The document discusses how financial services organizations can rein in spiraling application support costs through addressing four issues: 1) disparate data from different monitoring systems, 2) dysfunctional systems that lack necessary information, 3) demanding and repetitive manual processes, and 4) lack of historical trends for planning. It provides case studies of how large investment banks addressed these issues by implementing an integrated application performance management solution for consolidated monitoring across layers and business units to reduce outages, automate processes, and leverage trend data for planning.

1. Reining in the 4 D’s of SpiralingReining in the 4 D s of Spiraling
Application Support Costs
Marie Hoch, Director of APM Solutions, SL Corporation
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2. The 4 D’s of Spiraling App Support Costs
• Disparate data
• Dysfunctional systems
• Demanding processesDemanding processes
• Divined planning
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3. Disparate Data
• Financial services organizations have multiple layers of
information
– Infrastructure
– Middleware
– Application performance
• Various application support teams are creating their own
monitoring solutions or using their own tools
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4. Disparate Data Case Study:
Large U.S. Investment Bank
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5. Disparate Data Case Study:
Large U.S. Investment Bank
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6. Disparate Data Case Study:
Large U.S. Investment Bank
• Eliminated Sev 1 application performance outages, quickly detecting
root cause of the application problem to meet 15 minute SLAsroot cause of the application problem to meet 15 minute SLAs
• Implemented summary and in-depth dashboard views to monitor:
– Cuts across monitoring silos for more than 100 apps across different
b i itbusiness units
– every layer in their IT landscape
– proactively detect problems
• Business & technical users:
Business metrics
App
Performance
Infrastructure
Performance
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7. Dysfunctional Systems
• Increasing reliance on experts
• Junior support engineers need greater visibility in order
t b ff tito be effective
• Systems are not able to provide the necessary
information for early notification, analysis and resolutioninformation for early notification, analysis and resolution
of issues
• Inability to reduce the noise and focus on issues that
i h b iimpact the business
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8. Dysfunctional Systems Case Study:
Another Large U.S. Investment Bank
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9. Demanding (and Repetitive) Processes
Takes an inordinate amount of time for app support team
members to go out of the monitoring environment to do the
manual checks or reparative actions when errors are
discovered.
There are costs associated with initial and ongoing training
to understand how these checks and fixes should be
performed.
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10. How to Rein in Cost of Demanding Processes
Automate manual processes such as:
• Health checksHealth checks
• Digging through log files
Implement command & control functions such as:
• starting and stopping processes
t UNIX h ll d• system or UNIX shell commands
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11. How to Rein in Cost of Demanding Processes
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12. Divined Planning
• Inability to understand state of transactions and
utilization off of command line administrative utility
• Too many data points to extrapolate meaningful
information and make good decisions – “Crystal Ball”
• Lack of historical trends• Lack of historical trends
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13. Divined Planning
31,500 Data points for
1 hour – Too much!
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14. How to Rein in Cost of Divined Planning
• Get historical metrics over a period of time to understand
usage
• Gain meaningful, correlated views without having to go
to the operations teams
• Leverage trend graphs• Leverage trend graphs
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15. How to Rein in Cost of Divined Planning
How many orders are in the queue?
How many exceptions are in the queue?
How many orders are in the retry queue?
How fast are orders flowing out of the queue?
How fast are orders coming into the queue?
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16. How to Rein in Cost of Divined Planning
Are we there yet?
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17. Thank you for your time!
For more information or to set up a demo, please visit SL in booth
#1513, or contact me at mhoch@sl.com or at +1 415-927-8510.
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