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1© Würth Phoenix … more than software
When Performance Metrics
and User Experience
Come Together
Susanne Greiner, PhD
GrafanaConEU 2018, Amsterdam
http://www.neteye-blog.com/
https://www.linkedin.com/company/wuerth-phoenix
https://www.linkedin.com/in/susanne-greiner-5746ba1b/
 IT and Consulting Company of the Würth-Group
 Headquartered in Italy, Europe-wide presence, more than 160 highly skilled employees
 International experience in Business Software and IT Management
 Core competencies in trading processes, wholesale distribution and logistics
 Microsoft Gold Certified Partner, ITIL certified, OTRS Preferred Partner
2
ABOUT WÜRTH PHOENIX
Facts & figures
 More than 1,000 customers
worldwide
 Over 70 successfully
implemented ERP and CRM
projects
 400 NetEye customers
 HQ in Italy
We improve business productivity by
delivering world class software
solutions with a team of highly
motivated and skilled IT experts
© Würth Phoenix … more than software
3
BUSINESS CRITICAL APPLICATIONS AND PERFORMANCE PROBLEMS
© Würth Phoenix … more than software
Business
Critical
Application
Software
Hardware
Cloud
User
interactions
Virtualization
Internet
Connectivity
…
PERFORMANCE
PROBLEMS
 Are not trivial to solve
 Cost money
→ Avoid them proactively
BUT > 500,000,000 data points a day
4
Performance MOnitoring
© Würth Phoenix … more than software
Heart Rate
Can be influenced by
 Pathology
 Sport
 Breathing
 Drugs
 Temperature
 Dehydration
 Pressure
 Etc.
Monitoring & Alarms
Subject-specific historical data Population data
Expectation
 Time series
 Alarm thresholds
5
Performance MOnitoring
© Würth Phoenix … more than software
Can be influenced by
 Batch requests
 Transactions
 Memory
 SAN
 Network
 Side Processes
 Etc.
Monitoring & Alarms
Machine/setting specific
Historical data
Experience
Data from similar machines/settings
Expectation
 Time series
 Alarm thresholds
Percentage Processor Time
6
A TIME SERIES IS NOT ALONE…
© Würth Phoenix … more than software
Percentage Processor Time
Batch Requests
Transactions
Etc.
 All time series are analyzed together
 Thresholds are calculated dynamically
via baselining and anomaly detection
 AScore estimation in addition to a global
alarm and specific alarms
 Relationships between time series are
used to create more reliable alarms and
risks
 Shape of time series data is considered
Motivations
 Common Data Source
 Grafana & InfluxDB
 Today we need to go beyond common
practice
 Proactivity
Multivariate Data Analysis
7
Performance Monitoring: NetEYE ITOA
© Würth Phoenix … more than software
Moving average
Value range
AScore
Difference between now
and historic data
Effect quantification
8
USER EXPERIENCE
© Würth Phoenix … more than software
“the overall experience of a person using a product such as a website or computer application,
especially in terms of how easy or pleasing it is to use.”
How to monitor user experience?
 VISUAL
Humans look at graphical interfaces and interact with them
 SYNTHETIC
Solution should behave like a human
 MONITORING
Solution should track transaction performance
http://www.alyvix.com/
9
USER EXPERIENCE: Alyvix - active end user monitoring
© Würth Phoenix … more than software
Detailed analysis & Troubleshooting
Cumulative test performance
ordered by test state
● ok
● warning
● critical
● timed out
● not executed
Test performance
ordered by
transaction name
and
transaction group
http://www.alyvix.com/
10
When Performance Metrics and User Experience Come Together
© Würth Phoenix … more than software
 Heterogeneous performance data in one single data source
 Multi-level dashboarding >> Faster troubleshooting
 Historic data on hand >> Easy effect quantification
 ML, Anomaly Detection, Forecasting
11
Performance Monitoring & User Experience
© Würth Phoenix … more than software
Server
Performance
Metrics
Anomaly
Score
Batch
Analysis
Alyvix
User
Experience
12
Multi-Level Dashboards
© Würth Phoenix … more than software
13
TROUBLESHOOTING
© Würth Phoenix … more than software
14
Machine Learning – Anomaly Detection – Forecasting
© Würth Phoenix … more than software
Metrics
MODEL
STANDARD
BEHAVIOR
TRAIN
DATA
• Historical data of same metric
• Historical data of similar metric
• Historical data of similar machine
WHAT DO WE EXPECT?
TEST
DATA
• The farther away from expectations
the higher the AScore
• AScore: different and rare
HOW FAR ARE WE FROM OUR EXPECTATIONS?
