George -
This is why I hate statistics.  You can make them say anything.
Wouldn't the better calculation be based on the average number of currently 
active sessions at one data center, since when it goes down, that is the number 
of users which will be affected.
The calculation should also include probability and length of outage and then 
weighed against the downside of the end user gettng an error message and having 
to login again and start over.
I'd really only see it as being a problem if there were extremely long-running 
transactions that would have to be restarted in the event of an outage (or a 
really poorly designed app).
Jeff
p.s. I'm with you on this probably being a minor concern causing a larger 
headache, but we should get the scope of the problem correct to begin with. 
(said by one who both supports and uses webapps that support large numbers of 
users)

-----Original Message-----
From: George Sexton [mailto:geor...@mhsoftware.com] 
Sent: Wednesday, August 26, 2009 9:52 AM
To: 'Tomcat Users List'
Subject: RE: Multiple data centers and redundency?

> -----Original Message-----
> From: Andre-John Mas [mailto:aj...@sympatico.ca]
> Sent: Tuesday, August 25, 2009 6:30 PM
> To: Tomcat Users List
> Subject: Multiple data centers and redundency?
> 
> Hi,
> 
> I have been asked to look into a solution that would involve a few
> different data centres each with their own set of load balanced Tomcat
> servers. The requirement is for the users not to lose their session if
> one data center goes down. I have never had to work on something this
> large and have no idea to what extent this can be achieved with Tomcat.
> 
> My initial thoughts would be for each data center to have a session
> pool, which is synced with each other, so if ever a Tomcat server or
> data center goes down they can check in the pool to see if it exists
> and then reuse that. It would mean extra communication behind the
> scene, but I see no other way go about it.
> 
> Any help would be appreciated.
> 
> André-John

Has anyone really done any math to determine the risk?

Here an example of what I mean.

Say you are in a high quality co-location. The probability of an outage is
maybe once in 3 years. That's overstating the probability in my mind, but
we'll use it. Let's also say that you have a high quality clustering
solution in place in each data center that handles failover of any equipment
WITHIN the data center.

Say the average length of a user/customer session is 2 hours, and your
failover system will route any new users to a remaining data center. I think
2 hours is kind of a long session but we'll use it. Say you have two data
centers.
 
So, the probability of an average customer being affected by a data center
outage is:

1/( (2 hours)/24(Hours day) * 1/(3*365))/2 (Data centers)

The probability of an average customer being affected by an outage is
conservatively 1 in 26280. Expressed as a percentage, the probability of any
individual session being affected is 0.0038%.

Is your application really so big and critical that you have to address this
very small percentage chance of a session being interrupted?


George Sexton
MH Software, Inc.
http://www.mhsoftware.com/
Voice: 303 438 9585


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