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1© 2016 CSAA Insurance Group. Confidential and proprietary.© 2016 CSAA Insurance Group. Confidential and proprietary.
CSAA Insurance Group
Splunking the User Experience
Going Beyond Application Logs
with APM data
Doug Erkkila
2© 2016 CSAA Insurance Group. Confidential and proprietary.
Agenda
Introduction
How We Introduced Splunk – Logs
Expanding Beyond Logs with Dynatrace
Feeding Knowledge Back into Development
Lessons Learned
Questions?
3© 2016 CSAA Insurance Group. Confidential and proprietary.
Who am I?
Doug Erkkila
Capacity Management Analyst
• 10 years as an application
developer
• Specialized in data related
products
• 3 years with CSAA Insurance
Group
• Application Performance
Optimization
• Operational Monitoring
• DevOps
4© 2016 CSAA Insurance Group. Confidential and proprietary.
What is CSAA Insurance Group?
• Insurance company offering
automobile, homeowners and
other personal lines of
insurance to AAA members
through AAA clubs
• More than 3600 employees
coast to coast
• Reaching nearly 17 million
AAA members in 23 states
and Washington DC
5© 2016 CSAA Insurance Group. Confidential and proprietary.
What is PAS?
PAS is the central Policy
Administration System
• Consolidate policy administration
from across different insurance
categories and across different
states into one central system
• A Team of over 300 developers
and analysts
 Optimization Team is 5 Analysts
6© 2016 CSAA Insurance Group. Confidential and proprietary.
In The Beginning:
There were Logs…..
7© 2016 CSAA Insurance Group. Confidential and proprietary.
What Started It All?
Customer complaints about Application Errors (Error 500s)
• Was there an increase in exceptions?
• Difficult to understand error patterns across a cluster of servers
 Was an exception only occurring on a single server?
 Was an exception only occurring at a certain time of day?
• Is this a matter of perception or application quality?
8© 2016 CSAA Insurance Group. Confidential and proprietary.
What Started It All?
A lot of questions, but finding answers was difficult
• Logs were rolled off so exception history was hard to gather
• Difficult to understand error patterns across a cluster of servers
 Any patterns had to come from intimate knowledge of logs
 Wasted support time reading logs every day
• Customer feedback can be sporadic and you tend to hear from the same
small group
9© 2016 CSAA Insurance Group. Confidential and proprietary.
Error 500s
A single measurable use case
• Basic Aggregation and
Trends
10© 2016 CSAA Insurance Group. Confidential and proprietary.
Error 500s
A single measurable use case
• Basic Aggregation and
Trends
• Added categorization
11© 2016 CSAA Insurance Group. Confidential and proprietary.
Error 500s
A single measurable use case
• Basic Aggregation and Trends
• Added categorization
• Segment by Server
12© 2016 CSAA Insurance Group. Confidential and proprietary.
Error 500s
A single measurable use case
• Basic Aggregation and Trends
• Added categorization
• Segment by Server
• Merge user information
13© 2016 CSAA Insurance Group. Confidential and proprietary.
Error 500s
A single measurable use case
• Basic Aggregation and Trends
 Helped us see the increase in exceptions
• Added categorization
 Narrowed down timeframes for specific
errors
• Segment by Server
 Easy to see if the issue was server specific
• Merge user information
 Answered our Perception vs Quality
question
14© 2016 CSAA Insurance Group. Confidential and proprietary.
What Started It All?
Customer complaints about Application Errors (Error 500s)
• Was there an increase in exceptions?
• Difficult to understand error patterns across a cluster of servers
 Was an exception only occurring on a single server?
 Was an exception only occurring at a certain time of day?
• Is this a matter of perception or application quality?
15© 2016 CSAA Insurance Group. Confidential and proprietary.
What Started It All?
Customer complaints about Application Errors (Error 500s)
• Was there an increase in exceptions?
• Difficult to understand error patterns across a cluster of servers
 Was an exception only occurring on a single server?
 Was an exception only occurring at a certain time of day?
• Is this a matter of perception or application quality?
