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Move to a New Server [message #1536] Tue, 31 October 2006 15:38
lleachii
Messages: 13
Registered: August 2006
Junior Member
Hello,

The hardware in my old server is dying and I need to move NST to a new server, what files do I need to save in order to keep my current configurations?

Thanks
Re: Move to a New Server [message #1537 is a reply to message #1536] Thu, 02 November 2006 15:25 Go to previous message
support
Messages: 919
Registered: April 2004
Senior Member
> The hardware in my old server is dying and I need to move NST
> to a new server, what files do I need to save in order to keep
> my current configurations?

You should backup
- the nospamtoday.cf file,
- the local.cf file in the sa\ruleset subdirectory (and any other rules files you changed or added manually)
- the complete db subdirectory (if you want to keep your Bayesian database).

Remember to change the Incoming and Outgoing IP addresses and ports in the nospamtoday.cf file accordingly before starting the NoSpamToday! service on the new machine.



Customer Support
Byteplant GmbH
Re: Move to a New Server [message #1538 is a reply to message #1537] Sat, 04 November 2006 14:59 Go to previous message
mafoo
Messages: 1
Registered: November 2006
Junior Member
Sorry to hijack the topic but it is along the same lines. Are these the files I should include in my daily backup? What is the bayesian database file and what are the advantages/disadvantages if I don't back it up.

Cheers Very Happy



Re: Move to a New Server [message #1539 is a reply to message #1538] Tue, 07 November 2006 15:19 Go to previous message
support
Messages: 919
Registered: April 2004
Senior Member
> Sorry to hijack the topic but it is along the same lines. Are
> these the files I should include in my daily backup? What is
> the bayesian database file and what are the
> advantages/disadvantages if I don't back it up.

Yes, it is a good idea to backup these files.
The Bayesian database stores information for the probability analysis of emails.
You can restart with an empty database at any time, but this means you'll loose
all information the Bayesian learner has accumulated so far.



Customer Support
Byteplant GmbH
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