ASCORE
15
Machine Learning – Anomaly Detection – Forecasting
© Würth Phoenix … more than software
IOs
HIGH RISK
PERIODS
• Historical data of same metric
• Historical data of similar metric
• Historical data of similar machine
• Historical data of neighbors
• Which (set of) machine(s)
is most probably causing
the high AScore
• Proactive analysis to
prevent congestion
AUTOMATED
ANALYSIS
• Check machines with
high AScore first, there might be
no need to check the others
Proactive search for
potential future suspects
Faster Troubleshooting
16
Desireable FUTURE FEATURES
© Würth Phoenix … more than software
 LDAP folders
 Min/max values, as variables >> passable
 Use time series as annotation
of other time series on mouse over
© Würth Phoenix
www.wuerth-phoenix.com
17… more than software

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GrafanaCon EU 2018

  • 1. 1© Würth Phoenix … more than software When Performance Metrics and User Experience Come Together Susanne Greiner, PhD GrafanaConEU 2018, Amsterdam http://www.neteye-blog.com/ https://www.linkedin.com/company/wuerth-phoenix https://www.linkedin.com/in/susanne-greiner-5746ba1b/
  • 2.  IT and Consulting Company of the Würth-Group  Headquartered in Italy, Europe-wide presence, more than 160 highly skilled employees  International experience in Business Software and IT Management  Core competencies in trading processes, wholesale distribution and logistics  Microsoft Gold Certified Partner, ITIL certified, OTRS Preferred Partner 2 ABOUT WÜRTH PHOENIX Facts & figures  More than 1,000 customers worldwide  Over 70 successfully implemented ERP and CRM projects  400 NetEye customers  HQ in Italy We improve business productivity by delivering world class software solutions with a team of highly motivated and skilled IT experts © Würth Phoenix … more than software
  • 3. 3 BUSINESS CRITICAL APPLICATIONS AND PERFORMANCE PROBLEMS © Würth Phoenix … more than software Business Critical Application Software Hardware Cloud User interactions Virtualization Internet Connectivity … PERFORMANCE PROBLEMS  Are not trivial to solve  Cost money → Avoid them proactively BUT > 500,000,000 data points a day
  • 4. 4 Performance MOnitoring © Würth Phoenix … more than software Heart Rate Can be influenced by  Pathology  Sport  Breathing  Drugs  Temperature  Dehydration  Pressure  Etc. Monitoring & Alarms Subject-specific historical data Population data Expectation  Time series  Alarm thresholds
  • 5. 5 Performance MOnitoring © Würth Phoenix … more than software Can be influenced by  Batch requests  Transactions  Memory  SAN  Network  Side Processes  Etc. Monitoring & Alarms Machine/setting specific Historical data Experience Data from similar machines/settings Expectation  Time series  Alarm thresholds Percentage Processor Time
  • 6. 6 A TIME SERIES IS NOT ALONE… © Würth Phoenix … more than software Percentage Processor Time Batch Requests Transactions Etc.  All time series are analyzed together  Thresholds are calculated dynamically via baselining and anomaly detection  AScore estimation in addition to a global alarm and specific alarms  Relationships between time series are used to create more reliable alarms and risks  Shape of time series data is considered Motivations  Common Data Source  Grafana & InfluxDB  Today we need to go beyond common practice  Proactivity Multivariate Data Analysis
  • 7. 7 Performance Monitoring: NetEYE ITOA © Würth Phoenix … more than software Moving average Value range AScore Difference between now and historic data Effect quantification
  • 8. 8 USER EXPERIENCE © Würth Phoenix … more than software “the overall experience of a person using a product such as a website or computer application, especially in terms of how easy or pleasing it is to use.” How to monitor user experience?  VISUAL Humans look at graphical interfaces and interact with them  SYNTHETIC Solution should behave like a human  MONITORING Solution should track transaction performance http://www.alyvix.com/
  • 9. 9 USER EXPERIENCE: Alyvix - active end user monitoring © Würth Phoenix … more than software Detailed analysis & Troubleshooting Cumulative test performance ordered by test state ● ok ● warning ● critical ● timed out ● not executed Test performance ordered by transaction name and transaction group http://www.alyvix.com/
  • 10. 10 When Performance Metrics and User Experience Come Together © Würth Phoenix … more than software  Heterogeneous performance data in one single data source  Multi-level dashboarding >> Faster troubleshooting  Historic data on hand >> Easy effect quantification  ML, Anomaly Detection, Forecasting
  • 11. 11 Performance Monitoring & User Experience © Würth Phoenix … more than software Server Performance Metrics Anomaly Score Batch Analysis Alyvix User Experience
  • 12. 12 Multi-Level Dashboards © Würth Phoenix … more than software
  • 13. 13 TROUBLESHOOTING © Würth Phoenix … more than software
  • 14. 14 Machine Learning – Anomaly Detection – Forecasting © Würth Phoenix … more than software Metrics MODEL STANDARD BEHAVIOR TRAIN DATA • Historical data of same metric • Historical data of similar metric • Historical data of similar machine WHAT DO WE EXPECT? TEST DATA • The farther away from expectations the higher the AScore • AScore: different and rare HOW FAR ARE WE FROM OUR EXPECTATIONS? ASCORE
  • 15. 15 Machine Learning – Anomaly Detection – Forecasting © Würth Phoenix … more than software IOs HIGH RISK PERIODS • Historical data of same metric • Historical data of similar metric • Historical data of similar machine • Historical data of neighbors • Which (set of) machine(s) is most probably causing the high AScore • Proactive analysis to prevent congestion AUTOMATED ANALYSIS • Check machines with high AScore first, there might be no need to check the others Proactive search for potential future suspects Faster Troubleshooting
  • 16. 16 Desireable FUTURE FEATURES © Würth Phoenix … more than software  LDAP folders  Min/max values, as variables >> passable  Use time series as annotation of other time series on mouse over