16© 2016 CSAA Insurance Group. Confidential and proprietary.
What Started It All?
Customer complaints about Application Errors (Error 500s)
Was there an increase in exceptions?
Difficult to understand error patterns across a cluster of servers
 Was an exception only occurring on a single server?
 Was an exception only occurring at a certain time of day?
Is this a matter of perception or application quality?
17© 2016 CSAA Insurance Group. Confidential and proprietary.
What Started It All?
Customer complaints about Application Errors (Error 500s)
Was there an increase in exceptions?
Difficult to understand error patterns across a cluster of servers
 Was an exception only occurring on a single server?
 Was an exception only occurring at a certain time of day?
Is this a matter of perception or application quality?
18© 2016 CSAA Insurance Group. Confidential and proprietary.
Changing The Reality
75% reduction in errors
5076 0 1524 1074 5150
1000
2000
3000
4000
5000
6000
March 2014 March 2015 July 2015 January 2016
Without Splunk With Splunk
19© 2016 CSAA Insurance Group. Confidential and proprietary.
Moving Beyond Logs with Dynatrace APM
20© 2016 CSAA Insurance Group. Confidential and proprietary.
The Power of APM
We were already using Dynatrace for
APM
• Method level execution times
• User Experience Management
 Server/Network/Client side load times
 Browser data
• Database Response times
• JVM Heap Stats
Agent
Info
Dynatrace
Performance
Data
User-centered
Performance
Reports
21© 2016 CSAA Insurance Group. Confidential and proprietary.
Exporting Data out of Dynatrace
• Using the Dynatrace REST API
• Nightly scheduled ETL
• Database storage
• Excel based reporting
Before Splunk
Nightly
ETL
Nightly
ETL
Performance
Warehouse
Weekly
Reporting
Excel
Reports
DynatraceVM
22© 2016 CSAA Insurance Group. Confidential and proprietary.
Exporting Data out of Dynatrace
• Not real time
• Limited user population
• Fragile
 Scheduled tasks failed to trigger
 User account credentials changed
frequently
 VM configuration issues
 REST API calls timed out
• Hours spent cleaning up Excel
reports every week
But there were flaws…
23© 2016 CSAA Insurance Group. Confidential and proprietary.
Exporting Data out of Dynatrace
• Real time push from Dynatrace
• Anyone with Splunk access
could get performance data
• Limited areas for interruption
• No manual report modification
• Added additional report types
We addressed those flaws
Flume
Dynatrace
24© 2016 CSAA Insurance Group. Confidential and proprietary.
Real Time Performance View
25© 2016 CSAA Insurance Group. Confidential and proprietary.
Real Time Performance View
26© 2016 CSAA Insurance Group. Confidential and proprietary.
Club Performance Reports
27© 2016 CSAA Insurance Group. Confidential and proprietary.
Club Performance Reports
28© 2016 CSAA Insurance Group. Confidential and proprietary.
Club Performance Reports
29© 2016 CSAA Insurance Group. Confidential and proprietary.
Individual User Performance Trends
30© 2016 CSAA Insurance Group. Confidential and proprietary.
Individual User Performance Trends
31© 2016 CSAA Insurance Group. Confidential and proprietary.
Making Data Available Through Models
32© 2016 CSAA Insurance Group. Confidential and proprietary.
Feeding Back Into Development
33© 2016 CSAA Insurance Group. Confidential and proprietary.
Going Beyond Just Monitoring
• Easily searchable data repository
• Quick long term trending
• Extensible…
34© 2016 CSAA Insurance Group. Confidential and proprietary.
Going Beyond Just Monitoring
• Easily searchable data repository
• Quick long term trending
• Extensible…
35© 2016 CSAA Insurance Group. Confidential and proprietary.
Updating Testing Plans
• Using production
transaction frequency
• More realistic performance
testing
36© 2016 CSAA Insurance Group. Confidential and proprietary.
Performance Comparisons
• Typically baseline to
baseline comparison in
the save environment
• Differences between
production and
performance
environments
• More accurate
understanding forecasts
37© 2016 CSAA Insurance Group. Confidential and proprietary.
