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ADVANCED VISUALISATION ON MAINFRAME

RMF AND SMF DATA

(APPLYING BIG DATA SOLUTIONS TO IT SYSTEM UTILISATION DATA)

ANDREW GADSBY, MAINFRAME BUSINESS DEVELOPMENTandrew.gadsby@sas.com

MIKE WROOT, MAINFRAME TECHNICAL SPECIALISTmichael.wroot@sas.com

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ABSTRACT ANDREW GADSBY and MIKE WROOT

Title:

Advanced Visualisation and Analytics on Mainframe RMF and SMF Data

(Applying Big Data techniques to IT system utilisation data)

Abstract:

Much has been written about applying analytics to Big Data problems and how advanced visualisation techniques allow

businesses to create new value from Big Data. At SAS we are seeing many customer facing organisations make

extensive use of new visualisation techniques to derive significant business value from the mass of data available to

them.

IT also suffers from its own Big Data problem with the 4 V’s (volume, velocity, variety and variability) applying to IT

systems performance and capacity data. We wondered if it would be possible to apply Big Data visualisation and

analytic techniques to mainframe RMF and SMF data. In particular, we wanted to understand if analysis in this way

could deliver value back into IT.

This session will present an overview of the approach we took to analyse and visualise this data, and illustrate some of

the value that could be derived from such analysis. We will also give a live demonstration of our solution.

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AGENDA ADVANCED VISUALISATION

• Introductions

• How are Your Business Users Looking at their Data?

Demonstration

• How does IT undertake capacity reporting today?

• Linking Visualisation to Capacity Reporting and Forecasting

Demonstration

• Observations and Conclusion

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ACKNOWLEDGEMENT FROM THE MAGIC CIRCLE….

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AGENDA ADVANCED VISUALISATION

• Introductions

• How are Your Business Users Looking at their Data?

Demonstration

• How does IT undertake capacity reporting today?

• Linking Visualisation to Capacity Reporting and Forecasting

Demonstration

• Observations and Conclusion

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“The Greatest Value Of A Picture

Is When It Forces Us To Notice

What We Never Expected To See.”John W. Tukey, Exploratory Data Analysis 1977

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BUSINESS USERS

VIEWVISUALISATION OF BIG DATA

• Visually Exploring Their Data Using Tablets

• User Self Service is Becoming the Norm

• Speed of Thought Investigation and Discovery

• Building Analytical Data Warehouses (ADW)

• Improved Decision Taking Across the Business

• Static Reports are No Longer Acceptable

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Central Entry Point Integration Role-Based Views

DELIVERPREPARE EXPLORE DESIGN

• SAS®

Mobile BI - native tablet applications delivering interactive reports

• Web and PDF

• Manage data• Load and join data• Create calculated

columns

• Perform ad-hoc data exploration

• Insights generated through analytic visualizations

• Create dashboard style reports for web or mobile

IN-MEMORY ANALYTICS ENGINE

SAS®VISUAL

ANALYTICSA SOLUTION FOR FASTER, SMARTER DECISIONS

www.sas.com/visualanalytics

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DEMONSTRATION

SAS® VISUAL ANALYTICS

MEGACORP

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AGENDA ADVANCED VISUALISATION

• Introductions

• How are Your Business Users Looking at their Data?

Demonstration

• How does IT undertake capacity reporting today?

• Linking Visualisation to Capacity Reporting and Forecasting

Demonstration

• Observations and Conclusion

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HOW I.T. LOOKS AT

PERFORMANCE

DATA

VISUALISATION OF I.T. DATA

• Mainframe e.g. MXG, MICS using SMF and RMF data

• Distributed e.g. SAR, NMON…

• Static Reports - GIFs

• Export to Excel

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AGENDA ADVANCED VISUALISATION

• Introductions

• How are Your Business Users Looking at their Data?

Demonstration

• How does IT undertake capacity reporting today?

• Linking Visualisation to Capacity Reporting and Forecasting

Demonstration

• Observations and Conclusion

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LINKING

VISUALISATION TO

I.T. DATA

EXAMPLE HIGH-LEVEL ARCHITECTURE

SAS® VISUAL ANALYTICS ENVIRONMENT

Desktop

Web

Mobile

SAS VA CLIENTS

SMF/RMF

SAR

OpenView

AWR

Workspace Server

Mid-Tier

VA Server

Co-Located Data Storage

Co-Located Data Storage

Co-Located Data Storage

SAS® LASR Analytic Server

LASR Cluster

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DEMONSTRATION

SAS® VISUAL ANALYTICS FOR I.T.

MEGACORP I.T.

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OBSERVATIONS &

CONCLUSIONSVISUALISATION OF I.T. DATA

• Loading and Visualisation of the underlying data was the easy bit

• Understanding what the data means is critical

• Just because you can view things a certain way doesn’t mean it makes sense!

• Good news here as a capacity planning expert you will still keep your job

• Correlation is hard

• Drill down from CPU utilisation at point of time to recreate workload/job step view

is difficult

• Resolving this needs effort at data preparation / load time

• Changes way that capacity planning and forecasting is approached

• Could drive significant reduction in static report production on mainframe (CPU saving ? )

• We are Continuing Development of this Technology and Use Case

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QUESTIONS?

THANK YOU