How To Calculate How Many?
As promised in last week’s SharePoint Blog this week I am going to talk about Capacity Planning and how to calculate the approximate number of Requests Per Second your SharePoint Server will get.
I am going to explain the formula for calculating the Requests Per Seconds which is recommended for SharePoint.
(Number of users x % users active per day) x Number of requests per active user per day x peak factor
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360 000 x working hours per day
But what does it really mean! To help explain the different parts of the complex looking calculation I am going to use two real-life examples that have got me thinking during the last few days.
The first real-life example hit me on Tuesday evening when I was wedged between a smelly armpit of a long-haired youth and a business man with a rather large brief case on the Northern Line travelling back to Euston Station. With my SharePoint hat on I considered if Transport London had used a similar calculation, to the one above, to see if the number of trains could cope with the number of commuters especially at peak times.
Secondly, you might have noticed in the news that many Villa fans are not happy that former Blues manager Alex McLeish (the legend who got the Blues Noses relegated twice) looks set to be named the new manager of the mighty Aston Villa. While many fans protested yesterday I queued up the purchase my season ticket in the Trinity Road for the 31st consecutive year. So as I waited behind the only other person waiting at the Villa Ticket Office I was thinking how the appointment of Mr. McLeish would affect the number of tickets the Villa Ticket Office would have to sell in the new season.
1. Number of Users x % Users Active Per Day
So how does the calculation work? The first part is the number of users multiplied by the % Users Active per day.
Often when trying to calculate worse case scenarios for SharePoint it is best to use 100% for this figure. Also it makes it easier for the less gifted mathematicians.
With the underground the number of users would probably be how many people are usually in London (residents, tourists and workers) times by the percentage Active Users. The Active Users being those able to use the Underground. It is not really the place for very young children and I expect quite scary if you are blind and have a Guide Dog. Apparently around 11 million people are in London on a normal week day. So if 80% of them are capable of using the underground that would be 11000000 x 80 which is 880000000.
Back at Villa Park the calculation would be the number of Villa fans Worldwide times the percentage of active ones. The active ones are those that do attend Villa games. If we say there are one million worldwide Villa fans and maybe 20% of these attend matches then the first part of the calculation would be 1000000 x 20 which is 20000000.
2. Number of Active Requests per Active User per Day
The next part of the calculation is the number of active requests per active user per day. To help us Microsoft produced a common set of figures for users of SharePoint 2010. It describes frequency of use and a requests/second (RPS) to users ratio for each. These user figures are;
- Light user, access every 180 seconds (20/hr)
- Typical user, access every 100 seconds (36/hr)
- Heavy user, access every 60 seconds (60/hr)
- Extreme user, access every 30 seconds (120/hr)
So if you have 100 SharePoint Users and let’s say that 80 of them are ‘Light Users’ and 20 are ‘Extreme Users’ then all we need to know is numbers of hours they work in a day to find the ‘number of active requests per active user per day’.
If the usual working day is 10 hours (well we need to make them work) then the calculation is as follows;
i) Light Users : 80 x 20 x 10 = 16000 (Requests per Day)
[20 is from Microsoft’s set of figures for number of requests per hour for a Light User]
ii) Extreme Users : 20 x 120 x 10 = 24000 (Requests per Day)
We then add the Light Users and Extreme Users together to get the overall total Requests per Day;
iii) 16000 + 24000 = 40000 (Requests per Day)
As we have overall 100 users (simple for Maths again) we divide the total Requests per Day by 100 to get the ‘number of active requests per active user per day’.
iv) 40000 / 100 = 400 (Active Requests per Active User per Day)
Back in the Underground maybe the Tube Bigwigs have their own definitions to help calculate number of travellers a day. Maybe it is similar to the following;
Light User – Use Tube once every 10 days (0.1/days)
Typical User – Use Tube to go to and from work every day (2/days)
Heavy User – Use Tube for several journeys every day (5/days)
Extreme User – Always on the Tube (20/days)
So assuming that the 11000000 people in London are broken down as follows;