Lessons Learned
38© 2016 CSAA Insurance Group. Confidential and proprietary.
Our Splunk Architecture
Splunk started out as a PAS only tool.
PAS
39© 2016 CSAA Insurance Group. Confidential and proprietary.
Our Splunk Architecture
But quickly other teams in the enterprise began using it too.
PAS
SOA Shared Services
40© 2016 CSAA Insurance Group. Confidential and proprietary.
Our Splunk Architecture
PAS
SOA Shared Services Enterprise Analytics
But quickly other teams in the enterprise began using it too.
41© 2016 CSAA Insurance Group. Confidential and proprietary.
Our Splunk Architecture
PAS
SOA Shared Services Enterprise Analytics
UBI
But quickly other teams in the enterprise began using it too.
42© 2016 CSAA Insurance Group. Confidential and proprietary.
Our Splunk Architecture
PAS
SOA Shared Services Enterprise Analytics
UBI
Digital Services
But quickly other teams in the enterprise began using it too.
43© 2016 CSAA Insurance Group. Confidential and proprietary.
Our Splunk Architecture
PAS
SOA Shared Services Enterprise Analytics
UBI
Digital ServicesMRM
But quickly other teams in the enterprise began using it too.
44© 2016 CSAA Insurance Group. Confidential and proprietary.
Keeping up with the times
Splunk added the HTTP Event Collector in Splunk 6.3
Flume
Dynatrace
Dynatrace
45© 2016 CSAA Insurance Group. Confidential and proprietary.
Questions?
46© 2016 CSAA Insurance Group. Confidential and proprietary.
Thank you!

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Going Beyond Logs with APM Data

  • 1. 1© 2016 CSAA Insurance Group. Confidential and proprietary.© 2016 CSAA Insurance Group. Confidential and proprietary. CSAA Insurance Group Splunking the User Experience Going Beyond Application Logs with APM data Doug Erkkila
  • 2. 2© 2016 CSAA Insurance Group. Confidential and proprietary. Agenda Introduction How We Introduced Splunk – Logs Expanding Beyond Logs with Dynatrace Feeding Knowledge Back into Development Lessons Learned Questions?
  • 3. 3© 2016 CSAA Insurance Group. Confidential and proprietary. Who am I? Doug Erkkila Capacity Management Analyst • 10 years as an application developer • Specialized in data related products • 3 years with CSAA Insurance Group • Application Performance Optimization • Operational Monitoring • DevOps
  • 4. 4© 2016 CSAA Insurance Group. Confidential and proprietary. What is CSAA Insurance Group? • Insurance company offering automobile, homeowners and other personal lines of insurance to AAA members through AAA clubs • More than 3600 employees coast to coast • Reaching nearly 17 million AAA members in 23 states and Washington DC
  • 5. 5© 2016 CSAA Insurance Group. Confidential and proprietary. What is PAS? PAS is the central Policy Administration System • Consolidate policy administration from across different insurance categories and across different states into one central system • A Team of over 300 developers and analysts  Optimization Team is 5 Analysts
  • 6. 6© 2016 CSAA Insurance Group. Confidential and proprietary. In The Beginning: There were Logs…..
  • 7. 7© 2016 CSAA Insurance Group. Confidential and proprietary. What Started It All? Customer complaints about Application Errors (Error 500s) • Was there an increase in exceptions? • Difficult to understand error patterns across a cluster of servers  Was an exception only occurring on a single server?  Was an exception only occurring at a certain time of day? • Is this a matter of perception or application quality?
