"Create Time Cluster Template for associate algorithm"
Hello Together,
it is easier if I first explain what I have. Here we go:
In my company there is an little Server farm with 5 Servers.
On the Servers is running one big CRM System.
Also there is a Monitoring System to check the availability of the servers.
If an error occurs the monitoring system recognize it, create a message for the support team and store the failure in a db2 datawarehouse.
Also the Monitoring Systems stores the status for many components like CPU_Usage, Memory_Usage,... for every Server every 15Minutes.
The idea is now to do analytical tasks on the datawarehouse. I want to see if there is a dependency beetwen a failure that occure on one server and the cpu usage on another one.
The Vision is to get a rule like this: "If it is Monday at 8:15 and Server1 CPU_Usage>85% and Server2 CPU_Usage>91% then exists a plausibility of 77% that failureX will occure"
In the first step i want to create an Time Cluster Template like shown:
[img=http://img13.imageshack.us/img13/3774/templateg.th.jpg]
So I can save the count of failure in that scheme, and i can save the mean values of the CPU_Usage for every Server in that scheme.
If i have these tables i can take a look at a failure timestamp, check the CPU_Usage at this moment with the "normal CPU_Usage" and decide if it is in a normal area or not. (for every Server). In the final i want to have a table, where the failure timestamp is stored an "y" if a CPU_Usage of a server is in abnormal area and a "n" if it is normal value. On this table i want to use a association algorithm, to get a rule like descibed above.
Here I want to discribe my proceeding (Red "V" are variables):
[img=http://img26.imageshack.us/img26/8751/modellc.th.jpg]
My Question is if i have to write an tool to do the extraction in the timeslots or is there a easier way to get what i want.
Thanks for all your help
Chris
P.S.
I know that this analytic is not very interessting, because a failur in a sever farm have many causes. But its just a first experiment for me to get into dataming.
it is easier if I first explain what I have. Here we go:
In my company there is an little Server farm with 5 Servers.
On the Servers is running one big CRM System.
Also there is a Monitoring System to check the availability of the servers.
If an error occurs the monitoring system recognize it, create a message for the support team and store the failure in a db2 datawarehouse.
Also the Monitoring Systems stores the status for many components like CPU_Usage, Memory_Usage,... for every Server every 15Minutes.
The idea is now to do analytical tasks on the datawarehouse. I want to see if there is a dependency beetwen a failure that occure on one server and the cpu usage on another one.
The Vision is to get a rule like this: "If it is Monday at 8:15 and Server1 CPU_Usage>85% and Server2 CPU_Usage>91% then exists a plausibility of 77% that failureX will occure"
In the first step i want to create an Time Cluster Template like shown:
[img=http://img13.imageshack.us/img13/3774/templateg.th.jpg]
So I can save the count of failure in that scheme, and i can save the mean values of the CPU_Usage for every Server in that scheme.
If i have these tables i can take a look at a failure timestamp, check the CPU_Usage at this moment with the "normal CPU_Usage" and decide if it is in a normal area or not. (for every Server). In the final i want to have a table, where the failure timestamp is stored an "y" if a CPU_Usage of a server is in abnormal area and a "n" if it is normal value. On this table i want to use a association algorithm, to get a rule like descibed above.
Here I want to discribe my proceeding (Red "V" are variables):
[img=http://img26.imageshack.us/img26/8751/modellc.th.jpg]
My Question is if i have to write an tool to do the extraction in the timeslots or is there a easier way to get what i want.
Thanks for all your help
Chris
P.S.
I know that this analytic is not very interessting, because a failur in a sever farm have many causes. But its just a first experiment for me to get into dataming.