6000000 Light Users, 3000000 Typical Users, 1000000 Heavy Users and 1000000 Extreme Users.
Then the number of users per day is;
i) (6000000 x 0.1)+(3000000 x 2)+(100000 x 5) + (1000000 x 20) = 27600000 Journeys Per Day
We can then divide it by the total number of people in London to give the ‘Active Requests per Active User per Day’;
In the claret and blue world it might work as follows;
Light User – A fan who goes a couple of times a season for special occasions (0.01/days)
Typical User – A fair weather fan who goes to the big games (0.05/days)
Heavy User – A real fan who goes to virtually every home game even the one against Wigan (0.8/days)
Extreme User – Goes to every single game even the reserves (0.1/days)
So assuming that the 1000000 Villa fans are broken down as follows;
950000 Light Users, 25000 Typical Users, 15000 Heavy Users and 10000 Extreme Users.
Then the number of users per day is;
i) (950000 x 0.01)+(25000 x 0.05)+(15000 x 0.8) + (1000 x 0.1) = 21725 Tickets Per Day
We can then divide it by the total number of Villa fans to give the ‘Active Requests per Active User per Day’;
ii) 21725 / 1000000 = 0.021725 (Active Requests per Active User per Day). Meaning that the average number of tickets per Villa fan buys per day is about a fiftieth of a ticket. Maybe this example is not going to quite work out.
3. Peak Factor
Peak Factor isn’t an old daytime soap opera but a value between 1 and 4 that indicates how long Peak Times lasts. If it was always Peak Time then the value would be 4, but for SharePoint Capacity Planning I usually use a value of 2.
With the London Underground probably Peak Hours are 8am to 10am and 4pm to 6pm. So as this is only 4 hours of the day we could use a Peak Factor of 2 as well.
Back in Aston the Peak Factor might be influenced by league position or manager. Maybe after the poor season last year and the possible negative feeling towards a new manager we might settle for a Peak Factor of 1.
4. 360,000 x Working Hours Per Day
Nearly there, hope you are following this. We are trying to calculate the Requests per Second (RPS) so we take number of seconds in an hour. From a good clock not the one in my car which keeps gaining one minute every couple of days. There are 3600 seconds in an hour and as we used a percentage in stage 1 we times it by 100 to give 360000 (I sound like Johnny Ball with all this Maths).
Now we just multiply the 360000 by the number of hours in working day. So if SharePoint users work 10 hours then that is 3600000 for the number at the bottom of our big calculation.
It doesn’t matter if it is SharePoint Users, Tube Passengers or Disgruntled Villa Fans we still divide by 3600000.
5. The Final Calculation
Let’s remind ourselves of the calculation we now have all the parts to complete
(Number of users x % users active per day) x Number of requests per active user per day x peak factor
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360 000 x working hours per day
So for SharePoint we used the following information;
a) 100 Users
b) 100% Active
c) 80 Light Users + 20 Extreme Users
d) 10 Hours a day are worked
e) Peak Factor of 2
This gives us :
(10000 x 400 x 2) / (360000 x 10) = 2.22 Requests Per Second
Just for fun let’s look at the Tube and Villa tickets. Don’t forget these are my figures and are totally fictional.
Starting with the Tube we used the following;
a) 11000000 people in London
b) 80% Active Users
c) 6000000 Light Users
d) 3000000 Typical Users
e) 1000000 Heavy Users
f) 1000000 Extreme Users
g) Trains run for 20 hours a day
h) Peak Factor 2
Which gives;
(88000000 x 2.51 x 2) / (360000 x 20) = 61.36 Travels Per Second
No wonder I didn’t get a seat and ended up re-enacting a Right Guard advert.
So to the mighty Aston Villa FC then where we used the following;
a) 1000000 supporters
b) 20% Active
c) 950000 Light Users
d) 25000 Typical Users
e) 15000 Heavy Users
f) 10000 Extreme Users.
g) Ticket Office open 8 hours a day
h) Peak Factor 1
Which gives;
(20000000 x 0.021725 x 1) / (360000 x 8) = 0.15 Tickets sold Per Second
As the Villa start to win next season maybe the Peak Factor will improve and that will dramatically increase the number of tickets sold a second.
Whoever is manager of Aston Villa next season they will be certain of one thing and that is the full support of this SharePoint Blogger.
The SharePoint Consultants at Office Talk are happy to provide Capacity Planning and Load Testing for any SharePoint environment be it 2007 or 2010. Just drop an email to marketing@office-talk.com
1 comment:
Hi Andy,
Thanks for the explanation on the formula...However, I could not follow how exactly Peak Factor is calculated.
Regards,
Krutika
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