Today we continue discussing the best practice from storage engineering:


528) Live updates versus backup traffic, for instance, qualify for separate products. Aging and tiering of data also qualify for separate storage. Data for reporting can similarly be separated into its own stack. Generated data that drains into logs can similarly feed diagnostic stacks.

529) The number of processors or resources assigned to a specific stack is generally earmarked with T-shirt sizing.  This is helpful for cases where the increment or decrement of resources doesn’t have to be done by a notch by notch level.

530) Public cloud and hybrid cloud storage discussions are elaborated on many forums. The hybrid storage provider is focused on letting the public cloud appear as front-end to harness the traffic from the users while allowing storage best practice for the on-premise data.

531) Data can be pushed or pulled from source to destination. If it’s possible to pull, it helps in relieving the workload to another process.

532) Lower level data transfers are favored over higher level data transfers involving say HTTP.

533) The smaller the data transfers the larger the number which results in more chatty and potentially fault prone traffic.  We are talking about very small  amount of data per request.

534) The larger size  reads and writes are best served by multiple parts as opposed to long running requests with frequent restarts

535) The up and down traversal of the layers of the stack are expensive operations. These need to be curtailed.

        static int GetNChooseKDP(int n, int k)
        {
            if ( n == 0 || k > n)
                return 0;
            if (k == 0 || k == n)
                return 1;
            return GetNChooseKDP(n - 1, k - 1) + GetNChooseKDP(n - 1, k);
        }