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.

Often it is easier to quickly grab its statistics dump and analyze it in few seconds, instead of collecting and consolidating data from all those servers?

Pytrend is a portable tool developed by me for quick workload analysis on various old storage arrays (non-EMC), for which I have no other means for doing quick historic performance reports.The basic idea is to quickly get overall storage system workload dynamic, without going too deep into components (LUNs, Disks, ports).

Pytrend is written on Python 3, which is absolutely amazing for dealing with heterogeneous data structures. The list of currently supported storage arrays is: IBM (SVC, Storwize and DS-series midrange), NetApp FAS (pre 8.3), and HPE 3PAR. I use plotly to draw the graphs.

I did not consider processing Dell EMC storage files, because we have plenty of tools for analyzing our arrays. For example, LiveOptics supports VNX and VMAX analysis.

But my aim is to teach Pytrend to aggregate workloads of heterogeneous arrays and build consolidated performances graphs, until such a time as our tools allow us to automate this analysis. Of course as Live Optics is enhanced, my script may become redundant sooner rather than later, but as an interim way to get array statistic overview quickly, this can help.

In this demo I want to show you how quick and effective Pytrend is for analyzing IBM DS-series stats dump.

If you would like to discuss how to analyse storage performance data, of course contact me at denis.serov@dell.com

 

 

P.S. Mitrend is nice too. You can create your Mitrend account for only 250 USD per month now.

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