  • 8. 8© 2016 CSAA Insurance Group. Confidential and proprietary. What Started It All? A lot of questions, but finding answers was difficult • Logs were rolled off so exception history was hard to gather • Difficult to understand error patterns across a cluster of servers  Any patterns had to come from intimate knowledge of logs  Wasted support time reading logs every day • Customer feedback can be sporadic and you tend to hear from the same small group
  • 9. 9© 2016 CSAA Insurance Group. Confidential and proprietary. Error 500s A single measurable use case • Basic Aggregation and Trends
  • 10. 10© 2016 CSAA Insurance Group. Confidential and proprietary. Error 500s A single measurable use case • Basic Aggregation and Trends • Added categorization
  • 11. 11© 2016 CSAA Insurance Group. Confidential and proprietary. Error 500s A single measurable use case • Basic Aggregation and Trends • Added categorization • Segment by Server
  • 12. 12© 2016 CSAA Insurance Group. Confidential and proprietary. Error 500s A single measurable use case • Basic Aggregation and Trends • Added categorization • Segment by Server • Merge user information
  • 13. 13© 2016 CSAA Insurance Group. Confidential and proprietary. Error 500s A single measurable use case • Basic Aggregation and Trends  Helped us see the increase in exceptions • Added categorization  Narrowed down timeframes for specific errors • Segment by Server  Easy to see if the issue was server specific • Merge user information  Answered our Perception vs Quality question
  • 14. 14© 2016 CSAA Insurance Group. Confidential and proprietary. What Started It All? Customer complaints about Application Errors (Error 500s) • Was there an increase in exceptions? • Difficult to understand error patterns across a cluster of servers  Was an exception only occurring on a single server?  Was an exception only occurring at a certain time of day? • Is this a matter of perception or application quality?
  • 15. 15© 2016 CSAA Insurance Group. Confidential and proprietary. What Started It All? Customer complaints about Application Errors (Error 500s) • Was there an increase in exceptions? • Difficult to understand error patterns across a cluster of servers  Was an exception only occurring on a single server?  Was an exception only occurring at a certain time of day? • Is this a matter of perception or application quality?
  • 16. 16© 2016 CSAA Insurance Group. Confidential and proprietary. What Started It All? Customer complaints about Application Errors (Error 500s) Was there an increase in exceptions? Difficult to understand error patterns across a cluster of servers  Was an exception only occurring on a single server?  Was an exception only occurring at a certain time of day? Is this a matter of perception or application quality?
  • 17. 17© 2016 CSAA Insurance Group. Confidential and proprietary. What Started It All? Customer complaints about Application Errors (Error 500s) Was there an increase in exceptions? Difficult to understand error patterns across a cluster of servers  Was an exception only occurring on a single server?  Was an exception only occurring at a certain time of day? Is this a matter of perception or application quality?
  • 18. 18© 2016 CSAA Insurance Group. Confidential and proprietary. Changing The Reality 75% reduction in errors 5076 0 1524 1074 5150 1000 2000 3000 4000 5000 6000 March 2014 March 2015 July 2015 January 2016 Without Splunk With Splunk
  • 19. 19© 2016 CSAA Insurance Group. Confidential and proprietary. Moving Beyond Logs with Dynatrace APM
  • 20. 20© 2016 CSAA Insurance Group. Confidential and proprietary. The Power of APM We were already using Dynatrace for APM • Method level execution times • User Experience Management  Server/Network/Client side load times  Browser data • Database Response times • JVM Heap Stats Agent Info Dynatrace Performance Data User-centered Performance Reports
  • 21. 21© 2016 CSAA Insurance Group. Confidential and proprietary. Exporting Data out of Dynatrace • Using the Dynatrace REST API • Nightly scheduled ETL • Database storage • Excel based reporting Before Splunk Nightly ETL Nightly ETL Performance Warehouse Weekly Reporting Excel Reports DynatraceVM
  • 22. 22© 2016 CSAA Insurance Group. Confidential and proprietary. Exporting Data out of Dynatrace • Not real time • Limited user population • Fragile  Scheduled tasks failed to trigger  User account credentials changed frequently  VM configuration issues  REST API calls timed out • Hours spent cleaning up Excel reports every week But there were flaws…
