-applications that survive tend to be the ones which can generate static pages instead of putting every request through a processing language.
There was an excellent video (I think it might have been on ted.com? I think it might have been by flickr web team? Does someone know the link?) with ideas on how to scale websites beyond the single server, e.g. how to allocate connections amongst the mix of read-only and read-write servers to get best effect for various types of users.
When I go to the control panel of my webhost, open up phpMyAdmin, and click on "Show MySQL runtime information", I get:
This MySQL server has been running for 53 days, 15 hours, 28 minutes and 53 seconds. It started up on Oct 24, 2008 at 04:03 AM.
Query statistics: Since its startup, 3,444,378,344 queries have been sent to the server.
Total 3,444 M
per hour 2.68 M
per minute 44.59 k
per second 743.13
That's an average of 743 mySQL queries every single second for the past 53 days!
I don't know about you, but to me that's fast! Very fast!!
less than 2 seconds per user usually - ie users that see slower responses than this think the system is slow.
Now you tell me how many users you have connected.
That is a very open apples-to-oranges type of question.
You are asking 1. the average request load for a production application 2. what is considered fast
These don't neccessarily relate.
Your average # of requests per second is determined by
a. the number of simultaneous users
b. the average number of page requests they make per second
c. the number of additional requests (i.e. ajax calls, etc)
As to what is considered fast.. do you mean how few requests a site can take? Or if a piece of hardware is considered fast if it can process xyz # of requests per second?
You can search "slashdot effect analysis" for graphs of what you would see if some aspect of the site suddenly became popular in the news, e.g. this graph on wiki.
Web-applications that survive tend to be the ones which can generate static pages instead of putting every request through a processing language.
There was an excellent video (I think it might have been on ted.com? I think it might have been by flickr web team? Does someone know the link?) with ideas on how to scale websites beyond the single server, e.g. how to allocate connections amongst the mix of read-only and read-write servers to get best effect for various types of users.
less than 2 seconds per user usually - ie users that see slower responses than this think the system is slow.
Now you tell me how many users you have connected.
You can search "slashdot effect analysis" for graphs of what you would see if some aspect of the site suddenly became popular in the news, e.g. this graph on wiki.
Web-applications that survive tend to be the ones which can generate static pages instead of putting every request through a processing language.
There was an excellent video (I think it might have been on ted.com? I think it might have been by flickr web team? Does someone know the link?) with ideas on how to scale websites beyond the single server, e.g. how to allocate connections amongst the mix of read-only and read-write servers to get best effect for various types of users.
less than 2 seconds per user usually - ie users that see slower responses than this think the system is slow.
Now you tell me how many users you have connected.
Not sure anyone is still interested, but this information was posted about Twitter (and here too):
The Stats
- Over 350,000 users. The actual numbers are as always, very super super top secret.
- 600 requests per second.
- Average 200-300 connections per second. Spiking to 800 connections per second.
- MySQL handled 2,400 requests per second.
- 180 Rails instances. Uses Mongrel as the "web" server.
- 1 MySQL Server (one big 8 core box) and 1 slave. Slave is read only for statistics and reporting.
- 30+ processes for handling odd jobs.
- 8 Sun X4100s.
- Process a request in 200 milliseconds in Rails.
- Average time spent in the database is 50-100 milliseconds.
- Over 16 GB of memcached.
That is a very open apples-to-oranges type of question.
You are asking 1. the average request load for a production application 2. what is considered fast
These don't neccessarily relate.
Your average # of requests per second is determined by
a. the number of simultaneous users
b. the average number of page requests they make per second
c. the number of additional requests (i.e. ajax calls, etc)
As to what is considered fast.. do you mean how few requests a site can take? Or if a piece of hardware is considered fast if it can process xyz # of requests per second?
When I go to the control panel of my webhost, open up phpMyAdmin, and click on "Show MySQL runtime information", I get:
This MySQL server has been running for 53 days, 15 hours, 28 minutes and 53 seconds. It started up on Oct 24, 2008 at 04:03 AM.
Query statistics: Since its startup, 3,444,378,344 queries have been sent to the server.
Total 3,444 M
per hour 2.68 M
per minute 44.59 k
per second 743.13
That's an average of 743 mySQL queries every single second for the past 53 days!
I don't know about you, but to me that's fast! Very fast!!
Note that hit-rate graphs will be sinusoidal patterns with 'peak hours' maybe 2x or 3x the rate that you get while users are sleeping. (Can be useful when you're scheduling the daily batch-processing stuff to happen on servers)
You can see the effect even on 'international' (multilingual, localised) sites like wikipedia
personally, I like both analysis done every time....requests/second and average time/request and love seeing the max request time as well on top of that. it is easy to flip if you have 61 requests/second, you can then just flip it to 1000ms / 61 requests.
To answer your question, we have been doing a huge load test ourselves and find it ranges on various amazon hardware we use(best value was the 32 bit medium cpu when it came down to $$ / event / second) and our requests / seconds ranged from 29 requests / second / node up to 150 requests/second/node.
Giving better hardware of course gives better results but not the best ROI. Anyways, this post was great as I was looking for some parallels to see if my numbers where in the ballpark and shared mine as well in case someone else is looking. Mine is purely loaded as high as I can go.
NOTE: thanks to requests/second analysis(not ms/request) we found a major linux issue that we are trying to resolve where linux(we tested a server in C and java) freezes all the calls into socket libraries when under too much load which seems very odd. The full post can be found here actually.... http://ubuntuforums.org/showthread.php?p=11202389
We are still trying to resolve that as it gives us a huge performance boost in that our test goes from 2 minutes 42 seconds to 1 minute 35 seconds when this is fixed so we see a 33% performancce improvement....not to mention, the worse the DoS attack is the longer these pauses are so that all cpus drop to zero and stop processing...in my opinion server processing should continue in the face of a DoS but for some reason, it freezes up every once in a while during the Dos sometimes up to 30 seconds!!!
ADDITION: We found out it was actually a jdk race condition bug....hard to isolate on big clusters but when we ran 1 server 1 data node but 10 of those, we could reproduce it every time then and just looked at the server/datanode it occurred on. Switching the jdk to an earlier release fixed the issue. We were on jdk1.6.0_26 I believe.
Source: Stackoverflow.com
