Pytrend. Quick demo of HPE 3PAR stats processing, time cuts and latency as a function of IOPS

In this short demo I am showing you that Pytrend now can process HPE 3PAR stats dumps and build various system level graphs, such as:

  1. IOPS over time (read/write/total)
  2. MB/sec over time (read/write/total)
  3. Latency over time (read/write/average)
  4. IO Size over time (read/write/average)
  5. CPU Utilization over time (system/user)

All above stats are directly parsed from dump into the graphs.

Though, there is another one, which I’ve added myself, because it is very useful to see how latency depends on IOPS, to see whether system resources (disks or controllers)are close to saturation.

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Pytrend Enhancement. Quick demo for IBM DS3000 and DS5000 series

In this little demo I show you two improvements for storage stats processing.

One of them is small enhancement of IBM DS3000/DS5000 series statistics. Originally, DS-series do not provide average IO Size in their service dump, so I have taught Pytrend to recognize bandwidth (KB/sec or MB/sec) and IOPS data to correctly calculate average IO size.

Another small enhancement for graphs now shows Average and 95-percentile for each plotted value. It is required in most situation for determining correct workload profile. This feature is available for all storage types.

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Pytrend — quick 3rd party storage array workload analysis. IBM DS5300 demo.

This is aimed at partners and Dell people…..

I’m often asked to analyse the performance of 3rd party arrays before I build a solution. We have many tools to analyse behavior, but sometimes you have to analyse the raw data from the 3rd party array, rather than use host-based tools, especially if there are hundreds of servers connected to the same array.

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