9 Responses

  1. Sunny Dua
    Sunny Dua at |

    Appreciate you taking time to write this stuff….

    Reply
  2. Jayadeep Purushotham
    Jayadeep Purushotham at |

    How much of these problems will be solved by all-flash arrays ?

    Reply
  3. VirtualInfra
    VirtualInfra at |

    Hi, Thanks for writing!!!

    Please help me with this

    First statement

    "Having far fewer underlying LUN’s is one of the great benefits of virtualization however, so you want to reduce the number of LUNs to increase manageability, but without sacrificing performance. "

    3rd statement

    "

    Size isn’t everything. But sizing your datastores or virtual machine storage so they are too big can have a big impact on the time it takes to recover a datastore in case of a disaster, and also what type of protection mechanisms you can use to reduce data loss.

    "

    With the first statement to have manageability and performance it’s good to have fewer lun, if we need to have fewer lun then, i need to go for big luns, and again if we have big luns it comes to 3rd statement of considering RTO.. Most sizing is done based on RTO, and always decided to go with smaller once and since the lun size is smaller, definitely the number of luns increase’s. How to accompany this with first statement for performance and manageability.

    So when I have more smaller LUN how to decide the queue depth size.. Basically I have multiple RDMs for MSCS solution, in this case how to make a decision on the queue depth size.

    Reply
  4. vmPete
    vmPete at |

    Great post Michael. Very timely for me as well, as we were scaling up our compute for a very specific use case, and unfortunately the storage had been cut from the budget. I described the results of this at: http://vmpete.com/2013/03/11/vroom-scaling-up-vir… Right now they are paying the price for not investing in the storage.

    Reply
  5. ranjitcool
    ranjitcool at |

    That book is 44$ on Amazon.. expensive 😀

    Reply
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