Neiman Marcus

1. #Perform2018
Digital experience and transformation
Neiman Marcus's journey into
the cloud with Dynatrace
with an AppMon mindset
Presenter Name
Title
#Perform2018

2. About NeimanMarcus
 Five luxury retailers — Neiman Marcus,
Bergdorf Goodman, Last Call, Horchow
and mytheresa.com — make up the Neiman
Marcus Group.
 Founded in 1907
 42 Neiman Marcus stores across the
United States
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3. About NeimanMarcus
 Two Bergdorf Goodman stores in Manhattan
 29 Last Call clearance centers
 3 Last Call Studios
 Serving online customers including mobile
through ecommerce websites for the last
17 years
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4. Appmon Usage
 Since 2012
 Instrumented in Dev, Preprod and Production
 Heavily used in identifying root cause analysis
 Instrumented in Native apps
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5. What made us look for a different solution?
Digital Transformation
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6. APM Challenges of Digital Transformation
 How to monitor Cloud Infrastructure?
 How to monitor Auto scaling environment?
 How to instrument Dynatrace?
 How to monitor microservices running on docker?
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7. Where is my PurePath?!

8. Found it
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9. That‘s not my PurePath!
Why are they making it
so hard for me to find the
PurePath
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10. First Impressions on Dynatrace
 Why cannot I put every
metric in dashboard like
AppMon?
 Where are my Business
Transactions?
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11. First Impressions on Dynatrace
 How can I trust
this artificial
intelligence?
 What are these
service groups,
process groups
and tags?
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12. What happened next?
 Started a POC
 Instrumented in preprod environment
 Did basic instrumentation and with no additional
configuration
 Tested Dynatrace with various edge case testing
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13. Results
 Auto instrumentation worked as advertised
 Identified the root cause for all edge case scenarios
 OOB Anomaly detection removed the overhead of
manual baselining
 RUM metrics provided much more valuable information
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14. Information Technology
Moved to Production &
Where did Dynatrace excel for us?
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15. Information Technology
Operations Case
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16. Problem Detection: Rabbit MQ
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17. Problem Detection: Rabbit MQ
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Were surprissed that a metric
like this is automatically
covered by AI

18. Problem Detection: Retransmissions Errors
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19. Problem Detection: Retransmission Errors

20. Why do we need Dynatrace when you
have Amazon cloudwatch?
 Does not provide process level monitoring
 Need to build dashboards from scratch
 Metrics are not stored in Artificial Intelligence engine
for anomaly detection
 Does not have Deep dive monitoring capabilities
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21. Information Technology
Mean Time to Detection
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22. Problem Detection at this best
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23. Problem Detection at this best
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24. Identifying the root cause
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25. Identifying the root cause
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26. Information Technology
MTTD with Customer in Mind
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27. Javascript Errors
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28. Javascript Errors

29. Why use Dynatrace Synthetic when we have
Synthetic Classic?
 Single view/portal
 Ease of use. No dependency on Windows OS
 Metrics integrated into the Real user monitoring view
 Data collected into Artificial Intelligence engine
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30. Future roads
 Pull the trigger on AppMon
 Move out off Synthetic Classic
 Plain Infrastructure agents to replace legacy
monitoring solutions
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31. Conclusion
 Best APM solution in market
 AI – works better than expected
 Easier onboarding of apps for monitoring
 MTTD faster than ever
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32. Thank you