The old work-horses of IT, mainframes, are still there and
we are still highly dependent on them. Although they run based on a code
written in an age-old language called COBOL, even today, the heavy number
crunching tasks they undertake and volumes they deliver are terrific! As part
of this process, they spew lot of data which tells a lot about their own system’s
performance, condition, etc. Now, the million dollar question is why not we use
this data to improve the performance of our old-age machines and make them run faster?
What helps us to do this?
The answer lies in analytics. Gather and channel data thrown
by mainframes in to a proper analytics application. Hurray! You could see you
old-number cruncher talking to you through graphs, charts, etc. The analytics application
dashboard displays all the data thrown by your mainframe in an easily
understandable format after applying all the pre-defined rules, models, etc.
Remember: the technology has moved from ‘management by
observation’ to ‘management by automation’ via ‘management by exception’.
As part of the automation, you can even set thresholds and alerts
based on these thresholds. Since thresholds change based on workloads, peak
hours, etc., you need to set different thresholds when it comes to mainframe
environment to help it alert you correctly based on a given scenario. You have
to set ‘new normal’ for all kinds of scenarios that your mainframe experiences
during its working period. Considering this new normal as the baseline, the
system alerts you when there are any deviations.
In summary, linking analytics to mainframes’ performance
helps you to reap rich benefits.
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