  • 23. 23© 2016 CSAA Insurance Group. Confidential and proprietary. Exporting Data out of Dynatrace • Real time push from Dynatrace • Anyone with Splunk access could get performance data • Limited areas for interruption • No manual report modification • Added additional report types We addressed those flaws Flume Dynatrace
  • 24. 24© 2016 CSAA Insurance Group. Confidential and proprietary. Real Time Performance View
  • 25. 25© 2016 CSAA Insurance Group. Confidential and proprietary. Real Time Performance View
  • 26. 26© 2016 CSAA Insurance Group. Confidential and proprietary. Club Performance Reports
  • 27. 27© 2016 CSAA Insurance Group. Confidential and proprietary. Club Performance Reports
  • 28. 28© 2016 CSAA Insurance Group. Confidential and proprietary. Club Performance Reports
  • 29. 29© 2016 CSAA Insurance Group. Confidential and proprietary. Individual User Performance Trends
  • 30. 30© 2016 CSAA Insurance Group. Confidential and proprietary. Individual User Performance Trends
  • 31. 31© 2016 CSAA Insurance Group. Confidential and proprietary. Making Data Available Through Models
  • 32. 32© 2016 CSAA Insurance Group. Confidential and proprietary. Feeding Back Into Development
  • 33. 33© 2016 CSAA Insurance Group. Confidential and proprietary. Going Beyond Just Monitoring • Easily searchable data repository • Quick long term trending • Extensible…
  • 34. 34© 2016 CSAA Insurance Group. Confidential and proprietary. Going Beyond Just Monitoring • Easily searchable data repository • Quick long term trending • Extensible…
  • 35. 35© 2016 CSAA Insurance Group. Confidential and proprietary. Updating Testing Plans • Using production transaction frequency • More realistic performance testing
  • 36. 36© 2016 CSAA Insurance Group. Confidential and proprietary. Performance Comparisons • Typically baseline to baseline comparison in the save environment • Differences between production and performance environments • More accurate understanding forecasts
  • 37. 37© 2016 CSAA Insurance Group. Confidential and proprietary. Lessons Learned
  • 38. 38© 2016 CSAA Insurance Group. Confidential and proprietary. Our Splunk Architecture Splunk started out as a PAS only tool. PAS
  • 39. 39© 2016 CSAA Insurance Group. Confidential and proprietary. Our Splunk Architecture But quickly other teams in the enterprise began using it too. PAS SOA Shared Services
  • 40. 40© 2016 CSAA Insurance Group. Confidential and proprietary. Our Splunk Architecture PAS SOA Shared Services Enterprise Analytics But quickly other teams in the enterprise began using it too.
  • 41. 41© 2016 CSAA Insurance Group. Confidential and proprietary. Our Splunk Architecture PAS SOA Shared Services Enterprise Analytics UBI But quickly other teams in the enterprise began using it too.
  • 42. 42© 2016 CSAA Insurance Group. Confidential and proprietary. Our Splunk Architecture PAS SOA Shared Services Enterprise Analytics UBI Digital Services But quickly other teams in the enterprise began using it too.
  • 43. 43© 2016 CSAA Insurance Group. Confidential and proprietary. Our Splunk Architecture PAS SOA Shared Services Enterprise Analytics UBI Digital ServicesMRM But quickly other teams in the enterprise began using it too.
  • 44. 44© 2016 CSAA Insurance Group. Confidential and proprietary. Keeping up with the times Splunk added the HTTP Event Collector in Splunk 6.3 Flume Dynatrace Dynatrace
  • 45. 45© 2016 CSAA Insurance Group. Confidential and proprietary. Questions?
  • 46. 46© 2016 CSAA Insurance Group. Confidential and proprietary. Thank you!

Editor's Notes

  1. Our relationship is unique We don’t work directly with the agents We work with the partner agencies who relate with the agents This adds additional communications steps and can limit visibility into customer experience
  2. CSAA maintains a mix of legacy platforms but PAS is a single transformational project to migrate insurance policies from those legacy systems (some from as early as the 1970s) to a single modern platform.
  3. CSAA maintains a mix of legacy platforms but PAS is a single transformational project to migrate insurance policies from those legacy systems (some from as early as the 1970s) to a single modern platform.
  4. Transaction records only provide so much information, what if an error prevented a transaction from even happening?
  5. Grown the business on the platform (over 1 million policies) while reducing the number of exceptions. Business was no longer focused on errors, freeing our time to turn to other areas of optimization.