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How to measure disk usage to estimate impact for Azure

  • February 8, 2017 at 9:15 am

    #335130

    I'm in the accidental DBA category and often lurk, but rarely post.
    When I have, I've gotten great responses, and thank everyone for their help!

    I've got a datawarehouse style server that has a good number of truncate and reload ETLs into a pair of databases, which is then lightly used for querying over the course of each day.
    We are looking at adding an Azure VM as a disaster recovery option , and it was explained to me that whether it's feasible for a SQL server to move or not really depends on how many gigs of data are moved, say , each day.
    if we hit too much traffic, they suggest using Always On and replicating the data out to azure that way.
    So I'm trying to find out exactly how much data my server is fiddling with daily. I honestly think it's lightly used, except for the truncate and reloads.

    is it enough to just find the table sizes of the tables I know are truncated and reloaded, and add them together? is there a DMV to check, or an extended event to add to try and measure this over time?
    all i seem to find is how large the existing databases are when i google, and not so much any measures of disc IO?

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  • February 8, 2017 at 1:50 pm

    #1927409

    bobbytables - Wednesday, February 8, 2017 9:15 AM

    is it enough to just find the table sizes of the tables I know are truncated and reloaded, and add them together? is there a DMV to check, or an extended event to add to try and measure this over time?
    all i seem to find is how large the existing databases are when i google, and not so much any measures of disc IO?

    One of the ways to get this information from dm_io_virtual_file_stats
    Glenn Berry has a good set of diagnostic queries for different versions of SQL Server and those include a few for disk diagnostics using that DMV. You can find the link to his set of queries here - lots of great scripts in there other than just the ones for IO performance:
    SQL Server Diagnostic Information Queries for January 2017

    Sue

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